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AI can improve federal service delivery, citizen survey says

Federal employees received high marks for their work. At the same time, the public also wants more from them, and federal agencies more broadly, especially around technology.

These are among the top findings of a survey of a thousand likely voters from last August by the Center for Accountability, Modernization and Innovation (CAMI).

Stan Soloway, the chairman of the board for CAMI, said the findings demonstrate at least two significant issues for federal executives to consider.

Stan Soloway is the chairman of the board for the Center for Accountability, Modernization and Innovation (CAMI).

โ€œIt very clear to us from the survey was that public actually has faith, to a certain extent, in public employees. The public also fully recognizes that the system itself is not serving them well,โ€ Soloway said on Ask the CIO. โ€œWe found well over half of the folks that were surveyed said that they didnโ€™t believe that government services are efficient. We found just under half of respondents had a favorable impression of government workers. And I think this is very much I respect my local civil servant because I know what they do, but I have a lot of skepticism about government writ large.โ€

CAMI, a non-partisan think tank, found that when it comes to government workers:

  • 47% favorable vs 38% unfavorable toward government workers (+9% net)
  • Self-identified very conservative voters showed strong support (+30% net)
  • African Americans showed the highest favorability (+31% net)
  • Self-identified independents are the exception, showing negative views (-14% net)

At the same time, when it comes to government services, CAMI found 54% of the respondents believe agencies arenโ€™t as efficient or as timely as they should be.

John Faso, a former Republican congressman from New York and a senior advisor for CAMI, said the call for more efficiencies and timeliness from citizens echoes a long-time goal of bringing federal agencies closer to the private sector.

โ€œPeople, and we see this in the survey, look at what government provides and how they provide it, and then to what theyโ€™re maybe accustomed to in private sector economy,โ€ Faso said. โ€œAmazon is a prime example. You can sit home and order something, a food product, an item of clothing or something else you want for your house or your family, and oftentimes itโ€™s there within a day or two. People are accustomed to getting that kind of service. People have an expectation that the government can do that. I think government is lagging, obviously, but itโ€™s catching up, and it needs to catch up fast.โ€

Faso said itโ€™s clear that a solid percentage of the reason for why the government is inefficient comes back to Congress. But at the same time, the CAMI survey demonstrated that there are things federal executives could do to address many of these long-standing challenges.

CAMI says respondents supported several changes to improve timely and efficient delivery of benefits:

  • 40% preferred hiring more government workers
  • 34% preferred partnering with outside organizations
  • Those self-identified as very liberal voters strongly favored more workers (+32% net)
  • Those identified as somewhat conservative voters prefer outside partnerships (-20% net)
  • Older voters (55+) preferred outside partnerships

โ€œWhether itโ€™s the Supplemental Nutrition Assistance Program (SNAP) or Medicaid and Medicare, the feds set all the rules for the administration and governance of the programs. So the first question you have to ask is, what is the federal role?โ€ Soloway said. โ€œEven though we have now shifted administrative responsibility for many programs to the states and to some cases, the counties, and reduced by 50% the financial support for administration of these programs, while the states have a lot to figure out and are somewhat panicked about it, because itโ€™s a huge lift. The feds canโ€™t just walk away. This is where we have issues of policy changes that are needed at the federal level, which we can talk about some of the ones that are desperately needed to give the states kind of the flexibility to innovate.โ€

Soloway added this also means agencies have to break down long-established siloes both around data and processes.

The Trump administration, for example, has prioritized data sharing across the government, especially to combat concerns around fraud. The Office of Management and Budget said in July it was supercharging the Do Not Pay list by removing the barriers to governmentwide data sharing.

Soloway said this is a prime example of where the private sector has figured out how to get different parts of their organization to talk to each other and where the government is lagging.

โ€œWhat is the federal role in helping to break down the silos and integrate applications, and to the certain extent help with the administration of programs with like beneficiaries? The data is pretty clear that thereโ€™s a lot of commonality across multiple programs, and when you think about the number of different departments and the bureaucracy that actually control those programs, thereโ€™s got to be leadership at the federal level, both on technology and to expand process transformation, otherwise youโ€™re not going to solve the problem,โ€ he said. โ€œThe second thing is when we talk about issues like program integrity, there are ways you can combat fraud and also protect the beneficiaries. But too often, the conversations are either/or any effort to combat fraud is seen as an effort to take eligible people off the rolls. Every effort to protect eligible people on the rolls is seen as just feeding into that so thatโ€™s where the federal leadership, and some of that is in technology, some of itโ€™s in policy. Some of itโ€™s going to be in resources, because it requires investments in technology across the board, state and federal.โ€

Respondents say technology can play a bigger role in improving the delivery of federal services.

CAMI says respondents offered strong support for using AI to improve government service delivery:

  • 48% support vs 29% oppose using AI tools (net +19%)
  • Self-identified republicans show stronger support than democrats (+36% vs +7% net)
  • Men are significantly more supportive than women (+35% vs +3% net)
  • Support is strongest among middle-aged voters (30-44: +40% net)

Soloway said CAMI is sharing its survey findings with both Congress and the executive branch.

โ€œWeโ€™re trying to get the conversations going and get the information to the right people. When we do that, we find, by and large, on both sides, thereโ€™s a lot of support to do stuff. The question is going to really be, whereโ€™s the leadership going to come from that will have the enough credibility on both sides to push this ball forward?โ€ Soloway said.

Faso added state governments also must play a big role in improving program delivery.

โ€œYou have cost sharing between the federal and state governments, and you have cost sharing in terms of the administrative burden to implement these programs. I think a lot of governors, frankly, are now really looking at themselves and saying, โ€˜How am I going to implement this?โ€™โ€ he said. โ€œHow do I collaborate with the federal government to make sure that weโ€™re all enrolling in the same direction in terms of implementing these requirements.โ€

The post AI can improve federal service delivery, citizen survey says first appeared on Federal News Network.

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์ผ๋ฌธ์ผ๋‹ต | ์ผ๋ณธ ์™ธ์‹ ๊ธฐ์—…์˜ ๊ธ€๋กœ๋ฒŒ ๋„์•ฝ, ํŠธ๋ฆฌ๋„๋ฅด CIO๊ฐ€ ๋งํ•˜๋Š” ๋ณ€ํ™”์— ๊ฐ•ํ•œ IT ์ „๋žต

์šฐ๋™ ๋ธŒ๋žœ๋“œ ๋งˆ๋ฃจ๊ฐ€๋ฉ”์ œ๋ฉด ๋“ฑ์„ ์šด์˜ํ•˜๋Š” ์ผ๋ณธ ์™ธ์‹ ๊ธฐ์—… ํŠธ๋ฆฌ๋„๋ฅดํ™€๋”ฉ์Šค๋Š” ๊ธ€๋กœ๋ฒŒ ์‹œ์žฅ ํ™•์žฅ์„ ๋ชฉํ‘œ๋กœ ๋””์ง€ํ„ธ๊ณผ IT ๊ธฐ๋ฐ˜์˜ ๊ฒฝ์˜ ํ˜์‹ ์— ์†๋„๋ฅผ ๋‚ด๊ณ  ์žˆ๋‹ค. ์ด ๊ณผ์ •์—์„œ ์‹œ์Šคํ…œ ์ „๋ฉด ํ˜„๋Œ€ํ™”์™€ ์กฐ์ง ๊ฐœํŽธ, SaaSยทAI ํ™œ์šฉ๊นŒ์ง€ ์ง์ ‘ ์ด๋Œ์–ด ์˜จ CIO ์ด์†Œ๋ฌด๋ผ ์•ผ์Šค๋…ธ๋ฆฌ(็ฃฏๆ‘ๅบทๅ…ธ)๊ฐ€ ๋ฒค๋” ๊ฒฝํ—˜๊ณผ ๊ฒฝ์˜ ์‹œ๊ฐ์„ ๋ฐ”ํƒ•์œผ๋กœ ๋ณ€ํ™”์— ๊ฐ•ํ•œ ๊ธฐ์—… ๊ธฐ๋ฐ˜์„ ๊ตฌ์ถ•ํ•˜๋Š” ์ „๋žต๊ณผ ์ฒ ํ•™์„ ์ œ์‹œํ–ˆ๋‹ค.

Q(CIO์žฌํŒฌ) : ์ง€๊ธˆ๊นŒ์ง€์˜ ๊ฒฝ๋ ฅ์— ๋Œ€ํ•ด ์„ค๋ช…ํ•ด ๋‹ฌ๋ผ.
A(์ด์†Œ๋ฌด๋ผ ์•ผ์Šค๋…ธ๋ฆฌ) : ์ปค๋ฆฌ์–ด๋Š” ํ›„์ง€์“ฐ์—์„œ ์‹œ์ž‘ํ–ˆ๋‹ค. ์•ฝ 7๋…„ ๋™์•ˆ ์ฃผ๋กœ ๊ณต๊ณต ๋ถ€๋ฌธ ์‹œ์Šคํ…œ์„ ๋‹ด๋‹นํ•˜๋Š” ์‹œ์Šคํ…œ ์—”์ง€๋‹ˆ์–ด๋กœ ์ผํ•˜๋ฉฐ ํ˜„์žฅ์—์„œ ๊ธฐ์ˆ  ์—ญ๋Ÿ‰์„ ๋‹ค์ ธ์™”๋‹ค.

์ดํ›„ 2000๋…„ ์†Œํ”„ํŠธ๋ฑ…ํฌ(ํ˜„ ์†Œํ”„ํŠธ๋ฑ…ํฌ๊ทธ๋ฃน)๋กœ ์ด์งํ–ˆ๋‹ค. ๋‹น์‹œ ์†์ •์˜ ํšŒ์žฅ์ด โ€œ์•ž์œผ๋กœ๋Š” ์ธํ„ฐ๋„ท ์‹œ๋Œ€โ€๋ผ๊ณ  ๊ฐ•์กฐํ•˜๋˜ ์‹œ๊ธฐ๋กœ, ์‚ฌ๋‚ด์—์„œ๋Š” ์ธํ„ฐ๋„ท ๊ด€๋ จ ๋ฒค์ฒ˜๊ฐ€ ์ž‡๋”ฐ๋ผ ์ถœ๋ฒ”ํ•˜๊ณ  ์žˆ์—ˆ๋‹ค. ๊ทธ์ค‘ ํ•˜๋‚˜๊ฐ€ ์ „์ž์ƒ๊ฑฐ๋ž˜ ์‚ฌ์—…์œผ๋กœ, ํ˜„์žฌ์˜ ์„ธ๋ธ๋„ท์‡ผํ•‘์ด๋‹ค. ๋‚˜๋Š” ์‹œ์Šคํ…œ ์ฑ…์ž„์ž๋กœ ์‚ฌ์—… ์ถœ๋ฒ”์— ์ฐธ์—ฌํ•ด ์•ฝ 8๋…„ ๋™์•ˆ ์‚ฌ์—… ์„ฑ์žฅ์„ ๋’ท๋ฐ›์นจํ•˜๋Š” ์—ญํ• ์„ ๋งก์•˜๋‹ค.

๋‹ค์Œ์œผ๋กœ ๋„์ „ํ•œ ๊ณณ์€ ์™ธ์‹ IT ๋ฒค์ฒ˜ ๊ฐˆํ”„๋„ท์ด๋‹ค. ํŠธ๋ฆฌ๋„๋ฅดํ™€๋”ฉ์Šค๋ฅผ ๋น„๋กฏํ•œ ์ฃผ์š” ์™ธ์‹ ์ฒด์ธ์„ ๊ณ ๊ฐ์œผ๋กœ ๋‘” ํšŒ์‚ฌ๋กœ, ์ด๊ณณ์—์„œ 4๋…„ ๋™์•ˆ ๊ฐœ๋ฐœ ์ฑ…์ž„์ž๋กœ ์‹œ์Šคํ…œ์„ ์ด๋Œ์—ˆ์„ ๋ฟ ์•„๋‹ˆ๋ผ ์˜์—… ์ฑ…์ž„์ž ์—ญํ• ๋„ ๊ฒฝํ—˜ํ–ˆ๋‹ค. ๊ธฐ์ˆ ๋ฟ ์•„๋‹ˆ๋ผ ๋น„์ฆˆ๋‹ˆ์Šค ํ˜„์žฅ์„ ์ง์ ‘ ์›€์ง์ด๋Š” ์–ด๋ ค์›€๊ณผ ์žฌ๋ฏธ๋ฅผ ์ฒด๊ฐํ•  ์ˆ˜ ์žˆ์—ˆ๋˜ ์ ์€ ํฐ ์ˆ˜ํ™•์ด์—ˆ๋‹ค.

์ดํ›„ ํˆฌ์žํšŒ์‚ฌ ์˜คํฌ์บํ”ผํƒˆ(ํ˜„ UNIVAยท์˜คํฌํ™€๋”ฉ์Šค)๋กœ ์ž๋ฆฌ๋ฅผ ์˜ฎ๊ฒจ ์•ฝ 8๋…„๊ฐ„ ํˆฌ์ž ๊ธฐ์—…์— ํ•ธ์ฆˆ์˜จ์œผ๋กœ ๊ด€์—ฌํ–ˆ๋‹ค. ๊ฒฝ์˜ ์žฌ๊ฑด๊ณผ ๊ธฐ์—… ๊ฐ€์น˜ ์ œ๊ณ ๋ฅผ ์ถ”์ง„ํ–ˆ๊ณ , ๊ฒฝ์šฐ์— ๋”ฐ๋ผ์„œ๋Š” ์ง์ ‘ ๋Œ€ํ‘œ์ด์‚ฌ๋ฅผ ๋งก๋Š” ๋“ฑ ๊ฒฝ์˜ ์ „๋ฐ˜์— ๊นŠ์ด ๊ด€์—ฌํ•˜๋Š” ๊ฒฝํ—˜์„ ์Œ“์•˜๋‹ค. ์ด ์‹œ๊ธฐ์— ํ˜•์„ฑ๋œ โ€˜์‚ฌ์—…์„ ์–ด๋–ป๊ฒŒ ์žฌ์ •๋น„ํ•˜๊ณ  ์„ฑ์žฅ์œผ๋กœ ์ด๋Œ ๊ฒƒ์ธ๊ฐ€โ€™๋ผ๋Š” ๊ด€์ ์€ ์ง€๊ธˆ์˜ ์ค‘์š”ํ•œ ์ž์‚ฐ์ด ๋˜๊ณ  ์žˆ๋‹ค.

๊ทธ๋ฆฌ๊ณ  2019๋…„ ํŠธ๋ฆฌ๋„๋ฅดํ™€๋”ฉ์Šค CIO๋กœ ๋ถ€์ž„ํ–ˆ๋‹ค. ์–ด๋А๋ง 6๋…„์ด ์ง€๋‚œ ํ˜„์žฌ, ๋ฒค๋”๋กœ์„œ ์ถ•์ ํ•œ ์ง€์‹๊ณผ ์‚ฌ์—…ํšŒ์‚ฌ์—์„œ์˜ ๊ฒฝํ—˜, ๊ฒฝ์˜์ž๋กœ์„œ์˜ ์‹œ๊ฐ์„ ๋ชจ๋‘ ํ™œ์šฉํ•ด ์‚ฌ์—… ์„ฑ์žฅ์„ ๊ฒฌ์ธํ•˜๋Š” CIO๋กœ์„œ ๋„์ „์„ ์ด์–ด๊ฐ€๊ณ  ์žˆ๋‹ค.

Q : ์ง€๊ธˆ๊นŒ์ง€์˜ ๊ฒฝ๋ ฅ ๊ฐ€์šด๋ฐ ํŠนํžˆ ์ธ์ƒ์— ๋‚จ๋Š” ์ผ์€ ๋ฌด์—‡์ธ๊ฐ€.
A : ๋Œ์•„๋ณด๋ฉด ๊ฐ ์—…์ข…๊ณผ ์—ญํ• ๋งˆ๋‹ค ํฐ ๋„์ „์ด ์žˆ์—ˆ๋‹ค. ์ฒ˜์Œ SI ์—…๋ฌด๋ฅผ ๋งก์•˜์„ ๋•Œ๋Š” ์–ผ๋งˆ๋‚˜ ํฐ ๊ทœ๋ชจ์˜ ํ”„๋กœ์ ํŠธ๋ฅผ ์šด์˜ํ•  ์ˆ˜ ์žˆ๋Š”์ง€๊ฐ€ ์„ฑ์žฅ์˜ ๊ธฐ์ค€์ด์—ˆ๋‹ค. ๋‹น์‹œ 20๋Œ€์— 800์ธ์›”(ไบบๆœˆ, ์—ฌ๋Ÿฌ ์ธ๋ ฅ์ด ์ˆ˜๊ฐœ์›” ์ด์ƒ ํˆฌ์ž…๋ผ, ์ธ๋ ฅ ์ˆ˜ร—ํˆฌ์ž… ๊ฐœ์›” ์ˆ˜๋ฅผ ํ•ฉ์‚ฐํ•˜๋ฉด 800์— ์ด๋ฅด๋Š”) ๊ทœ๋ชจ์˜ ํ”„๋กœ์ ํŠธ๋ฅผ ๋งก์•˜๋Š”๋ฐ, ์ง€๊ธˆ ์ƒ๊ฐํ•ด ๋ณด๋ฉด ์ Š์€ ์‹œ์ ˆ์— ์ƒ๋‹นํžˆ ํฐ ์ฑ…์ž„์„ ๋งก๊ธธ ๋งŒํผ ๊ธฐํšŒ๋ฅผ ์ฃผ๋˜ ํšŒ์‚ฌ์˜€๋‹ค๊ณ  ๋А๋‚€๋‹ค.

์†Œํ”„ํŠธ๋ฑ…ํฌ์—์„œ๋Š” ์ฒ˜์Œ์œผ๋กœ โ€˜๋น„์ฆˆ๋‹ˆ์Šค๋ฅผ ๋งŒ๋“ ๋‹คโ€™๋Š” ์ผ์— ๋„์ „ํ–ˆ๋‹ค. ๋‹ด๋‹นํ•œ ๊ฒƒ์€ ํ˜„์žฌ์˜ ์„ธ๋ธ๋„ท์‡ผํ•‘์œผ๋กœ ์ด์–ด์ง€๋Š” ์ „์ž์ƒ๊ฑฐ๋ž˜ ์‚ฌ์—…์ด๋‹ค. ๋งค์ถœ์ด ์ „ํ˜€ ์—†๋Š” ์ƒํƒœ์—์„œ ์ถœ๋ฐœํ•ด, ์‹œ์Šคํ…œ ์ฑ…์ž„์ž๋กœ์„œ ์‚ฌ์—…์ด ์•ฝ 200์–ต ์—” ๊ทœ๋ชจ๋กœ ์„ฑ์žฅํ•˜๋Š” ๊ณผ์ •์„ ๋’ท๋ฐ›์นจํ–ˆ๋‹ค. ๋‹จ์ˆœํ•œ ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ์ด ์•„๋‹ˆ๋ผ, ๋น„์ฆˆ๋‹ˆ์Šค ์„ฑ์žฅ๊ณผ ์ง์ ‘์ ์œผ๋กœ ์—ฐ๊ฒฐ๋œ ๊ฒฝํ—˜์ด์—ˆ๋‹ค๋Š” ์ ์—์„œ ์ปค๋ฆฌ์–ด ์ „๋ฐ˜์— ๋งค์šฐ ํฐ ์˜๋ฏธ๋ฅผ ๋‚จ๊ฒผ๋‹ค.

ํ˜„์ง์ธ ํŠธ๋ฆฌ๋„๋ฅดํ™€๋”ฉ์Šค CIO๋กœ์„œ ์ฒ˜์Œ ๋งก์€ ํฐ ๊ณผ์ œ๋Š” ์ „์‚ฌ ์‹œ์Šคํ…œ์˜ ์ „๋ฉด์ ์ธ ํ˜„๋Œ€ํ™”์˜€๋‹ค. ๋ถ€์ž„ ์ดํ›„ ์•ฝ 6๋…„์— ๊ฑธ์ณ ์ถ”์ง„ํ•ด ์™”๊ณ , ์ด์ œ ๋ชจ๋“  ๊ต์ฒด ์ž‘์—…์ด ๋งˆ๋ฌด๋ฆฌ ๋‹จ๊ณ„์— ์ด๋ฅด๊ณ  ์žˆ๋‹ค.

๋‹น์ดˆ์—๋Š” 3๋…„ ๋‚ด ์™„๋ฃŒ๋ฅผ ๋ชฉํ‘œ๋กœ ํ–ˆ์ง€๋งŒ, ์‚ฌ๋‚ด ์‚ฌ์ •๊ณผ ๊ธฐ์กด ๊ตฌ์กฐ๋ฅผ ์„ธ์‹ฌํ•˜๊ฒŒ ๊ณ ๋ คํ•˜๋ฉฐ ์ง„ํ–‰ํ•  ํ•„์š”๊ฐ€ ์žˆ์—ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ์†๋„๋ณด๋‹ค ์™„์„ฑ๋„๋ฅผ ํƒํ•ด ์‹œ๊ฐ„์ด ๊ฑธ๋ฆฌ๋”๋ผ๋„ ํ™•์‹คํžˆ ๋๋‚ด๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์ถ”์ง„ํ•˜๊ฒŒ ๋๋‹ค.

ํ”„๋กœ์ ํŠธ์˜ ์ถœ๋ฐœ์ ์€ โ€˜์‹œ์Šคํ…œ์ด ๋ช‡ ๊ฐœ๋‚˜ ์žˆ๋Š”์ง€๋ฅผ ํŒŒ์•…ํ•˜๋Š” ๊ฒƒโ€™์ด์—ˆ๋‹ค. ์ฒ˜์Œ ์ ๊ฒ€ํ–ˆ์„ ๋•Œ ์•ฝ 180๊ฐœ์˜ ์‹œ์Šคํ…œ์ด ์กด์žฌํ–ˆ๊ณ , ์ดํ›„ ์—…๋ฌด ๋ชฉ์ ์— ๋”ฐ๋ผ ์žฌ์ •๋ฆฌํ•˜๋ฉฐ ํ†ตํ•ฉ์„ ์ง„ํ–‰ํ–ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ํ˜„์žฌ๋Š” ์•ฝ 40๊ฐœ ์ˆ˜์ค€๊นŒ์ง€ ๋Œ€ํญ ์ค„์ผ ์ˆ˜ ์žˆ์—ˆ๋‹ค.

์ด ๊ณผ์ •์„ ๋Œ์•„๋ณด๋ฉด, ์‹œ์Šคํ…œ ์ž์‚ฐ ์ •๋ฆฌ๋ถ€ํ„ฐ ํ˜„๋Œ€ํ™”๊นŒ์ง€ ์ „ ๊ณผ์ •์„ ์ง์ ‘ ์ด๋Œ์–ด ์˜จ ๊ฒฝํ—˜์€ CIO๋กœ์„œ ๊ฐ€์žฅ ์ฒ˜์Œ์— ๋„์ „ํ•˜๊ธฐ์— ๊ฑธ๋งž์€ ๊ณผ์ œ์˜€๋‹ค๊ณ  ์ƒ๊ฐํ•œ๋‹ค.

Q : ๊ฐ€์žฅ ์–ด๋ ค์› ๋˜ ๊ฒฝํ—˜์€ ๋ฌด์—‡์ธ๊ฐ€.
A : ๊ฐ€์žฅ ์‹ ๊ฒฝ์„ ๋งŽ์ด ์“ด ์ผ์€ ํŠธ๋ฆฌ๋„๋ฅดํ™€๋”ฉ์Šค์—์„œ ์ถ”์ง„ํ•œ ์—…๋ฌด ์กฐ์ง ๊ฐœํŽธ์ด์—ˆ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ๋Š” ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์˜ ๋ณธ์‚ฌ ์—…๋ฌด๋ฅผ ์ง€์ฃผํšŒ์‚ฌ์™€ ์‰์–ด๋“œ์„œ๋น„์Šค ํšŒ์‚ฌ(๊ทธ๋ฃน ๊ณตํ†ต ๊ด€๋ฆฌยท์šด์˜ ์—…๋ฌด๋ฅผ ํ†ตํ•ฉ ์ˆ˜ํ–‰ํ•˜๋Š” ์กฐ์ง)๋กœ ์—ญํ• ์„ ๋‚˜๋ˆ  ์žฌ๊ตฌ์„ฑํ–ˆ๋‹ค. ์ดํ›„ ํšŒ๊ณ„ยท์ธ์‚ฌยทIT ์šด์˜ ๋“ฑ ๋ฐ˜๋ณต์ ์ธ ๊ด€๋ฆฌ ์—…๋ฌด๋ฅผ ๋‚ด๋ถ€ ์กฐ์ง์ด ์•„๋‹Œ ์™ธ๋ถ€ ์ „๋ฌธ ์œ„ํƒ์—…์ฒด(Business Process Outsourcing, BPO)์— ๋งก๊ธฐ๋Š” ๋ฐฉ์‹์œผ๋กœ ์šด์˜ ๊ตฌ์กฐ๋ฅผ ๋ฐ”๊ฟจ๋‹ค.

์‚ฌ๋‚ด์—์„œ ์ˆ˜ํ–‰ํ•˜๋˜ ์—…๋ฌด๋ฅผ ์™ธ๋ถ€๋กœ ์˜ฎ๊ธฐ๋Š” ๊ณผ์ •์€ ๋Œ€๋‹ดํ•˜๋ฉด์„œ๋„ ๋งค์šฐ ์„ฌ์„ธํ•œ ์กฐ์ •์ด ํ•„์š”ํ•œ ํ”„๋กœ์ ํŠธ์˜€๋‹ค. ์šฐ์„  IT ๋ถ€๋ฌธ๋ถ€ํ„ฐ ์ฐฉ์ˆ˜ํ–ˆ๋Š”๋ฐ, ์ด ๊ณผ์ •์ด ๊ฐ€์žฅ ์–ด๋ ค์› ๋‹ค.

๋‹น์‹œ ๋‚˜๋Š” ์‰์–ด๋“œ์„œ๋น„์Šค ํšŒ์‚ฌ์˜ ๋Œ€ํ‘œ๋ฅผ ๊ฒธ์ž„ํ•˜๋ฉฐ ์ตœ๋Œ€ ์•ฝ 180๋ช…์˜ ์ธ๋ ฅ์„ ์ด๋Œ๊ณ  ์žˆ์—ˆ๋‹ค. ์ด ์กฐ์ง์—๋Š” IT ์šด์˜ํŒ€๋ฟ ์•„๋‹ˆ๋ผ ํšŒ๊ณ„ ๊ธฐ์žฅ์„ ๋‹ด๋‹นํ•˜๋Š” ์žฌ๋ฌด ์กฐ์ง, ๊ธ‰์—ฌ ๊ณ„์‚ฐ์„ ๋งก์€ ์ธ์‚ฌ ์กฐ์ง ๋“ฑ ์ด๋ฅธ๋ฐ” ์˜คํผ๋ ˆ์ด์…˜ ๊ธฐ๋Šฅ์ด ์ง‘์•ฝ๋ผ ์žˆ์—ˆ๋‹ค. ์ „๋žต ์ˆ˜๋ฆฝ์€ ์ง€์ฃผํšŒ์‚ฌ๊ฐ€ ๋งก๊ณ , ์ผ์ƒ์ ์ธ ์˜คํผ๋ ˆ์ด์…˜์€ ํ•˜๋‚˜๋กœ ๋ฌถ์–ด ๊ด€๋ฆฌํ•˜๋Š” ์ฒด์ œ๋ฅผ ๊ฐ–์ถ”๊ณ  ์žˆ์—ˆ์œผ๋ฉฐ, ์ด ๊ฐ€์šด๋ฐ ์ผ๋ถ€ ์—…๋ฌด๋ฅผ ๋‹จ๊ณ„์ ์œผ๋กœ ๋ถ„๋ฆฌํ•ด ์™ธ๋ถ€๋กœ ์ด์ „ํ•˜๋Š” ๊ฒƒ์ด ๋‹น์‹œ ๋งก์€ ์—ญํ• ์ด์—ˆ๋‹ค.

๋‹น์—ฐํžˆ ๊ธฐ์กด ์—…๋ฌด๋ฅผ ์ˆ˜ํ–‰ํ•˜๋˜ ์ธ๋ ฅ์˜ ๋‹ค์Œ ์ปค๋ฆฌ์–ด๋ฅผ ์–ด๋–ป๊ฒŒ ์„ค๊ณ„ํ• ์ง€๊ฐ€ ํฐ ๊ณผ์ œ๊ฐ€ ๋๋‹ค. ํŠธ๋ฆฌ๋„๋ฅด๋Š” ํšจ๊ณ ํ˜„ ๊ฐ€์ฝ”๊ฐ€์™€์‹œ์—์„œ ์ฐฝ์—…ํ•ด ์ดํ›„ ๊ณ ๋ฒ ์‹œ์— ๋ณธ์‚ฌ๋ฅผ ๋‘๊ณ  ์žˆ์—ˆ๊ณ , ๋‹น์‹œ ์‰์–ด๋“œ์„œ๋น„์Šค ํšŒ์‚ฌ์˜ ๊ฑฐ์  ์—ญ์‹œ ๊ณ ๋ฒ ์— ์žˆ์—ˆ๋‹ค.

์‹œ๋ถ€์•ผ ๋ณธ์‚ฌ๋กœ ์ด๋™์ด ๊ฐ€๋Šฅํ•œ ์ธ๋ ฅ์—๊ฒŒ๋Š” ์ง€์ฃผํšŒ์‚ฌ ์—…๋ฌด๋ฅผ ์ œ์•ˆํ–ˆ์ง€๋งŒ, ๊ฐ€์ • ์‚ฌ์ • ๋“ฑ์œผ๋กœ ์ „๊ทผ์ด ์–ด๋ ค์šด ๊ฒฝ์šฐ๋„ ์ ์ง€ ์•Š์•˜๋‹ค. ์ด๋Ÿฐ ๊ฒฝ์šฐ์—๋Š” BPO ๋ฒค๋”๋กœ ์ „์ ํ•ด ๊ธฐ์กด๊ณผ ๊ฐ™์€ ์—…๋ฌด๋ฅผ ์ด์–ด๊ฐ€๋„๋ก ํ•˜๊ฑฐ๋‚˜, ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน ๋งค์žฅ์œผ๋กœ ํ™œ๋™ ๋ฌด๋Œ€๋ฅผ ์˜ฎ๊ธฐ๋Š” ๋ฐฉ์•ˆ์„ ์ œ์‹œํ–ˆ๋‹ค. ๋‚˜๋Š” ๊ตฌ์„ฑ์› ํ•œ ์‚ฌ๋žŒ ํ•œ ์‚ฌ๋žŒ๊ณผ ๋ฉด๋‹ด์„ ๊ฑฐ๋“ญํ•˜๋ฉฐ ๋‹ค์Œ ์ง„๋กœ๋ฅผ ํ•จ๊ป˜ ๊ฒฐ์ •ํ•ด ๋‚˜๊ฐ”๋‹ค.

๋ฌผ๋ก  ์ด ๊ณผ์ •์€ ํ˜ผ์ž์„œ ๊ฐ๋‹นํ•  ์ˆ˜ ์žˆ๋Š” ์ผ์ด ์•„๋‹ˆ์—ˆ๋‹ค. ๋ถ€์žฅ๊ณผ ๊ด€๋ฆฌ์ง์˜ ํ˜‘์กฐ๋ฅผ ์–ป์–ด ์ง์›๋“ค๊ณผ ์ง„์ง€ํ•˜๊ฒŒ ๋Œ€ํ™”๋ฅผ ์ด์–ด๊ฐ€๋ฉฐ ์ถ”์ง„ํ–ˆ๋‹ค. ์ตœ์ข…์ ์ธ ๋ชฉํ‘œ๋Š” ๊ฐ์ž๊ฐ€ ์ƒˆ๋กœ์šด ํ™˜๊ฒฝ์—์„œ๋„ ์žฅ๊ธฐ๊ฐ„ ์—ญ๋Ÿ‰์„ ๋ฐœํœ˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜๋Š” ๊ฒƒ์ด์—ˆ๋‹ค. ํšŒ์‚ฌ ์ฐจ์›์˜ ๋ฐฉ์นจ์€ ๋ถ„๋ช…ํ–ˆ์ง€๋งŒ, ์ตœ๋Œ€ํ•œ ๊ตฌ์„ฑ์›๋“ค์ด ๋‚ฉ๋“ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒฐ๋ก ์— ์ด๋ฅด๋Š” ๊ฒƒ์ด ๋‹น์‹œ ์Šค์Šค๋กœ์—๊ฒŒ ์ฃผ์–ด์ง„ ๊ฐ€์žฅ ํฐ ์ฑ…์ž„์ด์—ˆ๋‹ค๊ณ  ๋ณธ๋‹ค.

Q : ํŠนํžˆ ๊ธฐ์–ต์— ๋‚จ๋Š” ๋ง์ด๋‚˜ ์‚ฌ๊ฑด์ด ์žˆ๋Š”๊ฐ€.
A : ํฌ๊ฒŒ ๋‘ ๊ฐ€์ง€๊ฐ€ ์žˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ์„ธ๋ธ๋„ท์‡ผํ•‘ ์ถœ๋ฒ”์— ๊ด€์—ฌํ•˜๋˜ ์‹œ๊ธฐ์˜ ๊ฒฝํ—˜์ด๋‹ค. ๋‹น์‹œ ์„ธ๋ธ&์•„์ดํ™€๋”ฉ์Šค ํšŒ์žฅ์ด์—ˆ๋˜ ์Šค์ฆˆํ‚ค ๋„์‹œํ›„๋ฏธ์˜ ๋ง์„, ๋‹น์‹œ ์ƒ์‚ฌ์ด์ž ํšŒ์žฅ์˜ ์•„๋“ค์ธ ์Šค์ฆˆํ‚ค ์•ผ์Šคํžˆ๋กœ๋กœ๋ถ€ํ„ฐ ์ „ํ•ด ๋“ค์€ ์ ์ด ์žˆ๋‹ค.

ํ•œ ๋ฒˆ์€ โ€œ์‚ฌ๋žŒ๋“ค ์•ž์—์„œ ์ด์•ผ๊ธฐํ•  ๋•Œ ์–ด๋–ป๊ฒŒ ํ•˜๋ฉด ๊ธด์žฅํ•˜์ง€ ์•Š์„ ์ˆ˜ ์žˆ๋А๋ƒโ€๊ณ  ๋ฌผ์—ˆ๋Š”๋ฐ, โ€œ๋ฌด๋ฆฌํ•ด์„œ ์ž˜๋‚œ ์ฒ™ํ•˜์ง€ ๋ง๊ณ , ๋ชจ๋ฅด๋Š” ๊ฒƒ์€ ์ด์•ผ๊ธฐํ•˜์ง€ ์•Š์œผ๋ฉฐ, ์•Œ๊ณ  ์žˆ๋Š” ๊ฒƒ๋งŒ ๋งํ•˜๋ฉด ๊ธด์žฅํ•˜์ง€ ์•Š๋Š”๋‹คโ€๋Š” ๋‹ต์„ ๋“ค์—ˆ๋‹ค. ๋ชจ๋ฅด๋Š” ๊ฒƒ์€ ๋ชจ๋ฅธ๋‹ค๊ณ  ๋งํ•˜๋ฉด ๋œ๋‹ค๋Š” ์ด์•ผ๊ธฐ์˜€๋‹ค. ์žˆ๋Š” ๊ทธ๋Œ€๋กœ, ๊ณผ์žฅํ•˜์ง€ ์•Š๊ณ  ๋งํ•˜๋Š” ์‚ฌ๋žŒ์ด์•ผ๋ง๋กœ ๊ฒฐ๊ตญ ์„ฑ๊ณผ๋ฅผ ๋งŒ๋“ค์–ด ๊ฐ„๋‹ค๋Š” ์ ์„ ๊ฐ•ํ•˜๊ฒŒ ๋А๊ผˆ๋‹ค.

๋‘ ๋ฒˆ์งธ๋Š” ๊ฐ™์€ ์‹œ๊ธฐ, ์„ธ๋ธ๋„ท์‡ผํ•‘์ด ์•ผํ›„์˜ ์žํšŒ์‚ฌ ์‚ฌ์—…์ด์—ˆ์„ ๋•Œ์˜ ๊ฒฝํ—˜์ด๋‹ค. ๋‹น์‹œ์—๋Š” ์ธํ„ฐ๋„ท์ด ์•„์ง ๋ณธ๊ฒฉ์ ์ธ ๋น„์ฆˆ๋‹ˆ์Šค๋กœ ์ž๋ฆฌ ์žก๊ธฐ ์ „์ด์—ˆ๊ณ , ์ผ๋ณธ์—์„œ๋Š” ์•ผํ›„๊ฐ€ ์•ž์„œ ์žˆ์—ˆ์œผ๋ฉฐ ๊ตฌ๊ธ€์ด ๋ง‰ ์ง„์ž…ํ•˜๋˜ ์‹œ๊ธฐ์˜€๋‹ค.

์ด์šฉ์ž๊ฐ€ ๊ธ‰์ฆํ•˜๋ฉด์„œ ์„œ๋ฒ„๊ฐ€ ํ˜ผ์žกํ•ด์ง€๊ณ  ์‹œ์Šคํ…œ์ด ํ•œ๊ณ„์— ๋ถ€๋”ชํžˆ๋Š” ์ƒํ™ฉ์ด ์ž์ฃผ ๋ฐœ์ƒํ–ˆ๋Š”๋ฐ, ๊ทธ๋•Œ ๋‹น์‹œ ์•ผํ›„ ๋Œ€ํ‘œ์˜€๋˜ ์ด๋…ธ์šฐ์— ๋งˆ์‚ฌํžˆ๋กœ๋กœ๋ถ€ํ„ฐ โ€œ์ธํ„ฐ๋„ท ๋น„์ฆˆ๋‹ˆ์Šค์—์„œ๋Š” ์‚ฌ์šฉ์ž๊ฐ€ ๋Š˜์–ด๋‚˜๋ฉด ์„œ๋ฒ„๋ฅผ ์ฆ์„คํ•˜๋Š” ๊ฒƒ์ด ๊ธฐ๋ณธ ์›์น™โ€์ด๋ผ๋Š” ๋ง์„ ๋“ค์—ˆ๋‹ค. ๊ทธ ํ•œ๋งˆ๋””์— ํฐ ๊นจ๋‹ฌ์Œ์„ ์–ป์—ˆ๋‹ค.

๊ธฐ์กด ์—”ํ„ฐํ”„๋ผ์ด์ฆˆ ํ™˜๊ฒฝ์—์„œ๋Š” ๊ฐ’๋น„์‹ผ ์ž์›์„ ์–ด๋–ป๊ฒŒ ์ตœ์ ํ™”ํ•ด ๋๊นŒ์ง€ ํ™œ์šฉํ•  ๊ฒƒ์ธ๊ฐ€๊ฐ€ ๊ธฐ๋ณธ์ ์ธ ์‚ฌ๊ณ ๋ฐฉ์‹์ด์—ˆ๋‹ค. ๋‚˜๋Š” ์—ญ์‹œ ์ œํ•œ๋œ ์ž์›์„ ํšจ์œจ์ ์œผ๋กœ ์“ฐ๋Š” ๊ฒƒ์ด ๋‹น์—ฐํ•˜๋‹ค๊ณ  ์—ฌ๊ฒจ ์™”๋‹ค.

ํ•˜์ง€๋งŒ ์ธํ„ฐ๋„ท์˜ ์„ธ๊ณ„์—์„œ๋Š” ์ €๋ ดํ•œ ์„œ๋ฒ„๋ฅผ ์ถ”๊ฐ€ํ•ด ํ™•์žฅํ•˜๋Š” ๊ฒƒ์ด ์ž์—ฐ์Šค๋Ÿฌ์šด ์„ ํƒ์ด์—ˆ๋‹ค. ํˆฌ์ž๋ฅผ ์ „์ œ๋กœ ํ•œ ์Šค์ผ€์ผ์•„์›ƒ ๋ฌธํ™”๊ฐ€ ๋ฟŒ๋ฆฌ๋‚ด๋ ค ์žˆ์—ˆ๊ณ , ์ถ”๊ฐ€ ํˆฌ์ž๊ฐ€ ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค๋ฉด ์ธํ„ฐ๋„ท ๋น„์ฆˆ๋‹ˆ์Šค ์ž์ฒด๊ฐ€ ์„ฑ๋ฆฝํ•˜์ง€ ์•Š๋Š”๋‹ค๋Š” ์ธ์‹์ด ์ž๋ฆฌ ์žก๊ณ  ์žˆ์—ˆ๋‹ค.

์ด๋Ÿฌํ•œ ์‚ฌ๊ณ ๋ฐฉ์‹์˜ ์ฐจ์ด๋Š” ๋งค์šฐ ์ถฉ๊ฒฉ์ ์ด์—ˆ๋‹ค. ์—”ํ„ฐํ”„๋ผ์ด์ฆˆ ๊ธฐ์ˆ ๊ณผ ์ธํ„ฐ๋„ท ๊ธฐ์ˆ  ์‚ฌ์ด์˜ ๋ณธ์งˆ์ ์ธ ์ฐจ์ด๋ฅผ ๋ถ„๋ช…ํ•˜๊ฒŒ ์ฒด๊ฐํ•œ ์ˆœ๊ฐ„์ด์—ˆ๊ณ , ๊ทธ ๊ฐ„๊ทน์€ ์ง€๊ธˆ๋„ ์™„์ „ํžˆ ๋ฉ”์›Œ์ง€์ง€ ์•Š์€ ์ฑ„ ๋‚จ์•„ ์žˆ๋‹ค๊ณ  ๋А๋ผ๊ณ  ์žˆ๋‹ค.

Q : CIO๋กœ์„œ ์–ด๋–จ ๋•Œ ๋ณด๋žŒ์„ ๋А๋ผ๋Š”๊ฐ€.
A: ํšŒ์‚ฌ์˜ ๋ฐฉํ–ฅ์„ฑ์„ ๋น ๋ฅด๊ฒŒ ์‹คํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ๋ฐ˜์„ ๋งˆ๋ จํ•  ๋•Œ CIO๋กœ์„œ์˜ ๋ณด๋žŒ์„ ๋А๋‚€๋‹ค. ๊ทธ๋Ÿฐ ๋ฉด์—์„œ ํŠธ๋ฆฌ๋„๋ฅด์˜ ๋ชฉํ‘œ๋Š” ๊ณ ๊ฐ์—๊ฒŒ ๊ฐ๋™์ ์ธ ๊ฒฝํ—˜์„ ์ œ๊ณตํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๊ทธ ์ตœ์ „์„ ์—๋Š” ๋งค์žฅ์—์„œ ์ผํ•˜๋Š” ์ง์›๊ณผ ์ด๋ฅผ ๋’ท๋ฐ›์นจํ•˜๋Š” ๋งค๋‹ˆ์ง€๋จผํŠธ๊ฐ€ ์žˆ๋‹ค. ๋‹ค๋งŒ ์‚ฌ๋žŒ์˜ ํž˜์—๋งŒ ์˜์กดํ•˜๋Š” ๋ฐ์—๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๊ธฐ ๋•Œ๋ฌธ์—, ์ด๋“ค์„ ๋’ค์—์„œ ์–ด๋–ป๊ฒŒ ์ง€์›ํ• ์ง€๊ฐ€ ์ค‘์š”ํ•˜๋‹ค. ๋ณ€ํ™”์— ์‹ ์†ํžˆ ๋Œ€์‘ํ•  ์ˆ˜ ์žˆ๋Š” ๋น„์ฆˆ๋‹ˆ์Šค ๊ธฐ๋ฐ˜์„ ๊ฐ–์ถ”๋Š” ๊ฒƒ์ด์•ผ๋ง๋กœ CIO๋กœ์„œ์˜ ๊ฐ€์žฅ ํฐ ๋ณด๋žŒ์ด๋‹ค.

IT ๋ถ€์„œ๊ฐ€ ์ž์ฒด ๋…ผ๋ฆฌ๋งŒ์œผ๋กœ ์›€์ง์—ฌ์„œ๋Š” ์˜๋ฏธ๊ฐ€ ์—†๋‹ค. ์ค‘์š”ํ•œ ๊ฒƒ์€ IT๊ฐ€ ๋น„์ฆˆ๋‹ˆ์Šค์— ์–ผ๋งˆ๋‚˜ ๊ธฐ์—ฌํ•˜๊ณ  ์žˆ๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ๋ณ€ํ™”์— ์–ผ๋งˆ๋‚˜ ์œ ์—ฐํ•˜๊ฒŒ ๋Œ€์‘ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ๋ฐ˜์„ ๊ตฌ์ถ•ํ–ˆ๋Š”์ง€๋‹ค.

์˜ˆ๋ฅผ ๋“ค์–ด ์‚ฌ์—… ํ™•์žฅ์„ ๊ณ ๋ฏผํ•  ๋•Œ๋Š” ์—…ํƒœ๊ฐ€ ๋Š˜์–ด๋‚  ๊ฒฝ์šฐ ํ•˜๋‚˜์˜ ๊ตฌ์กฐ๋กœ ๋Œ€์‘ํ• ์ง€, ์—ฌ๋Ÿฌ ๊ตฌ์กฐ๋ฅผ ์กฐํ•ฉํ• ์ง€์— ๋Œ€ํ•œ ์„ค๊ณ„ ํŒ๋‹จ์ด ํ•„์š”ํ•˜๋‹ค. ์„œ๋ฒ„๋ฅผ ๋Š˜๋ฆด ๊ฒƒ์ธ์ง€, ํ•œ ๋Œ€๋ฅผ ๋Œ€ํ˜•ํ™”ํ•  ๊ฒƒ์ธ์ง€์™€ ๊ฐ™์€ ์Šค์ผ€์ผ์•„์›ƒ๊ณผ ์Šค์ผ€์ผ์—… ์„ ํƒ๋„ ๋งˆ์ฐฌ๊ฐ€์ง€๋‹ค. ์ด๋Ÿฐ ์•„ํ‚คํ…์ฒ˜๋ฅผ ๊ฒ€ํ† ํ•˜๋Š” ๊ณผ์ • ์ž์ฒด๊ฐ€ ๋งค์šฐ ํฅ๋ฏธ๋กœ์šด ์˜์—ญ์ด๋‹ค.

๋˜ ์ง€๊ธˆ์ฒ˜๋Ÿผ ๋ณ€ํ™”๊ฐ€ ์žฆ์€ ์‹œ๋Œ€์—๋Š” ๊ฒฝ์˜์ง„์ด ๊ธฐ์กด ๋ฐฉ์นจ์„ ๋ฐ”๊พธ๋Š” ์ผ๋„ ๋ฐœ์ƒํ•œ๋‹ค. ์ด๋•Œ ๋Œ€๊ทœ๋ชจ ํˆฌ์ž๋ฅผ ์ด์œ ๋กœ ์‹œ์Šคํ…œ์„ ํฌ๊ธฐํ•˜์ง€ ๋ชปํ•˜๋Š” ์ƒํ™ฉ์€ ๋ฐ”๋žŒ์งํ•˜์ง€ ์•Š๋‹ค. ๊ทธ๋ž˜์„œ ๊ฐ€๋Šฅํ•œ ํ•œ ๊ตฌ๋…ํ˜• ์„œ๋น„์Šค, ์ฆ‰ SaaS๋ฅผ ์ ๊ทน ํ™œ์šฉํ•˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์œ ์—ฐ์„ฑ์ด ์š”๊ตฌ๋˜๋Š” ๋ฐฑ์˜คํ”ผ์Šค ์˜์—ญ์€ SaaS๋ฅผ ์กฐํ•ฉํ•˜๋Š” ํŽธ์ด ๋ฆฌ์Šคํฌ๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค.

์ด๋Ÿฌํ•œ ํŒ๋‹จ์„ ๋’ท๋ฐ›์นจํ•˜๋Š” ๊ฒƒ์€ ์—”์ง€๋‹ˆ์–ด๋กœ์„œ์˜ ๊ฒฝํ—˜๊ณผ ์‚ฌ์—… ๊ฒฝ์˜์— ์ง์ ‘ ๊ด€์—ฌํ–ˆ๋˜ ๊ฒฝํ—˜์ด๋‹ค. ๊ธฐ์ˆ ์„ ์ถฉ๋ถ„ํžˆ ์ดํ•ดํ•˜์ง€ ๋ชปํ•˜๋ฉด ์ตœ์ ์˜ ์„ ํƒ์„ ํ•  ์ˆ˜ ์—†๊ณ , ๊ฒฝ์˜ ๊ด€์ ์ด ์—†์œผ๋ฉด ๋น„์ฆˆ๋‹ˆ์Šค๋ฅผ ์–ด๋–ป๊ฒŒ ์ง€์›ํ• ์ง€์— ๋Œ€ํ•œ ๋‹ต๋„ ๋‚˜์˜ค์ง€ ์•Š๋Š”๋‹ค. ์ด ๋‘ ๊ฐ€์ง€๋ฅผ ํ•จ๊ป˜ ํ™œ์šฉํ•ด ์‚ฌ๊ณ ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์ด CIO ์—ญํ• ์˜ ๊ฐ€์žฅ ํฐ ์ฆ๊ฑฐ์›€์ด๋‹ค.

์‚ฌ์‹ค IT ๋ฒค๋” ์‹œ์ ˆ๋ถ€ํ„ฐ ์•ž์œผ๋กœ๋Š” SaaS๊ฐ€ ํ•„์ˆ˜๊ฐ€ ๋  ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•ด ์™”๋‹ค. ๋‹น์‹œ์—๋Š” ์ œ์•ˆํ•˜๋”๋ผ๋„ ์‚ฌ์šฉ์ž ๊ธฐ์—…์ด ์ฑ„ํƒํ•˜์ง€ ์•Š์œผ๋ฉด ์‹คํ–‰์œผ๋กœ ์ด์–ด์ง€์ง€ ์•Š์•˜์ง€๋งŒ, CIO๊ฐ€ ๋œ ์ดํ›„์—๋Š” ์Šค์Šค๋กœ ๊ฒฐ์ •ํ•ด ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์„ ์‹ค๊ฐํ–ˆ๋‹ค. ์ด๋Š” ๋งค์šฐ ํฐ ์ฐจ์ด์ด๋ฉฐ, ์‚ฌ์—…ํšŒ์‚ฌ๋กœ ์ž๋ฆฌ๋ฅผ ์˜ฎ๊ฒผ๊ธฐ์— ๊ฐ€๋Šฅํ•ด์ง„ ๋„์ „์ด๋‹ค.

ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์€ ๋ณ€ํ™”๋ฅผ ๋‘๋ ค์›Œํ•˜์ง€ ์•Š๊ณ  ์ง„ํ™”๋ฅผ ๊ฑฐ๋“ญํ•ด ์˜จ ๊ธฐ์—…์ด๋‹ค. ๊ทธ ๋•๋ถ„์— ๊ธ‰์„ฑ์žฅ์„ ์ด๋ค˜๊ณ , ๊ฒฉ๋ณ€ํ•˜๋Š” ํ™˜๊ฒฝ ์†์—์„œ๋„ ๋Œ€์‘ํ•ด ์˜ฌ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด ๊ฐ•์ ์€ ๋ฐ˜๋“œ์‹œ ์ง€์ผœ์•ผ ํ•œ๋‹ค๊ณ  ๋ณด๊ณ , ์‹œ์Šคํ…œ ๊ธฐ๋ฐ˜์„ ์ „๋ฉด์ ์œผ๋กœ SaaS ์ค‘์‹ฌ์œผ๋กœ ์ „ํ™˜ํ•˜๋Š” ์ž‘์—…์„ ์ถ”์ง„ํ•ด ์™”๋‹ค.

SaaS ๋ฒค๋”์˜ ์ œํ’ˆ ๋’ค์—๋Š” ์ˆ˜๋งŽ์€ ๋›ฐ์–ด๋‚œ ์—”์ง€๋‹ˆ์–ด๊ฐ€ ์กด์žฌํ•œ๋‹ค. ๊ด€์ ์— ๋”ฐ๋ผ์„œ๋Š” ์ด๋“ค์ด ๋ชจ๋‘ ํšŒ์‚ฌ๋ฅผ ๋’ท๋ฐ›์นจํ•˜๋Š” ์™ธ๋ถ€ ์ธ๋ ฅ์ด๋ผ๊ณ ๋„ ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ์ž์‚ฌ ์—ญ๋Ÿ‰์—๋งŒ ์˜์กดํ•˜์ง€ ์•Š๊ณ  ์™ธ๋ถ€์˜ ํž˜์„ ์–ด๋–ป๊ฒŒ ์กฐํ•ฉํ• ์ง€ ์„ค๊ณ„ํ•˜๋Š” ๊ฒƒ, ๊ทธ๊ฒƒ์ด CIO์˜ ์—ญํ• ์ด๋ฉฐ ๋‚˜์—๊ฒŒ ๊ฐ€์žฅ ํฐ ๋ณด๋žŒ์ด๋‹ค.

Q : AI ํ™œ์šฉ์— ๋Œ€ํ•ด์„œ๋Š” ์–ด๋–ป๊ฒŒ ๋ณด๊ณ  ์žˆ๋Š”๊ฐ€.
A: ์ตœ๊ทผ ์ƒ์„ฑํ˜• AI์— ๋Œ€ํ•œ ๊ด€์‹ฌ์ด ๋†’์•„์ง€๊ณ  ์žˆ์ง€๋งŒ, ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์ด ์ง‘์ค‘ํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์€ ํ˜„์žฅ์˜ ์ƒ์‚ฐ์„ฑ์„ ๋†’์ด๋Š” AI ํ™œ์šฉ์ด๋‹ค. ์ƒ์„ฑํ˜• AI๋Š” ํ™”์ดํŠธ์นผ๋ผ ์—…๋ฌด์˜ ํšจ์œจํ™”์—๋Š” ํšจ๊ณผ์ ์ด๋‹ค. ๋‹ค๋งŒ ์‚ฌ์—…๊ณผ ์ง์ ‘ ๋งž๋‹ฟ์•„ ์žˆ๋Š” ํ˜„์žฅ ์—…๋ฌด์—์„œ๋Š” ์ฆ‰์‹œ ์‹คํ–‰ ๊ฐ€๋Šฅํ•˜๊ณ  ์‹คํšจ์„ฑ์ด ๋ถ„๋ช…ํ•œ AI ํ™œ์šฉ์ด ํ•„์š”ํ•œ ๊ฒƒ ๊ฐ™๋‹ค.

๊ทธ ๋Œ€ํ‘œ์ ์ธ ์‚ฌ๋ก€๊ฐ€ ์ˆ˜์š” ์˜ˆ์ธก์ด๋‹ค. ๋งค์ถœ๊ณผ ๋ฐฉ๋ฌธ๊ฐ ์ˆ˜๋ฅผ AI๋กœ ์˜ˆ์ธกํ•จ์œผ๋กœ์จ ๋‹ค์Œ ๋‚  ํ•„์š”ํ•œ ์ธ๋ ฅ ๊ทœ๋ชจ๋‚˜ ์‹์ž์žฌ ๋ฐœ์ฃผ๋Ÿ‰์„ ๋ณด๋‹ค ํšจ์œจ์ ์œผ๋กœ ์‚ฐ์ •ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋งค์žฅ ์šด์˜ ๊ณ„ํš์ด ํ•œ์ธต ์ˆ˜์›”ํ•ด์กŒ๊ณ , ํ˜„์žฅ์˜ ๋ถ€๋‹ด๋„ ํฌ๊ฒŒ ์ค„์—ˆ๋‹ค.

๋˜ ํ•˜๋‚˜๋Š” ์–ผ๊ตด ์ธ์‹์„ ํ™œ์šฉํ•œ ๊ทผํƒœ ๊ด€๋ฆฌ๋‹ค. ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์—๋Š” ํŒŒํŠธํƒ€์ž„๊ณผ ์•„๋ฅด๋ฐ”์ดํŠธ ์ง์›์ด ๋งŽ์•„ ์ถœํ‡ด๊ทผ ๊ธฐ๋ก ๊ด€๋ฆฌ๊ฐ€ ์ค‘์š”ํ•œ ๊ณผ์ œ์˜€๋‹ค. ๊ธฐ์กด์˜ ์ง€๋ฌธ์ด๋‚˜ ์ •๋งฅ ์ธ์‹ ๋ฐฉ์‹์€ ๋ฌผ์„ ์ž์ฃผ ์‚ฌ์šฉํ•˜๋Š” ํ™˜๊ฒฝ์ด๋‚˜ ์ถ”์šด ๋‚ ์”จ๋กœ ์ธํ•ด ์˜ˆ์™ธ๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ์•˜์ง€๋งŒ, ์–ผ๊ตด ์ธ์‹์œผ๋กœ ์ „ํ™˜ํ•œ ์ดํ›„์—๋Š” ์˜ˆ์™ธ๊ฐ€ ๊ฑฐ์˜ ๋ฐœ์ƒํ•˜์ง€ ์•Š๊ณ  ์žˆ๋‹ค. ์ธ์‹ ์†๋„๋„ ๋น ๋ฅด๊ณ  ๋งˆ์Šคํฌ๋ฅผ ์ฐฉ์šฉํ•œ ์ƒํƒœ์—์„œ๋„ ์ฆ‰์‹œ ์ธ์‹ํ•  ์ˆ˜ ์žˆ์–ด, ํ˜„์žฅ์—์„œ๋Š” ๊ทผํƒœ ๊ด€๋ฆฌ๊ฐ€ ํ›จ์”ฌ ์ˆ˜์›”ํ•ด์กŒ๋‹ค๋Š” ๋ฐ˜์‘์ด ๋‚˜์˜จ๋‹ค.

ํ™”๋ คํ•ด ๋ณด์ด๋Š” ๊ธฐ์ˆ ์€ ์•„๋‹์ง€ ๋ชจ๋ฅด์ง€๋งŒ, ์ด๋Ÿฐ ์ ‘๊ทผ์ด ํ˜„์žฅ์˜ ์ƒ์‚ฐ์„ฑ์„ ๊พธ์ค€ํžˆ ๋Œ์–ด์˜ฌ๋ฆฌ๊ณ  ์žˆ๋‹ค. ์ด๊ฒƒ์ด ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์ด ์ง€ํ–ฅํ•˜๋Š” AI ํ™œ์šฉ์˜ ๋ณธ์งˆ์ด๋ผ๊ณ  ๋ณธ๋‹ค.

Q : CIO์—๊ฒŒ ํ•„์š”ํ•œ ์ž์งˆ์€ ๋ฌด์—‡์ด๋ผ๊ณ  ๋ณด๋Š”๊ฐ€.
A : ๊ฐ€์žฅ ์ค‘์š”ํ•˜๋‹ค๊ณ  ์ƒ๊ฐํ•˜๋Š” ๊ฒƒ์€ โ€˜๊ฐ์˜คโ€™๋‹ค. ๋ฌผ๋ก  ํ•œ ๋ฒˆ ์ •ํ•œ ์ผ์„ ๋๊นŒ์ง€ ํ•ด๋‚ด๋Š” ๊ฒƒ๋„ ์ค‘์š”ํ•˜์ง€๋งŒ, ๊ทธ์— ์•ž์„œ ๋ฌด์—‡์„ ๋ชฉํ‘œ๋กœ ํ•˜๋Š”์ง€ ๋ถ„๋ช…ํžˆ ์ œ์‹œํ•ด์•ผ ํ•œ๋‹ค. ๋ฏธ๋ž˜์˜ ๋ชจ์Šต์„ ๊ทธ๋ฆฐ ๋’ค โ€œ์ด ๋ฐฉํ–ฅ์œผ๋กœ ํšŒ์‚ฌ๋ฅผ ์ด๋Œ๊ฒ ๋‹คโ€๊ณ  ์„ ์–ธํ•˜๋Š” ๊ฒƒ ์ž์ฒด๊ฐ€ CIO์—๊ฒŒ๋Š” ๊ฐ์˜ค์˜ ํ‘œํ˜„์ด๋ผ๊ณ  ๋ณธ๋‹ค.

๋‚˜ ์—ญ์‹œ DX ๋น„์ „์„ ์™ธ๋ถ€์— ๊ณต๊ฐœํ•˜๋ฉด์„œ โ€œ์ด์ œ๋Š” ๋ฐ˜๋“œ์‹œ ํ•ด๋‚ด์•ผ ํ•œ๋‹คโ€๋Š” ๊ฒฐ์‹ฌ์ด ์„ฐ๋‹ค. ๊ทธ๋ ‡๊ฒŒ ํ•ด์•ผ ์ง์›๊ณผ ๋ฒค๋” ๋ชจ๋‘๊ฐ€ ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์ด ์–ด๋–ค ๋ชจ์Šต์„ ์ง€ํ–ฅํ•˜๋Š”์ง€ ์ดํ•ดํ•˜๊ณ , ๊ฐ™์€ ๋ฐฉํ–ฅ์„ ๋ฐ”๋ผ๋ณด๊ฒŒ ๋œ๋‹ค. ์ด๋Š” ๋งค์šฐ ํฐ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„๋‹ค.

CIO์—๊ฒŒ๋Š” ๋ชฉํ‘œ๋กœ ํ•˜๋Š” ๋ชจ์Šต์„ ํ•˜๋‚˜์˜ ๊ทธ๋ฆผ์œผ๋กœ ์ œ์‹œํ•˜๊ณ , ๊ทธ ๋น„์ „์„ ํ–ฅํ•ด ํ”๋“ค๋ฆผ ์—†์ด ๋‚˜์•„๊ฐ€๋Š” ์ถ”์ง„๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค. ์ด๋•Œ ์ค‘์š”ํ•œ ๊ฒƒ์ด ๋ฐฑ์บ์ŠคํŠธ(backcast) ์‚ฌ๊ณ , ์ฆ‰ ์ตœ์ข… ๋ชฉํ‘œ์— ๋„๋‹ฌํ•˜๊ธฐ ์œ„ํ•ด ์ง€๊ธˆ ๋ฌด์—‡์„ ํ•ด์•ผ ํ•˜๋Š”์ง€๋ฅผ ๊ฑฐ๊พธ๋กœ ๊ณ„์‚ฐํ•ด ๋‚˜๊ฐ€๋Š” ๋ฐฉ์‹์ด๋‹ค. ํฌ์–ด์บ์ŠคํŠธ(forecast) ๋ฐฉ์‹, ๋‹ค์‹œ ๋งํ•ด ํ˜„์žฌ ์ƒํƒœ๋ฅผ ์ถœ๋ฐœ์ ์œผ๋กœ ์‚ผ์•„ ๊ณผ์ œ๋ฅผ ํ•˜๋‚˜์”ฉ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐฉ์‹๋งŒ์œผ๋กœ๋Š” ์ƒˆ๋กœ์šด ๊ฐ€์น˜๋ฅผ ๋งŒ๋“ค์–ด๋‚ด๊ธฐ ์–ด๋ ต๋‹ค.

๋ฌผ๋ก  ์ผ์ • ์ˆ˜์ค€์˜ ์•ˆ์ •๊ธฐ์— ๋“ค์–ด์„œ๋ฉด ํฌ์–ด์บ์ŠคํŠธ ๋ฐฉ์‹์˜ ๊ฐœ์„ ์œผ๋กœ ์ถฉ๋ถ„ํ•œ ๊ฒฝ์šฐ๋„ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ํฐ ๋ณ€ํ™”๋ฅผ ๋งŒ๋“ค์–ด์•ผ ํ•  ๋•Œ๋Š” ๋ฐฑ์บ์ŠคํŠธ ๊ด€์ ์—์„œ ๊ณผ๊ฐํ•˜๊ฒŒ ๋ฐฉํ–ฅ๊ณผ ๊ฒฝ๋กœ๋ฅผ ๊ทธ๋ ค์•ผ ํ•œ๋‹ค.

๊ทธ๋ฆฌ๊ณ  ๊ทธ ๊ณผ์ •์—์„œ ์˜ˆ์ƒ๊ณผ ํ˜„์‹ค ์‚ฌ์ด์— ํฐ ๊ฐ„๊ทน์ด ์ƒ๊ธด๋‹ค๋ฉด, โ€œ์ด๊ฑด ์•„๋‹ˆ๋‹คโ€๋ผ๊ณ  ํŒ๋‹จํ•˜๊ณ  ๊ณผ๊ฐํ•˜๊ฒŒ ๋ฐฉํ–ฅ์„ ์ „ํ™˜ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒฐ๋‹จ๋ ฅ๊นŒ์ง€ ๊ฐ–์ถ”๋Š” ๊ฒƒ, ์ด๊ฒƒ์ด CIO์—๊ฒŒ ์š”๊ตฌ๋˜๋Š” ํ•ต์‹ฌ ์ž์งˆ์ด๋ผ๊ณ  ๋ณธ๋‹ค.

Q : CIO๋ฅผ ๊ฟˆ๊พธ๋Š” ์ง์›์—๊ฒŒ ํ•„์š”ํ•œ ์—ญ๋Ÿ‰์€ ๋ฌด์—‡์ธ๊ฐ€.
A : ๋‚˜๋Š” ํŒ€์›๋“ค์—๊ฒŒ ๋Š˜ โ€œ์žฅ์ฐจ CIO๋‚˜ CTO, ํ˜น์€ CDO ๊ฐ™์€ ์—ญํ• ์„ ๋งก์„ ์ˆ˜ ์žˆ๋Š” ์ธ์žฌ๋กœ ์„ฑ์žฅํ•˜๊ธธ ๋ฐ”๋ž€๋‹คโ€๊ณ  ์ด์•ผ๊ธฐํ•˜๊ณ  ์žˆ๋‹ค. ์ผ๋ณธ์—๋Š” ์•„์ง ๊ทธ๋Ÿฐ ์ธ์žฌ๊ฐ€ ์ถฉ๋ถ„ํžˆ ๋งŽ์ง€ ์•Š๋‹ค. ๊ทธ๋ ‡๊ธฐ ๋•Œ๋ฌธ์— ๋””์ง€ํ„ธ์„ ๋น„์ฆˆ๋‹ˆ์Šค์™€ ์—ฐ๊ฒฐํ•˜๋Š” ๊ฐ€๊ต ์—ญํ• ์„ ํ•  ์ˆ˜ ์žˆ๋Š” ์‚ฌ๋žŒ์„ ๋” ๋Š˜๋ ค์•ผ ํ•œ๋‹ค๊ณ  ๋ณธ๋‹ค. ์ Š์€ ์‹œ์ ˆ๋ถ€ํ„ฐ ์ด ์—ญํ• ์„ ๋ชฉํ‘œ๋กœ ์ปค๋ฆฌ์–ด๋ฅผ ์Œ“์•„ ๊ฐ€๊ธธ ๋ฐ”๋ž€๋‹ค.

์ด๋ฅผ ์œ„ํ•ด ํ•„์š”ํ•œ ์—ญ๋Ÿ‰์€ ํฌ๊ฒŒ ์„ธ ๊ฐ€์ง€๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ๊ธฐ์ดˆ์ ์ธ ๊ธฐ์ˆ  ์—ญ๋Ÿ‰์ด๋‹ค. ์ฝ”๋“œ๋ฅผ ์ง์ ‘ ์ž‘์„ฑํ•˜์ง€ ์•Š๋Š” IT ๋ฆฌ๋”๋„ ์žˆ์ง€๋งŒ, ํ•  ์ˆ˜ ์žˆ๋‹ค๋ฉด ๊ทธ ํŽธ์ด ํ›จ์”ฌ ๋‚ซ๋‹ค. ๋‚˜ ์—ญ์‹œ ์ค‘ํ•™์ƒ ๋•Œ๋ถ€ํ„ฐ ์ฝ”๋“œ๋ฅผ ์จ ์™”๋‹ค. ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด๋„ ํ•˜๋‚˜๋งŒ ์•„๋Š” ๊ฒƒ๋ณด๋‹ค ๋‘ ๊ฐ€์ง€ ์ด์ƒ์„ ์ตํžˆ๋ฉด ๋น„๊ต๊ฐ€ ๊ฐ€๋Šฅํ•ด์ง€๊ณ  ์ดํ•ด์˜ ๊นŠ์ด๋„ ๋‹ฌ๋ผ์ง„๋‹ค. ์ด๋Š” ์ด์ง์„ ํ†ตํ•ด ์ƒˆ๋กœ์šด ์‹œ์•ผ๊ฐ€ ์—ด๋ฆฌ๋Š” ๊ฒƒ๊ณผ ๋น„์Šทํ•˜๋ฉฐ, ์—ฌ๋Ÿฌ ๊ด€์ ์„ ๊ฐ–๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค๊ณ  ์ƒ๊ฐํ•œ๋‹ค.

๋‘ ๋ฒˆ์งธ๋Š” ์•„ํ‚คํ…ํŠธ๋กœ์„œ์˜ ์—ญ๋Ÿ‰์ด๋‹ค. ์‚ฌ์šฉ์ž ๊ธฐ์—…์˜ CIO๋Š” ๊ธฐ์กด ๊ธฐ์ˆ ์„ ์–ด๋–ป๊ฒŒ ์กฐํ•ฉํ•ด ์ž์‚ฌ ๋น„์ฆˆ๋‹ˆ์Šค์— ๊ฐ€์žฅ ์ ํ•ฉํ•œ ๊ตฌ์กฐ๋ฅผ ๋งŒ๋“ค ๊ฒƒ์ธ์ง€๋ฅผ ๋Š์ž„์—†์ด ๊ณ ๋ฏผํ•ด์•ผ ํ•œ๋‹ค. CTO์˜ ์—ญํ• ๊ณผ ๋งž๋‹ฟ์•„ ์žˆ๋Š” ๋ถ€๋ถ„๋„ ์žˆ์ง€๋งŒ, ๋„คํŠธ์›Œํฌ๋‚˜ ์ธํ”„๋ผ, ํด๋ผ์šฐ๋“œ ๊ฐ™์€ ๊ธฐ์ดˆ๋ฅผ ์ดํ•ดํ•˜์ง€ ๋ชปํ•˜๋ฉด ์ตœ์ ์˜ ์กฐํ•ฉ์„ ํŒ๋‹จํ•  ์ˆ˜ ์—†๋‹ค. ์‹œ์Šคํ…œ ์•„ํ‚คํ…ํŠธ๋กœ์„œ์˜ ์ง€์‹๊ณผ ์‚ฌ๊ณ ๋Š” ํ•„์ˆ˜์ ์ด๋‹ค.

๋งˆ์ง€๋ง‰์€ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ์—ญ๋Ÿ‰์ด๋‹ค. ํ”„๋กœ์ ํŠธ๊ฐ€ ์‹คํŒจํ•˜๋Š” ์ด์œ ๋Š” ๊ธฐ์ˆ  ๋ถ€์กฑ๋ณด๋‹ค ์†Œํ†ต ๋ถ€์กฑ์—์„œ ๋น„๋กฏ๋˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ํ›จ์”ฌ ๋งŽ๋‹ค. ๋‚˜๋Š” ํ‰์†Œ ์ผ๋Œ€์ผ ๋Œ€ํ™”๋ฅผ ์ž์ฃผ ํ•˜๋Š”๋ฐ, ๋Œ€ํ™” ์ƒ๋Œ€๋Š” ๋Œ€ํ‘œ๋ถ€ํ„ฐ ๊ทธ๋ฃน์‚ฌ ์ž„์›, ์‚ฌ์—…ํšŒ์‚ฌ ๊ฒฝ์˜์ง„๊นŒ์ง€ ๋‹ค์–‘ํ•˜๋‹ค. ์ด๋“ค์ด ๋ฌด์—‡์„ ํ•˜๊ณ  ์‹ถ์€์ง€ ์ดํ•ดํ•˜์ง€ ๋ชปํ•˜๋ฉด ์žฅ๊ธฐ์ ์ธ ๊ด€์ ์˜ ์‹œ์Šคํ…œ ์„ค๊ณ„๋Š” ๋ถˆ๊ฐ€๋Šฅํ•˜๊ณ , ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š” ์กฐ์–ธ์ž๊ฐ€ ๋˜์ง€ ๋ชปํ•˜๋ฉด ์„ฑ๊ณผ๋„ ๋‚˜์˜ค๊ธฐ ์–ด๋ ต๋‹ค. ์ด๋Ÿฐ ์—ญ๋Ÿ‰์€ ๋‚˜๋ฟ ์•„๋‹ˆ๋ผ ๋ถ€์žฅ๊ธ‰ ๊ตฌ์„ฑ์›์—๊ฒŒ๋„ ์š”๊ตฌํ•˜๊ณ  ์žˆ๋‹ค.

๊ธฐ์ดˆ์ ์ธ ๊ธฐ์ˆ  ์—ญ๋Ÿ‰, ์•„ํ‚คํ…ํŠธ๋กœ์„œ์˜ ์„ค๊ณ„ ์—ญ๋Ÿ‰, ๊ทธ๋ฆฌ๊ณ  ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ์—ญ๋Ÿ‰. ์ด ์„ธ ๊ฐ€์ง€๋Š” CIO๋ฅผ ๋ชฉํ‘œ๋กœ ํ•  ๋•Œ ๋ฐ˜๋“œ์‹œ ๊ฐ–์ถฐ์•ผ ํ•  ์ž์งˆ์ด๋‹ค. ํŠนํžˆ B2B ๊ธฐ์—…์ผ์ˆ˜๋ก ํŒŒํŠธ๋„ˆ ๊ธฐ์—…๊ณผ์˜ ๊ด€๊ณ„๊ฐ€ ์ค‘์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ์ Š์€ ์‹œ์ ˆ๋ถ€ํ„ฐ ์ด๋ฅผ ๊ฐ•ํ•˜๊ฒŒ ์˜์‹ํ•˜๊ธธ ๊ถŒํ•˜๊ณ  ์‹ถ๋‹ค.

Q : ์•ž์œผ๋กœ์˜ ๋ชฉํ‘œ๋Š”?
A: ์šฐ๋ฆฌ๋Š” โ€˜๊ธ€๋กœ๋ฒŒ ํ‘ธ๋“œ ์ปดํผ๋‹ˆโ€™๋ฅผ ๊ธฐ์—… ๋น„์ „์œผ๋กœ ๋‚ด์„ธ์šฐ๊ณ  ์žˆ๋‹ค. ๋ชฉํ‘œ๋Š” ์œ ๋ช…ํ•œ ํ–„๋ฒ„๊ฑฐ ์ฒด์ธ์ด๋‚˜ ์ปคํ”ผ ์ฒด์ธ๊ณผ ์–ด๊นจ๋ฅผ ๋‚˜๋ž€ํžˆ ํ•˜๋Š”, ์ผ๋ณธ ์ตœ์ดˆ์˜ โ€˜์„ธ๊ณ„์—์„œ ํ†ตํ•˜๋Š” ์™ธ์‹ ๊ธฐ์—…โ€™์ด ๋˜๋Š” ๊ฒƒ์ด๋‹ค.

ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์€ ์ด๋ฏธ 30๊ฐœ๊ตญ ์ด์ƒ์— ์ง„์ถœํ•ด ์žˆ์ง€๋งŒ, ๋ชจ๋“  ๊ตญ๊ฐ€์—์„œ ์ผ๋ณธ๊ณผ ๋™์ผํ•œ ํ’ˆ์งˆ์„ ๊ตฌํ˜„ํ•˜๊ณ  ์žˆ๋А๋ƒ๊ณ  ํ•˜๋ฉด ์•„์ง ๊ณผ์ œ๊ฐ€ ๋‚จ์•„ ์žˆ๋‹ค. ์ด ์ˆ˜์ค€์„ ์–ด๋–ป๊ฒŒ ๋Œ์–ด์˜ฌ๋ฆด์ง€๊ฐ€ ์•ž์œผ๋กœ์˜ ํฐ ๊ณผ์ œ๋‹ค. ๋””์ง€ํ„ธ์˜ ํž˜์œผ๋กœ ๊ธฐ์ค€์„ ๋งž์ถ”๊ณ , ์ƒˆ๋กœ์šด ๊ตญ๊ฐ€๋กœ๋„ ๋ณด๋‹ค ์‰ฝ๊ฒŒ ํ™•์žฅํ•  ์ˆ˜ ์žˆ๋Š” ํ™˜๊ฒฝ์„ ๋งŒ๋“œ๋Š” ๊ฒƒ์ด ์‚ฌ์—… ๊ฐ€์†์œผ๋กœ ์ด์–ด์ง„๋‹ค๊ณ  ๋ณธ๋‹ค.

์ง€๊ธˆ๊นŒ์ง€๋Š” ์ผ๋ณธ ์‹œ์žฅ์— ์ง‘์ค‘ํ•ด ์™”์ง€๋งŒ, ์•ž์œผ๋กœ๋Š” ๊ธ€๋กœ๋ฒŒ ์žํšŒ์‚ฌ์™€ ํ”„๋žœ์ฐจ์ด์ฆˆ ํŒŒํŠธ๋„ˆ์— ๋Œ€ํ•ด์„œ๋„ ๋ณด๋‹ค ์ ๊ทน์ ์œผ๋กœ ์ง€์›ํ•ด ๋‚˜๊ฐˆ ์ƒ๊ฐ์ด๋‹ค.

๋ฌผ๋ก  ๋ชจ๋“  ๊ฒƒ์„ ์ผ๋ฅ ์ ์ธ ๊ตฌ์กฐ๋กœ ์ ์šฉํ•˜๋Š” ๊ฒƒ์€ ํ˜„์‹ค์ ์ด์ง€ ์•Š๋‹ค. ์ œ์กฐ์—…์ฒ˜๋Ÿผ ์ „ ์„ธ๊ณ„์— ๋™์ผํ•œ ์‹œ์Šคํ…œ์„ ์ ์šฉํ•˜๋Š” ๋ฐฉ์‹๋„ ์žˆ์ง€๋งŒ, ์™ธ์‹ ์‚ฐ์—…์€ ํ˜„์ง€ ์†Œ๋น„์ž๊ฐ€ ์‹ค์ œ๋กœ ๋จน์–ด์•ผ ๊ฐ€์น˜๊ฐ€ ์ƒ๊ธด๋‹ค. ์ผ์ •ํ•œ ์ž์œจ์„ฑ์„ ์œ ์ง€ํ•˜๋ฉด์„œ๋„, ํŠธ๋ฆฌ๋„๋ฅด๊ทธ๋ฃน์œผ๋กœ์„œ ๋ฐ˜๋“œ์‹œ ์ง€์ผœ์•ผ ํ•  ๊ธฐ์ค€์„ ์–ด๋–ป๊ฒŒ ์ •์ฐฉ์‹œํ‚ฌ์ง€๊ฐ€ ์ค‘์š”ํ•˜๋‹ค.

์ด ๊ณผ์ •์—์„œ ํšจ๊ณผ์ ์ธ ์ˆ˜๋‹จ์ด ๋””์ง€ํ„ธ ๊ธฐ๋ฐ˜์ด๋‹ค. ๊ธฐ์ค€์„ ์‹œ์Šคํ…œ์— ๋…น์—ฌ ๋‘๋ฉด, ์˜์‹ํ•˜์ง€ ์•Š์•„๋„ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ํ’ˆ์งˆ๊ณผ ์šด์˜ ๊ธฐ์ค€์ด ์œ ์ง€๋œ๋‹ค. ์ด๋Ÿฐ ๊ตฌ์กฐ๋ฅผ ์•ž์œผ๋กœ ๋” ๋Š˜๋ ค ๊ฐ€๊ณ ์ž ํ•œ๋‹ค.

๋‹ค๋งŒ ๊ณผ๋„ํ•˜๊ฒŒ ์ ์šฉํ•˜๋ฉด โ€˜์†์œผ๋กœ ๋งŒ๋“ค๊ณ  ๊ฐ“ ์กฐ๋ฆฌํ•œ๋‹คโ€™๋Š” ์šฐ๋ฆฌ์˜ ์šด์˜ ์ฒ ํ•™์ด ์•ฝํ•ด์งˆ ์œ„ํ—˜๋„ ์žˆ๋‹ค. ๊ทธ ๊ท ํ˜•์„ ์–ด๋””์— ๋‘˜ ๊ฒƒ์ธ์ง€๋Š” ์‰ฝ์ง€ ์•Š์€ ๊ณผ์ œ์ง€๋งŒ, ์˜คํžˆ๋ ค ๊ทธ ์ง€์ ์— ์žฌ๋ฏธ๊ฐ€ ์žˆ๋‹ค๊ณ  ๋А๋‚€๋‹ค.

๋ณธ์‚ฌ ๊ฒฝ์˜์ง„๊ณผ ๊ฐ ์‚ฌ์—… ์ฑ…์ž„์ž๋“ค๊ณผ ์ง€์†์ ์œผ๋กœ ๋…ผ์˜ํ•˜๋ฉฐ, ๊ฐ ์ง€์—ญ์— ๋งž๋Š” ์ตœ์ ์˜ ๊ท ํ˜•์ ์„ ์ฐพ์•„๊ฐ€๋Š” ์ž‘์—…์„ ์ „ ์„ธ๊ณ„๋กœ ํ™•๋Œ€ํ•ด ๋‚˜๊ฐ€๊ณ  ์‹ถ๋‹ค.
dl-ciokorea@foundryco.com

*์ด ๊ธฐ์‚ฌ๋Š” CIO ์žฌํŒฌ์— ๊ฒŒ์žฌ๋œ ์›๋ฌธ์„ ๋ฐ”ํƒ•์œผ๋กœ ์žฌ๊ตฌ์„ฑํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์›๋ฌธ์€ ์—ฌ๊ธฐ์„œ ํ™•์ธํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

โ€œ๋ณด์•ˆยท๋ฐ์ดํ„ฐยท์กฐ์ง์ด ์Šน๋ถ€ ๊ฐ€๋ฅธ๋‹คโ€ 2026๋…„ CIO 10๋Œ€ ๊ณผ์ œ

CIO์˜ โ€˜ํฌ๋ง ๋ชฉ๋กโ€™์€ ๋Š˜ ๊ธธ๊ณ  ๋น„์šฉ๋„ ๋งŽ์ด ๋“ ๋‹ค. ํ•˜์ง€๋งŒ ์šฐ์„ ์ˆœ์œ„๋ฅผ ํ•ฉ๋ฆฌ์ ์œผ๋กœ ์„ธ์šฐ๋ฉด, ํŒ€๊ณผ ์˜ˆ์‚ฐ์„ ์†Œ์ง„ํ•˜์ง€ ์•Š์œผ๋ฉด์„œ๋„ ๊ธ‰๋ณ€ํ•˜๋Š” ์š”๊ตฌ์— ๋Œ€์‘ํ•  ์ˆ˜ ์žˆ๋‹ค.

ํŠนํžˆ 2026๋…„์—๋Š” IT ์šด์˜์„ โ€˜๋น„์šฉ ์„ผํ„ฐโ€™๊ฐ€ ์•„๋‹ˆ๋ผ ์†์ต ๊ด€์ ์—์„œ ์žฌ์ •์˜ํ•˜๋ฉด์„œ, ๊ธฐ์ˆ ๋กœ ๋น„์ฆˆ๋‹ˆ์Šค๋ฅผ ์žฌ์ฐฝ์กฐํ•˜๋Š” ์ ‘๊ทผ์ด ํ•„์š”ํ•˜๋‹ค. ์•ก์„ผ์ถ”์–ด(Accenture)์˜ ๊ธฐ์ˆ  ์ „๋žตยท์ž๋ฌธ ๊ธ€๋กœ๋ฒŒ ๋ฆฌ๋“œ ์ฝ”์—”๋ผํŠธ ์…ธํฌํŠธ๋Š” โ€œ์ตœ์†Œํ•œ์˜ ํˆฌ์ž๋กœ โ€˜๋ถˆ๋งŒ ๊บผ์ง€์ง€ ์•Š๊ฒŒ ์œ ์ง€โ€™ํ•˜๋Š” ๋ฐ์„œ ๋ฒ—์–ด๋‚˜, ๊ธฐ์ˆ ๋กœ ๋งค์ถœ ์„ฑ์žฅ์„ ๊ฒฌ์ธํ•˜๊ณ  ์ƒˆ๋กœ์šด ๋””์ง€ํ„ธ ์ œํ’ˆ์„ ๋งŒ๋“ค๋ฉฐ, ์ƒˆ ๋น„์ฆˆ๋‹ˆ์Šค ๋ชจ๋ธ์„ ๋” ๋น ๋ฅด๊ฒŒ ์‹œ์žฅ์— ๋‚ด๋†“๋Š” ์ชฝ์œผ๋กœ ์ดˆ์ ์„ ์˜ฎ๊ฒจ์•ผ ํ•œ๋‹คโ€๋ผ๊ณ  ๊ถŒ๊ณ ํ–ˆ๋‹ค.

๋‹ค์Œ์€ CIO๊ฐ€ 2026๋…„์— ์šฐ์„ ์ˆœ์œ„ ์ƒ๋‹จ์— ์˜ฌ๋ ค์•ผ ํ•  10๊ฐ€์ง€ ํ•ต์‹ฌ ๊ณผ์ œ๋‹ค.

1. ์‚ฌ์ด๋ฒ„ ๋ณด์•ˆ ํšŒ๋ณตํƒ„๋ ฅ์„ฑ๊ณผ ๋ฐ์ดํ„ฐ ํ”„๋ผ์ด๋ฒ„์‹œ ๊ฐ•ํ™”

๊ธฐ์—…์ด ์ƒ์„ฑํ˜• AI์™€ ์—์ด์ „ํ‹ฑ AI๋ฅผ ํ•ต์‹ฌ ์›Œํฌํ”Œ๋กœ์šฐ ๊นŠ์ˆ™์ด ํ†ตํ•ฉํ•˜๋ฉด์„œ, ๊ณต๊ฒฉ์ž ์—ญ์‹œ ๊ฐ™์€ AI ๊ธฐ์ˆ ๋กœ ์›Œํฌํ”Œ๋กœ์šฐ๋ฅผ ๊ต๋ž€ํ•˜๊ณ  ์ง€์‹์žฌ์‚ฐ(IP)๊ณผ ๋ฏผ๊ฐ ๋ฐ์ดํ„ฐ๋ฅผ ๋…ธ๋ฆด ๊ฐ€๋Šฅ์„ฑ์ด ์ปค์กŒ๋‹ค. ์†Œ๋น„์ž ์‹ ์šฉํ‰๊ฐ€ ๊ธฐ์—… ํŠธ๋žœ์Šค์œ ๋‹ˆ์–ธ(TransUnion)์˜ ๊ธ€๋กœ๋ฒŒ ์ œํ’ˆ ํ”Œ๋žซํผ ๋‹ด๋‹น ์ˆ˜์„๋ถ€์‚ฌ์žฅ ์š”๊ฒŒ์‹œ ์กฐ์‹œ๋Š” โ€œ๊ทธ ๊ฒฐ๊ณผ CIO์™€ CISO๋Š” ๋‚˜์œ ํ–‰์œ„์ž๋“ค์ด ๋™์ผํ•œ AI ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•ด ์›Œํฌํ”Œ๋กœ์šฐ๋ฅผ ๋ฐฉํ•ดํ•˜๊ณ , ๊ณ ๊ฐ ๋ฏผ๊ฐ ๋ฐ์ดํ„ฐ์™€ ๊ฒฝ์Ÿ์šฐ์œ„์— ํ•ด๋‹นํ•˜๋Š” ์ •๋ณดยท์ž์‚ฐ์„ ํฌํ•จํ•œ IP๋ฅผ ํƒˆ์ทจํ•˜๋ ค ํ•  ๊ฒƒ์ž„์„ ์˜ˆ์ƒํ•ด์•ผ ํ•œ๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค.

์กฐ์‹œ๋Š” ๋””์ง€ํ„ธ ์ „ํ™˜ ๊ฐ€์†๊ณผ AI ํ†ตํ•ฉ ํ™•๋Œ€๋กœ ๋ฆฌ์Šคํฌ ํ™˜๊ฒฝ์ด ํฌ๊ฒŒ ๋„“์–ด์งˆ ๊ฒƒ์œผ๋กœ ๋ณด๊ณ , 2026๋…„ ์ตœ์šฐ์„  ๊ณผ์ œ๋กœ โ€˜๋ณด์•ˆ ํšŒ๋ณตํƒ„๋ ฅ์„ฑโ€™๊ณผ โ€˜๋ฐ์ดํ„ฐ ํ”„๋ผ์ด๋ฒ„์‹œโ€™๋ฅผ ๊ผฝ์•˜๋‹ค. ํŠนํžˆ, โ€œ๋ฏผ๊ฐ ๋ฐ์ดํ„ฐ ๋ณดํ˜ธ์™€ ๊ธ€๋กœ๋ฒŒ ๊ทœ์ œ ์ค€์ˆ˜๋Š” ํ˜‘์ƒ ๋Œ€์ƒ์ด ์•„๋‹ˆ๋‹คโ€๋ผ๊ณ  ๊ฐ•์กฐํ–ˆ๋‹ค.

2. ๋ณด์•ˆ ๋„๊ตฌ ํ†ตํ•ฉ

AI์˜ ํšจ๊ณผ๋ฅผ ์ œ๋Œ€๋กœ ๋Œ์–ด๋‚ด๋ ค๋ฉด ๊ธฐ๋ฐ˜์„ ๋‹ค์‹œ ๋‹ค์ ธ์•ผ ํ•œ๋‹ค๋Š” ์ฃผ์žฅ๋„ ์žˆ๋‹ค. ๋”œ๋กœ์ดํŠธ์˜ ๋ฏธ๊ตญ ์‚ฌ์ด๋ฒ„ ํ”Œ๋žซํผ ๋ฐ ๊ธฐ์ˆ ยท๋ฏธ๋””์–ดยทํ†ต์‹ (TMT) ์‚ฐ์—… ๋ฆฌ๋” ์•„๋ฃฌ ํŽ˜๋ฆฐ์ฝœ๋žŒ์€ โ€œํ•„์ˆ˜ ์กฐ๊ฑด ์ค‘ ํ•˜๋‚˜๋Š” ํŒŒํŽธํ™”๋œ ๋ณด์•ˆ ๋„๊ตฌ๋ฅผ ํ†ตํ•ฉยท์—ฐ๋™๋œ ์‚ฌ์ด๋ฒ„ ๊ธฐ์ˆ  ํ”Œ๋žซํผ์œผ๋กœ ๋ฌถ๋Š” ๊ฒƒ์ธ๋ฐ, ์ด๋ฅผ โ€˜ํ”Œ๋žซํผํ™”(platformization)โ€™๋ผ๊ณ  ๋ถ€๋ฅธ๋‹คโ€๋ผ๊ณ  ์„ค๋ช…ํ–ˆ๋‹ค.

ํŽ˜๋ฆฐ์ฝœ๋žŒ์€ ํ†ตํ•ฉ์€ ๋ณด์•ˆ์„ โ€˜์—ฌ๋Ÿฌ ํฌ์ธํŠธ ์†”๋ฃจ์…˜์˜ ๋ˆ„๋”๊ธฐโ€™์—์„œ ๋น ๋ฅธ ํ˜์‹ ๊ณผ ํ™•์žฅ ๊ฐ€๋Šฅํ•œ AI ์ค‘์‹ฌ ์šด์˜์„ ์œ„ํ•œ ๋ฏผ์ฒฉํ•˜๊ณ  ํ™•์žฅ๋œ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ฐ”๊ฟ€ ๊ฒƒ์ด๋ผ๋ฉฐ, โ€œ์œ„ํ˜‘์ด ์ •๊ตํ•ด์งˆ์ˆ˜๋ก ํ†ตํ•ฉ ํ”Œ๋žซํผ์ด ์ค‘์š”ํ•ด์ง€๋ฉฐ, ๋„๊ตฌ ๋‚œ๋ฆฝ์„ ๋ฐฉ์น˜ํ•˜๋ฉด ์˜คํžˆ๋ ค ๋ถ„์ ˆ๋œ ๋ณด์•ˆ ํƒœ์„ธ๊ฐ€ ๊ณต๊ฒฉ์ž์—๊ฒŒ ์œ ๋ฆฌํ•˜๊ฒŒ ์ž‘๋™ํ•ด ์œ„ํ—˜์ด ์ปค์ง„๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ๋˜ โ€œ๊ธฐ์—…์€ ๋‚ ๋กœ ์ฆ๊ฐ€ํ•˜๋Š” ์œ„ํ˜‘์— ์ง๋ฉดํ•  ๊ฒƒ์ด๋ฉฐ, ์ด๋ฅผ ๊ด€๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด ๋ณด์•ˆ ๋„๊ตฌ๊ฐ€ ๋ฌด๋ถ„๋ณ„ํ•˜๊ฒŒ ํ™•์‚ฐ๋  ๊ฒƒ์ด๋‹ค. ๊ณต๊ฒฉ์ž๊ฐ€ ์ด๋ ‡๊ฒŒ ํŒŒํŽธํ™”๋œ ๋ณด์•ˆ ํƒœ์„ธ๋ฅผ ์•…์šฉํ•  ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ, ํ”Œ๋žซํผํ™”๋ฅผ ๋Šฆ์ถ”๋ฉด ์œ„ํ—˜๋งŒ ์ฆํญ๋  ๊ฒƒโ€์ด๋ผ๊ณ  ๋ง๋ถ™์˜€๋‹ค.

3. ๋ฐ์ดํ„ฐ ๋ณดํ˜ธ โ€˜๊ธฐ๋ณธ๊ธฐโ€™ ์žฌ์ ๊ฒ€

์กฐ์ง์ด ํšจ์œจยท์†๋„ยทํ˜์‹ ์„ ์œ„ํ•ด ์ƒˆ๋กœ์šด AI ๋ชจ๋ธ ๋„์ž… ๊ฒฝ์Ÿ์— ๋‚˜์„œ๊ณ  ์žˆ์ง€๋งŒ, ๋ฏผ๊ฐ ๋ฐ์ดํ„ฐ ๋ณดํ˜ธ๋ฅผ ์œ„ํ•œ ๊ธฐ๋ณธ ๋‹จ๊ณ„์กฐ์ฐจ ๋†“์น˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ์ ์ง€ ์•Š๋‹ค๋Š” ๊ฒฝ๊ณ ๋„ ๋‚˜์˜จ๋‹ค. ๋ฐ์ดํ„ฐ ํ”„๋ผ์ด๋ฒ„์‹œยท๋ณด์กด ์ „๋ฌธ์—…์ฒด ๋„๋…ธ๋งˆ ์†Œํ”„ํŠธ์›จ์–ด(Donoma Software)์˜ ์ตœ๊ณ ์ „๋žต์ฑ…์ž„์ž ํŒŒ์ปค ํ”ผ์–ด์Šจ์€ โ€œ์ƒˆ AI ๊ธฐ์ˆ ์„ ํ’€๊ธฐ ์ „์— ๋ฏผ๊ฐ ๋ฐ์ดํ„ฐ๋ฅผ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•œ ๊ธฐ๋ณธ ์กฐ์น˜๋ฅผ ํ•˜์ง€ ์•Š๋Š” ์กฐ์ง์ด ๋งŽ๋‹คโ€๋ผ๋ฉฐ 2026๋…„์—๋Š” โ€œ๋ฐ์ดํ„ฐ ํ”„๋ผ์ด๋ฒ„์‹œ๋ฅผ ๊ธด๊ธ‰ ๊ณผ์ œ๋กœ ๋ด์•ผ ํ•œ๋‹คโ€๋ผ๊ณ  ๊ฐ•์กฐํ–ˆ๋‹ค.

ํ”ผ์–ด์Šจ์€ ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ยท์‚ฌ์šฉยท๋ณดํ˜ธ ์ด์Šˆ๊ฐ€ ์ดˆ๊ธฐ ํ•™์Šต๋ถ€ํ„ฐ ์šด์˜๊นŒ์ง€ AI ๋ผ์ดํ”„์‚ฌ์ดํด ์ „๋ฐ˜์—์„œ ๋ฐœ์ƒํ•œ๋‹ค๊ณ  ์„ค๋ช…ํ–ˆ๋‹ค. ๋˜ ๋งŽ์€ ๊ธฐ์—…์ด โ€œAI๋ฅผ ๋ฌด์‹œํ•ด ๊ฒฝ์Ÿ์—์„œ ๋’ค์ฒ˜์ง€๊ฑฐ๋‚˜ ๋ฏผ๊ฐ ๋ฐ์ดํ„ฐ๋ฅผ ๋…ธ์ถœํ•  ์ˆ˜ ์žˆ๋Š” LLM์„ ๋„์ž…ํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ๋‚˜์œ ์„ ํƒ์ง€ ์‚ฌ์ด์— ๋†“์—ฌ ์žˆ๋‹คโ€๋ผ๊ณ  ์ง„๋‹จํ–ˆ๋‹ค.

ํ•ต์‹ฌ์€ โ€˜AI๋ฅผ ํ•  ๊ฒƒ์ธ๊ฐ€โ€™๊ฐ€ ์•„๋‹ˆ๋ผ โ€˜๋ฏผ๊ฐ ๋ฐ์ดํ„ฐ๋ฅผ ์œ„ํ—˜์— ๋น ๋œจ๋ฆฌ์ง€ ์•Š์œผ๋ฉด์„œ AI ๊ฐ€์น˜๋ฅผ ์ตœ์ ํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•โ€™์ด๋‹ค. ํ”ผ์–ด์Šจ์€ ํŠนํžˆ โ€œ๋ฐ์ดํ„ฐ๊ฐ€ โ€˜์™„์ „ํžˆโ€™ ๋˜๋Š” โ€˜์—”๋“œ ํˆฌ ์—”๋“œโ€™๋กœ ์•”ํ˜ธํ™”๋ผ ์žˆ๋‹คโ€๋Š” ์กฐ์ง์˜ ์ž์‹ ๊ฐ๊ณผ ๋‹ฌ๋ฆฌ, ์‹ค์ œ๋กœ๋Š” ์‚ฌ์šฉ ์ค‘ ๋ฐ์ดํ„ฐ๊นŒ์ง€ ํฌํ•จํ•ด ๋ชจ๋“  ์ƒํƒœ์—์„œ ์—ฐ์†์ ์œผ๋กœ ๋ณดํ˜ธํ•˜๋Š” ์ฒด๊ณ„๊ฐ€ ํ•„์š”ํ•˜๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ๋‹ค. ํ”„๋ผ์ด๋ฒ„์‹œ ๊ฐ•ํ™” ๊ธฐ์ˆ ์„ ์ง€๊ธˆ ๋„์ž…ํ•˜๋ฉด ์ดํ›„ AI ๋ชจ๋ธ ์ ์šฉ์—์„œ๋„ ๋ฐ์ดํ„ฐ ๊ตฌ์กฐํ™”ยท๋ณด์•ˆ์ด ์„ ํ–‰๋ผ ํ•™์Šต ํšจ์œจ์ด ์ข‹์•„์ง€๊ณ , ์žฌํ•™์Šต์— ๋”ฐ๋ฅธ ๋น„์šฉยท๋ฆฌ์Šคํฌ๋„ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค๋Š” ์„ค๋ช…์ด๋‹ค.

4. ํŒ€ ์ •์ฒด์„ฑ๊ณผ ๊ฒฝํ—˜์— ์ง‘์ค‘

2026๋…„ CIO ๊ณผ์ œ๋กœ โ€˜๊ธฐ์—… ์ •์ฒด์„ฑโ€™๊ณผ ์ง์› ๊ฒฝํ—˜์„ ์žฌ์ •๋น„ํ•ด์•ผ ํ•œ๋‹ค๋Š” ๋ชฉ์†Œ๋ฆฌ๋„ ์žˆ๋‹ค. IT ๋ณด์•ˆ ์†Œํ”„ํŠธ์›จ์–ด ์—…์ฒด ๋„ท์œ„๋ฆญ์Šค(Netwrix)์˜ CIO ๋งˆ์ดํด ์›ป์ ค์€ โ€œ์ •์ฒด์„ฑ์€ ์‚ฌ๋žŒ๋“ค์ด ์กฐ์ง์— ํ•ฉ๋ฅ˜ํ•˜๊ณ  ํ˜‘์—…ํ•˜๊ณ  ๊ธฐ์—ฌํ•˜๋Š” ๊ธฐ๋ฐ˜โ€์ด๋ผ๋ฉฐ, โ€œ์ •์ฒด์„ฑ๊ณผ ์ง์› ๊ฒฝํ—˜์„ ์ œ๋Œ€๋กœ ์žก์œผ๋ฉด ๋ณด์•ˆ, ์ƒ์‚ฐ์„ฑ, ๋„์ž… ๋“ฑ ๋‹ค๋ฅธ ๋ชจ๋“  ๊ฒƒ์ด ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ๋”ฐ๋ผ์˜จ๋‹คโ€๋ผ๊ณ  ๋งํ–ˆ๋‹ค.

์›ป์ ค์€ ์ง์›๋“ค์ด ์ง์žฅ์—์„œ โ€˜์†Œ๋น„์ž๊ธ‰โ€™ ๊ฒฝํ—˜์„ ๊ธฐ๋Œ€ํ•œ๋‹ค๊ณ  ์ง„๋‹จํ–ˆ๋‹ค. ๋‚ด๋ถ€ ๊ธฐ์ˆ ์ด ๋ถˆํŽธํ•˜๋ฉด ์‚ฌ์šฉํ•˜์ง€ ์•Š๊ณ  ์šฐํšŒํ•˜๊ฒŒ ๋˜๋ฉฐ, ๊ทธ ์ˆœ๊ฐ„ ์กฐ์ง์€ ๋ณด์•ˆ๊ณผ ์†๋„๋ฅผ ๋™์‹œ์— ์žƒ๋Š”๋‹ค๋Š” ์ง€์ ์ด๋‹ค. ๋ฐ˜๋Œ€๋กœ โ€˜์ •์ฒด์„ฑ์— ๋ฟŒ๋ฆฌ๋ฅผ ๋‘” ๋งค๋„๋Ÿฌ์šด ๊ฒฝํ—˜โ€™์„ ๊ตฌ์ถ•ํ•œ ๊ธฐ์—…์ด ํ˜์‹  ์†๋„์—์„œ ์•ž์„œ๊ฐˆ ๊ฒƒ์ด๋ผ๊ณ  ๋‚ด๋‹ค๋ดค๋‹ค.

5. ๊ฐ’๋น„์‹ผ ERP ๋งˆ์ด๊ทธ๋ ˆ์ด์…˜ ๋Œ€์‘ ๋ฐฉ์•ˆ ๋งˆ๋ จ

ERP ๋งˆ์ด๊ทธ๋ ˆ์ด์…˜์€ 2026๋…„์—๋„ CIO๋ฅผ ๊ฐ•ํ•˜๊ฒŒ ์••๋ฐ•ํ•  ์ „๋ง์ด๋‹ค. ์ธ๋ณด์ด์Šค ๋ผ์ดํ”„์‚ฌ์ดํด ๊ด€๋ฆฌ ์†Œํ”„ํŠธ์›จ์–ด ์—…์ฒด ๋ฐ”์Šค์›จ์–ด(Basware)์˜ CIO ๋ฐฐ๋Ÿฟ ์‰ฌ์œ„์ธ ๋Š” โ€œ์˜ˆ๋ฅผ ๋“ค์–ด SAP S/4HANA ๋งˆ์ด๊ทธ๋ ˆ์ด์…˜์€ ๋ณต์žกํ•˜๊ณ , ๊ณ„ํš๋ณด๋‹ค ๊ธธ์–ด์ง€๋ฉด์„œ ๋น„์šฉ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ์‰ฌ์œ„์ธ ๋Š” ์—…๊ทธ๋ ˆ์ด๋“œ ๋น„์šฉ์ด ๊ธฐ์—… ๊ทœ๋ชจ์™€ ๋ณต์žก๋„์— ๋”ฐ๋ผ 1์–ต ๋‹ฌ๋Ÿฌ ์ด์ƒ, ๋งŽ๊ฒŒ๋Š” 5์–ต ๋‹ฌ๋Ÿฌ๊นŒ์ง€ ๋›ธ ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋งํ–ˆ๋‹ค.

๋˜ํ•œ, ERP๊ฐ€ โ€˜๋ชจ๋“  ๊ฒƒ์„ ํ•˜๋ ค๋Š”โ€™ ๊ตฌ์กฐ์ธ ๋งŒํผ, ์ธ๋ณด์ด์Šค ์ฒ˜๋ฆฌ์ฒ˜๋Ÿผ ํŠน์ • ์—…๋ฌด๋ฅผ ์•„์ฃผ ์ž˜ ํ•ด๋‚ด๋Š” ๋ฐ์—๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค๊ณ  ๋งํ–ˆ๋‹ค. ์—ฌ๊ธฐ์— ์ˆ˜๋งŽ์€ ์• ๋“œ์˜จ ์ปค์Šคํ„ฐ๋งˆ์ด์ง•์ด ๋”ํ•ด์ง€๋ฉด ๋ฆฌ์Šคํฌ๊ฐ€ ์ปค์ง„๋‹ค. ์‹œ์œ„์ธ ๋Š” ์ด์— ๋Œ€ํ•œ ๋Œ€์•ˆ์œผ๋กœ๋Š” SAP๊ฐ€ ๊ฐ•์ ์„ ๊ฐ–๋Š” ํ•ต์‹ฌ์€ ๊ทธ๋Œ€๋กœ ๋‘๊ณ , ์ฃผ๋ณ€ ๊ธฐ๋Šฅ์€ ๋ฒ ์ŠคํŠธ ์˜ค๋ธŒ ๋ธŒ๋ฆฌ๋“œ ๋„๊ตฌ๋กœ ๋ณด์™„ํ•˜๋Š” โ€˜ํด๋ฆฐ ์ฝ”์–ด(clean core)โ€™ ์ „๋žต์„ ์ œ์‹œํ–ˆ๋‹ค.

6. ํ˜์‹ ์„ ํ™•์žฅํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐ์ดํ„ฐ ๊ฑฐ๋ฒ„๋„Œ์Šค

2026๋…„ ํ˜์‹ ์„ ์ง€์† ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋งŒ๋“ค๋ ค๋ฉด, ๋ชจ๋“ˆํ˜•ยทํ™•์žฅํ˜• ์•„ํ‚คํ…์ฒ˜์™€ ๋ฐ์ดํ„ฐ ์ „๋žต์ด ํ•ต์‹ฌ์ด๋ผ๋Š” ์˜๊ฒฌ๋„ ๋‚˜์™”๋‹ค. ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํ”Œ๋žซํผ ์—…์ฒด ์‚ผ์‚ฌ๋ผ(Samsara)์˜ CIO ์Šคํ‹ฐ๋ธ ํ”„๋ž€์ฒดํ‹ฐ๋Š” โ€œํ˜์‹ ์ด ํ™•์žฅ ๊ฐ€๋Šฅํ•˜๊ณ  ์ง€์† ๊ฐ€๋Šฅํ•˜๋ฉฐ ์•ˆ์ „ํ•˜๊ฒŒ ์ด๋ค„์ง€๋„๋ก ํ•˜๋Š” ๊ธฐ๋ฐ˜์„ ์„ค๊ณ„ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•œ ์šฐ์„ ์ˆœ์œ„ ์ค‘ ํ•˜๋‚˜โ€๋ผ๊ณ  ๋งํ–ˆ๋‹ค.

ํ”„๋ž€์ฒดํ‹ฐ๋Š” ๋А์Šจํ•˜๊ฒŒ ๊ฒฐํ•ฉ๋œ API ์šฐ์„  ์•„ํ‚คํ…์ฒ˜๋ฅผ ๊ตฌ์ถ• ์ค‘์ด๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋” ๋น ๋ฅด๊ฒŒ ์›€์ง์ด๊ณ  ๋ณ€ํ™”์— ์œ ์—ฐํ•˜๊ฒŒ ๋Œ€์‘ํ•˜๋ฉด์„œ ์†”๋ฃจ์…˜ ์—…์ฒด์™€ ํ”Œ๋žซํผ ์ข…์†์„ ํ”ผํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์„ค๋ช…ํ–ˆ๋‹ค. ์›Œํฌํ”Œ๋กœ์šฐยท๋„๊ตฌยทAI ์—์ด์ „ํŠธ๊นŒ์ง€ ๋” ์—ญ๋™์ ์œผ๋กœ ๋ฐ”๋€Œ๋Š” ํ™˜๊ฒฝ์—์„œ โ€˜๊ฐ•ํ•˜๊ฒŒ ๊ฒฐํ•ฉ๋œ ์Šคํƒโ€™์€ ํ™•์žฅ์— ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค๋Š” ํŒ๋‹จ์ด๋‹ค. ๋˜ํ•œ ๋ฐ์ดํ„ฐ๋Š” AI๋ฟ ์•„๋‹ˆ๋ผ ๋น„์ฆˆ๋‹ˆ์Šค ์ธ์‚ฌ์ดํŠธ, ๊ทœ์ œ ๋Œ€์‘, ๊ณ ๊ฐ ์‹ ๋ขฐ๋ฅผ ์œ„ํ•œ ์žฅ๊ธฐ ์ „๋žต ์ž์‚ฐ์ด๋ผ๋ฉฐ, ๋ฐ์ดํ„ฐ ํ’ˆ์งˆ๊ณผ ๊ฑฐ๋ฒ„๋„Œ์Šค, ์ ‘๊ทผ์„ฑ์„ ์ „์‚ฌ์ ์œผ๋กœ ๊ฐ•ํ™”ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ๋ง๋ถ™์˜€๋‹ค.

7. ์ธ๋ ฅ ์ „ํ™˜ ๊ฐ€์†ํ™”

AI ์‹œ๋Œ€ ์ธ๋ ฅ ์ „๋žต์€ โ€˜์ฑ„์šฉโ€™๋งŒ์œผ๋กœ ํ•ด๊ฒฐ๋˜์ง€ ์•Š๋Š”๋‹ค. ์ž„์› ์„œ์น˜ยท๊ฒฝ์˜ ์ปจ์„คํŒ… ๊ธฐ์—… ํ•˜์ด๋“œ๋ฆญ ์•ค ์ŠคํŠธ๋Ÿฌ๊ธ€์Šค(Heidrick & Struggles)์˜ ํŒŒํŠธ๋„ˆ ์Šค์ฝง ํ†ฐ์Šจ์€ โ€œ์—…์Šคํ‚ฌ๋ง๊ณผ ๋ฆฌ์Šคํ‚ฌ๋ง์€ ์ฐจ์„ธ๋Œ€ ๋ฆฌ๋”๋ฅผ ํ‚ค์šฐ๋Š” ํ•ต์‹ฌโ€์ด๋ผ๋ฉฐ, โ€œ2026๋…„์˜ ๊ธฐ์ˆ  ๋ฆฌ๋”๋Š” ์ œํ’ˆ ์ค‘์‹ฌ์˜ ๊ธฐ์ˆ  ๋ฆฌ๋”๋กœ์„œ, ์ œํ’ˆยท๊ธฐ์ˆ ยท๋น„์ฆˆ๋‹ˆ์Šค๋ฅผ ์‚ฌ์‹ค์ƒ ํ•˜๋‚˜๋กœ ๋ฌถ์–ด์•ผ ํ•œ๋‹คโ€๋ผ๊ณ  ๊ฐ•์กฐํ–ˆ๋‹ค.

ํ†ฐ์Šจ์€ โ€˜๋””์ง€ํ„ธ ์ธ์žฌ ๊ณต์žฅโ€™ ๋ชจ๋ธ์„ ์ œ์•ˆํ–ˆ๋‹ค. ์—ญ๋Ÿ‰ ๋ถ„๋ฅ˜ ์ฒด๊ณ„(๊ธฐ์ˆ  ์—ญ๋Ÿ‰ ๋ถ„๋ฅ˜), ์—ญํ•  ๊ธฐ๋ฐ˜ ํ•™์Šต ๊ฒฝ๋กœ, ์‹ค์ „ ํ”„๋กœ์ ํŠธ ์ˆœํ™˜์„ ๊ตฌ์กฐํ™”ํ•ด ๋‚ด๋ถ€์—์„œ ์ธ์žฌ๋ฅผ ํ‚ค์šฐ๋Š” ๋ฐฉ์‹์ด๋‹ค. ๋˜ํ•œ AI๊ฐ€ ํ™œ์„ฑํ™”๋œ ํ™˜๊ฒฝ์— ๋งž์ถฐ ์ง๋ฌด๋ฅผ ์žฌ์„ค๊ณ„ํ•˜๊ณ  ์ž๋™ํ™”๋กœ ๊ณ ๋„์˜ ์ „๋ฌธ ๋…ธ๋™ ์˜์กด๋„๋ฅผ ์ค„์ด๋ฉฐ, โ€˜ํ“จ์ „ ํŒ€(fusion teams)โ€™์œผ๋กœ ํฌ์†Œ ์—ญ๋Ÿ‰์„ ์กฐ์ง ์ „๋ฐ˜์— ํ™•์‚ฐํ•ด์•ผ ํ•œ๋‹ค๊ณ  ์„ค๋ช…ํ–ˆ๋‹ค.

8. ํŒ€ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๊ณ ๋„ํ™”

๊ธฐ์ˆ  ์กฐ์ง์—์„œ ๋ถˆํ™•์‹ค์„ฑ์ด ์ปค์งˆ์ˆ˜๋ก ๋ถˆ์•ˆ์ด ํ™•์‚ฐ๋˜๊ณ , ๊ทธ ์–‘์ƒ์€ ๊ฐœ์ธ๋ณ„๋กœ ๋‹ค๋ฅด๊ฒŒ ๋‚˜ํƒ€๋‚œ๋‹ค. CompTIA์˜ ์ตœ๊ณ  ๊ธฐ์ˆ  ์—๋ฐ˜์ ค๋ฆฌ์ŠคํŠธ ์ œ์ž„์Šค ์Šคํƒ ์ €๋Š” โ€œ๊ธฐ์ˆ  ๋ถ€์„œ์—์„œ ๋ถˆํ™•์‹ค์„ฑ์ด ๋ฏธ์น˜๋Š” 1์ฐจ ํšจ๊ณผ๋Š” ๋ถˆ์•ˆโ€์ด๋ผ๋ฉฐ, โ€œ๋ถˆ์•ˆ์€ ์‚ฌ๋žŒ๋งˆ๋‹ค ๋‹ค๋ฅธ ํ˜•ํƒœ๋กœ ๋“œ๋Ÿฌ๋‚œ๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ์Šคํƒ ์ €๋Š” ํŒ€์›๊ณผ์˜ ๋ฐ€์ฐฉ ์†Œํ†ต์„ ๊ฐ•ํ™”ํ•˜๊ณ , ๋” ํšจ๊ณผ์ ์ด๊ณ  ๊ด€๋ จ์„ฑ ๋†’์€ ๊ต์œก์œผ๋กœ ๋ถˆ์•ˆ์„ ๊ด€๋ฆฌํ•ด์•ผ ํ•œ๋‹ค๊ณ  ์ œ์•ˆํ–ˆ๋‹ค.

9. ๋ฏผ์ฒฉ์„ฑยท์‹ ๋ขฐยทํ™•์žฅ์„ฑ์„ ์œ„ํ•œ ์—ญ๋Ÿ‰ ๊ฐ•ํ™”

AI ์ž์ฒด๋ฟ ์•„๋‹ˆ๋ผ, ์ด๋ฅผ ์šด์˜ํ•  ์ˆ˜ ์žˆ๋Š” ์—ญ๋Ÿ‰๋„ 2026๋…„ ํ•ต์‹ฌ ๊ณผ์ œ ์ค‘ ํ•˜๋‚˜๋‹ค. ๋ณด์•ˆ ์†”๋ฃจ์…˜ ์—…์ฒด ๋„ท์Šค์ฝ”ํ”„(Netskope)์˜ CDIO ๋งˆ์ดํฌ ์•ค๋”์Šจ์€ โ€œAI๋ฅผ ๋„˜์–ด 2026๋…„ CIO ์šฐ์„ ์ˆœ์œ„๋Š” ๋ฏผ์ฒฉ์„ฑ, ์‹ ๋ขฐ, ํ™•์žฅ์„ฑ์„ ์ด๋„๋Š” ๊ธฐ๋ฐ˜ ์—ญ๋Ÿ‰์„ ๊ฐ•ํ™”ํ•˜๋Š” ๊ฒƒโ€์ด๋ผ๊ณ  ๋งํ–ˆ๋‹ค.

์•ค๋”์Šจ์€ ์ œํ’ˆ ์šด์˜ ๋ชจ๋ธ(product operating model)์ด ์ „ํ†ต์  ์†Œํ”„ํŠธ์›จ์–ด ํŒ€์„ ๋„˜์–ด, IAM, ๋ฐ์ดํ„ฐ ํ”Œ๋žซํผ, ํ†ตํ•ฉ ์„œ๋น„์Šค ๊ฐ™์€ ์—”ํ„ฐํ”„๋ผ์ด์ฆˆ ๊ธฐ๋ฐ˜ ์—ญ๋Ÿ‰๊นŒ์ง€ ํฌํ•จํ•˜๋Š” ํ˜•ํƒœ๋กœ ํ™•์žฅ๋  ๊ฒƒ์ด๋ผ๊ณ  ๋‚ด๋‹ค๋ดค๋‹ค. ์ด๋•Œ ์ง์›ยทํŒŒํŠธ๋„ˆยท๊ณ ๊ฐยท์„œ๋“œํŒŒํ‹ฐยทAI ์—์ด์ „ํŠธ ๋“ฑ โ€˜์ธ๊ฐ„/๋น„์ธ๊ฐ„ IDโ€™๋ฅผ ๋ชจ๋‘ ์ง€์›ํ•ด์•ผ ํ•˜๋ฉฐ, ์ตœ์†Œ ๊ถŒํ•œ๊ณผ ์ œ๋กœ ํŠธ๋Ÿฌ์ŠคํŠธ ์›์น™์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ์•ˆ์ „ํ•˜๊ณ  ์ ์‘ํ˜• ํ”„๋ ˆ์ž„์›Œํฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค๊ณ  ๊ฐ•์กฐํ–ˆ๋‹ค.

10. ์ง„ํ™”ํ•˜๋Š” IT ์•„ํ‚คํ…์ฒ˜

2026๋…„์—๋Š” ํ˜„์žฌ์˜ IT ์•„ํ‚คํ…์ฒ˜๊ฐ€ AI ์—์ด์ „ํŠธ์˜ ์ž์œจ์„ฑ์„ ๊ฐ๋‹นํ•˜์ง€ ๋ชปํ•˜๋Š” โ€˜๋ ˆ๊ฑฐ์‹œ ๋ชจ๋ธโ€™์ด ๋  ์ˆ˜๋„ ์žˆ๋‹ค. ์„ธ์ผ์ฆˆํฌ์Šค์˜ ์ตœ๊ณ  ์•„ํ‚คํ…ํŠธ ์—๋ฏผ ๊ฒŒ๋ฅด๋ฐ”๋Š” โ€œํšจ๊ณผ์ ์œผ๋กœ ํ™•์žฅํ•˜๋ ค๋ฉด ๊ธฐ์—…์€ ์ƒˆ๋กœ์šด ์—์ด์ „ํ‹ฑ ์—”ํ„ฐํ”„๋ผ์ด์ฆˆ๋กœ ์ „ํ™˜ํ•ด์•ผ ํ•œ๋‹คโ€๋ผ๋ฉฐ, ๋ฐ์ดํ„ฐ ์˜๋ฏธ๋ฅผ ํ†ตํ•ฉํ•˜๋Š” ๊ณต์œ  ์‹œ๋งจํ‹ฑ ๊ณ„์ธต, ์ค‘์•™ํ™”๋œ ์ง€๋Šฅ์„ ์œ„ํ•œ ํ†ตํ•ฉ AI/ML ๊ณ„์ธต, ํ™•์žฅ ๊ฐ€๋Šฅํ•œ ์—์ด์ „ํŠธ ์ธ๋ ฅ์˜ ๋ผ์ดํ”„์‚ฌ์ดํด์„ ๊ด€๋ฆฌํ•˜๋Š” ์—์ด์ „ํ‹ฑ ๊ณ„์ธต, ๋ณต์žกํ•œ ํฌ๋กœ์Šค ์‚ฌ์ผ๋กœ ์›Œํฌํ”Œ๋กœ์šฐ๋ฅผ ์•ˆ์ „ํ•˜๊ฒŒ ๊ด€๋ฆฌํ•˜๋Š” ์—”ํ„ฐํ”„๋ผ์ด์ฆˆ ์˜ค์ผ€์ŠคํŠธ๋ ˆ์ด์…˜ ๊ณ„์ธต ๋“ฑ 4๊ฐœ ๊ณ„์ธต์„ ์ œ์‹œํ–ˆ๋‹ค.

๊ฒŒ๋ฅด๋ฐ”๋Š” ์ด ์ „ํ™˜์ด โ€œ์—”๋“œ ํˆฌ ์—”๋“œ ์ž๋™ํ™”๋ฅผ ๋‹ฌ์„ฑํ•œ ๊ธฐ์—…๊ณผ ์—์ด์ „ํŠธ๊ฐ€ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ์‚ฌ์ผ๋กœ์— ๊ฐ‡ํžŒ ๊ธฐ์—…์„ ๊ฐ€๋ฅด๋Š” ๊ฒฐ์ •์  ๊ฒฝ์Ÿ๋ ฅโ€์ด ๋  ๊ฒƒ์ด๋ผ๊ณ  ๊ฐ•์กฐํ–ˆ๋‹ค.
dl-ciokorea@foundryco.com

10 top priorities for CIOs in 2026

A CIOโ€™s wish list is typically long and costly. Fortunately, by establishing reasonable priorities, itโ€™s possible to keep pace with emerging demands without draining your team or budget.

As 2026 arrives, CIOs need to take a step back and consider how they can use technology to help reinvent their wider business while running their IT capabilities with a profit and loss mindset, advises Koenraad Schelfaut, technology strategy and advisory global lead at business advisory firm Accenture. โ€œThe focus should shift from โ€˜keeping the lights onโ€™ at the lowest cost to using technology โ€ฆ to drive topline growth, create new digital products, and bring new business models faster to market.โ€

Hereโ€™s an overview of what should be at the top of your 2026 priorities list.

1. Strengthening cybersecurity resilience and data privacy

Enterprises are increasingly integrating generative and agentic AI deep into their business workflows, spanning all critical customer interactions and transactions, says Yogesh Joshi, senior vice president of global product platforms at consumer credit reporting firm TransUnion. โ€œAs a result, CIOs and CISOs must expect bad actors will use these same AI technologies to disrupt these workflows to compromise intellectual property, including customer sensitive data and competitively differentiated information and assets.โ€

Cybersecurity resilience and data privacy must be top priorities in 2026, Joshi says. He believes that as enterprises accelerate their digital transformation and increasingly integrate AI, the risk landscape will expand dramatically. โ€œProtecting sensitive data and ensuring compliance with global regulations is non-negotiable,โ€ Joshi states.

2. Consolidating security tools

CIOs should prioritize re-baselining their foundations to capitalize on the promise of AI, says Arun Perinkolam, Deloitteโ€™s US cyber platforms and technology, media, and telecommunications industry leader. โ€œOne of the prerequisites is consolidating fragmented security tools into unified, integrated, cyber technology platforms โ€” also known as platformization.โ€

Perinkolam says a consolidation shift will move security from a patchwork of isolated solutions to an agile, extensible foundation fit for rapid innovation and scalable AI-driven operations. โ€œAs cyber threats become increasingly sophisticated, and the technology landscape evolves, integrating cybersecurity solutions into unified platforms will be crucial,โ€ he says.

โ€œEnterprises now face a growing array of threats, resulting in a sprawling set of tools to manage them,โ€ Perinkolam notes. โ€œAs adversaries exploit fractured security postures, delaying platformization only amplifies these risks.โ€

3. Ensuring data protection

To take advantage of enhanced efficiency, speed, and innovation, organizations of all types and sizes are now racing to adopt new AI models, says Parker Pearson, chief strategy officer at data privacy and preservation firm Donoma Software.

โ€œUnfortunately, many organizations are failing to take the basic steps necessary to protect their sensitive data before unleashing new AI technologies that could potentially be left exposed,โ€ she warns, adding that in 2026 โ€œdata privacy should be viewed as an urgent priority.โ€

Implementing new AI models can raise significant concerns around how data is collected, used, and protected, Pearson notes. These issues arise across the entire AI lifecycle, from how the data used for initial training to ongoing interactions with the model. โ€œUntil now, the choices for most enterprises are between two bad options: either ignore AI and face the consequences in an increasingly competitive marketplace; or implement an LLM that could potentially expose sensitive data,โ€ she says. Both options, she adds, can result in an enormous amount of damage.

The question for CIOs is not whether to implement AI, but how to derive optimal value from AI without placing sensitive data at risk, Pearson says. โ€œMany CIOs confidently report that their organizationโ€™s data is either โ€˜fullyโ€™ or โ€˜end to endโ€™ encrypted.โ€ Yet Pearson believes that true data protection requires continuous encryption that keeps information secure during all states, including when itโ€™s being used. โ€œUntil organizations address this fundamental gap, they will continue to be blindsided by breaches that bypass all their traditional security measures.โ€

Organizations that implement privacy-enhancing technology today will have a distinct advantage in implementing future AI models, Pearson says. โ€œTheir data will be structured and secured correctly, and their AI training will be more efficient right from the start, rather than continually incurring the expense, and risk of retraining their models.โ€

4. Focusing on team identity and experience

A top priority for CIOs in 2026 should be resetting their enterprise identity and employee experience, says Michael Wetzel, CIO at IT security software company Netwrix. โ€œIdentity is the foundation of how people show up, collaborate, and contribute,โ€ he states. โ€œWhen you get identity and experience right, everything else, including security, productivity, and adoption, follows naturally.โ€

Employees expect a consumer-grade experience at work, Wetzel says. โ€œIf your internal technology is clunky, they simply wonโ€™t use it.โ€ When people work around IT, the organization loses both security and speed, he warns. โ€œEnterprises that build a seamless, identity-rooted experience will innovate faster while organizations that donโ€™t will fall behind.โ€

5. Navigating increasingly costly ERP migrations

Effectively navigating costly ERP migrations should be at the top of the CIO agenda in 2026, says Barrettโ€ฏSchiwitz, CIO atโ€ฏinvoice lifecycle management software firm Basware. โ€œSAP S/4HANA migrations, for instance, are complex and often take longer than planned, leading to rising costs.โ€ He notes that upgrades can cost enterprises upwards of $100 million, rising to as much as $500 million depending on the ERPโ€™s size and complexity.

The problem is that while ERPs try to do everything, they rarely perform specific tasks, such as invoice processing, really well, Schiwitz says. โ€œMany businesses overcomplicate their ERP systems, customizing them with lots of add-ons that further increase risk.โ€ The answer, he suggests, is adopting a โ€œclean coreโ€ strategy that lets SAP do what it does best and then supplement it with best-in-class tools to drive additional value.

6. Doubling-down on innovation โ€” and data governance

One of the most important priorities for CIOs in 2026 is architecting a foundation that makes innovation scalable, sustainable, and secure, says Stephen Franchetti, CIO at compliance platform provider Samsara.

Franchetti says heโ€™s currently building a loosely coupled, API-first architecture thatโ€™s designed to be modular, composable, and extensible. โ€œThis allows us to move faster, adapt to change more easily, and avoid vendor or platform lock-in.โ€ Franchetti adds that in an era where workflows, tools, and even AI agents are increasingly dynamic, a tightly bound stack simply wonโ€™t scale.

Franchetti is also continuing to evolve his enterprise data strategy. โ€œFor us, data is a long-term strategic asset โ€” not just for AI, but also for business insight, regulatory readiness, and customer trust,โ€ he says. โ€œThis means doubling down on data quality, lineage, governance, and accessibility across all functions.โ€

7. Facilitating workforce transformation

CIOs must prioritize workforce transformation in 2026, says Scott Thompson, a partner in executive search and management consulting company Heidrick & Struggles. โ€œUpskilling and reskilling teams will help develop the next generation of leaders,โ€ he predicts. โ€œThe technology leader of 2026 needs to be a product-centric tech leader, ensuring that product, technology, and the business are all one and the same.โ€

CIOs canโ€™t hire their way out of the talent gap, so they must build talent internally, not simply buy it on the market, Thompson says. โ€œThe most effective strategy is creating a digital talent factory with structured skills taxonomies, role-based learning paths, and hands-on project rotations.โ€

Thompson also believes that CIOs should redesign job roles for an AI-enabled environment and use automation to reduce the amount of specialized labor required. โ€œForming fusion teams will help spread scarce expertise across the organization, while strong career mobility and a modern engineering culture will improve retention,โ€ he states. โ€œTogether, these approaches will let CIOs grow, multiply, and retain the talent they need at scale.โ€

8. Improving team communication

A CIOโ€™s top priority should be developing sophisticated and nuanced approaches to communication, says James Stanger, chief technology evangelist at IT certification firm CompTIA. โ€œThe primary effect of uncertainty in tech departments is anxiety,โ€ he observes. โ€œAnxiety takes different forms, depending upon the individual worker.โ€

Stanger suggests working closer with team members as well as managing anxiety through more effective and relevant training.

9. Strengthening drive agility, trust, and scale

Beyond AI, the priority for CIOs in 2026 should be strengthening the enabling capabilities that drive agility, trust, and scale, says Mike Anderson, chief digital and information officer at security firm Netskope.

Anderson feels that the product operating model will be central to this shift, expanding beyond traditional software teams to include foundational enterprise capabilities, such as identity and access management, data platforms, and integration services.

โ€œThese capabilities must support both human and non-human identities โ€” employees, partners, customers, third parties, and AI agents โ€” through secure, adaptive frameworks built on least-privileged access and zero trust principles,โ€ he says, noting that CIOs who invest in these enabling capabilities now will be positioned to move faster and innovate more confidently throughout 2026 and beyond.

10. Addressing an evolving IT architecture

In 2026, todayโ€™s IT architecture will become a legacy model, unable to support the autonomous power of AI agents, predicts Emin Gerba, chief architect at Salesforce. He believes that in order to effectively scale, enterprises will have to pivot to a new agentic enterprise blueprint with four new architectural layers: a shared semantic layer to unify data meaning, an integrated AI/ML layer for centralized intelligence, an agentic layer to manage the full lifecycle of a scalable agent workforce, and an enterprise orchestration layer to securely manage complex, cross-silo agent workflows.

โ€œThis architectural shift will be the defining competitive wedge, separating companies that achieve end-to-end automation from those whose agents remain trapped in application silos,โ€ Gerba says.

The top 6 project management mistakes โ€” and what to do instead

Project managers are doing exactly what they were taught to do. They build plans, chase team members for updates, and report status. Despite all the activity, your leadership team is wondering why projects take so long and cost so much.

When projects donโ€™t seem to move fast enough or deliver the ROI you expected, it usually has less to do with effort and more with a set of common mistakes your project managers make because of how they were trained, and what that training left out. Most project teams operate like order takers instead of the business-focused leaders you need to deliver your organizationโ€™s strategy.

To accelerate strategy delivery in your organization, something has to change. The way projects are led needs to shift, and traditional project management approaches and mindsets wonโ€™t get you there.

Here are the most common project management mistakes we see holding teams back, and what you can do to help your project leaders shift from being order takers to drivers of IMPACT: instilling focus, measuring outcomes, performing, adapting, communicating, and transforming.

Mistake #1: Solving project problems instead of business problems

Project managers are trained to solve project problems. Scope creep. Missed deadlines. Resource bottlenecks. They spend their days managing tasks and chasing status updates, but most of them have no idea whether the work they manage is solving a real business problem.

Thatโ€™s not their fault. Theyโ€™ve been taught to stay in their lane in formal training and by many executives. Keep the project moving. Donโ€™t ask questions. Focus on delivery.

But no one is talking to them about the purpose of these projects and what success looks like from a business perspective, so how can they help you achieve it?

You donโ€™t need another project checked off the list. You need the business problem solved.

IMPACT driver mindset: Instill focus

Start by helping your teams understand the business context behind the work. What problem are we trying to solve? Why does this project matter to the organization? What outcome are we aiming for?

Your teams canโ€™t answer those questions unless you bring them into the strategy conversation. When they understand the business goals, not just the project goals, they can start making decisions differently. Their conversations change to ensure everyone knows why their work matters. The entire team begins choosing priorities, tradeoffs, and solutions that are aligned with solving that business problem instead of just checking tasks off the list.

Mistake #2: Tracking progress instead of measuring business value

Your teams are taught to track progress toward delivering outputs. On time, on scope, and on budget are the metrics they hear repeatedly. But those metrics only tell you if deliverables will be created as planned, not if that work will deliver the results the business expects.

Most project managers are taught to measure how busy the team is. Everyone walks around wearing their busy badge of honor as if that proves value. They give updates about whatโ€™s done, whatโ€™s in progress, and whatโ€™s late. But the metrics they use show how busy everyone is at creating outputs, not how theyโ€™re tracking toward achieving outcomes.

All of that busyness can look impressive on paper, but itโ€™s not the same as being productive. In fact, busy gets in the way of being productive.

IMPACT driver mindset: Measure outcomes

Now that the team understands what theyโ€™re doing and why, the next question to answer is how will we know weโ€™re successful.

Right from the start of the project, you need to define not just the business goal but how youโ€™ll measure it was successful in business terms. Did the project reduce cost, increase revenue, improve the customer experience? Thatโ€™s what you and your peers care about, but often thatโ€™s not the focus you ask the project people to drive toward.

Think about a project thatโ€™s intended to drive revenue but ends up costing you twice as much to deliver. If the revenue target stays the same, the project may no longer make sense. Or they might come up with a way to drive even higher revenue because they understood the way you measure success.

Shift how you measure project success from outputs to outcomes and watch how quickly your projects start creating real business value.

Mistake #3: Perfecting process instead of streamlining it

If your teams spend more time tweaking templates, building frameworks, or debating methodology than actually delivering results, processes become inefficient.

Often project managers are hired for their certifications, which leads many of them to believe their value is tied to how much of and how perfectly they create and follow that process. They work hard to make sure every box is checked, every template is filled out, and every report is delivered on time. But if the process becomes the goal, theyโ€™re missing the point.

You invested in project management to get business results, not build a deliverable machine, and the faster you achieve those results, the higher your return on your project investments.

IMPACT driver mindset: Perform relentlessly

With a clear plan to drive business value, now we need to show them how to accelerate. That means relentlessly evaluating, streamlining, and optimizing the delivery process so it helps the team achieve the project goals faster.

Give them permission to simplify. When the process slows them down or adds work that doesnโ€™t add value, they should be able to call it out.

This isnโ€™t an excuse to have no process or claim youโ€™re being agile just to skip the necessary steps. Itโ€™s about right-sizing the process, simplifying where you can, and being thoughtful about whatโ€™s truly needed to deliver the outcome. Do you really need a 30-page document no one will read, or would two pages that people actually use be enough? You donโ€™t need perfection. You need progress.

Mistake #4: Blaming people instead of leading them through change

A lot of leaders start from the belief that people are naturally resistant to change. When projects stall or results fall short, itโ€™s easy to assume someone just didnโ€™t want to change. Project teams blame people, then layer on more governance, more process, and more pressure. Most of the time, itโ€™s not a people problem. Itโ€™s how the changes are being done to people instead of with them.

People donโ€™t resist because theyโ€™re lazy or difficult. They resist because they donโ€™t understand why itโ€™s happening or what it means for them. And no amount of process will fix that.

IMPACT driver mindset: Adapt to thrive

With an accelerated delivery plan designed to drive business value, your project teams can now turn their attention to bringing people with them through the change process.

Change management is everyoneโ€™s job, not something you outsource to HR or a change team. Projects fail without good change management and everyone needs to be involved. Your teams must understand that people arenโ€™t resistant to change. Theyโ€™re resistant to having change done to them. You have to teach them how to bring others through the change process instead of pushing change at them.

Teach your project teams how to engage stakeholders early and often so they feel part of the change journey. When people are included, feel heard, and involved in shaping the solution, resistance starts to fade and you create a united force that supports your accelerated delivery plan.

Mistake #5: Communicating for compliance instead of engagement

The reason most project communication fails is because itโ€™s treated like a one-way path. Status reports people donโ€™t understand. Steering committee slides read to a room full of executives who arenโ€™t engaged. Unread emails. The information goes out because itโ€™s required, not because itโ€™s helping people make better decisions or take the right action.

But that kind of communication doesnโ€™t create clarity, build engagement, or drive alignment. And it doesnโ€™t inspire anyone to lean in and help solve the real problems.

IMPACT driver mindset: Communicate with purpose

To keep people engaged in the project and help it keep accelerating toward business goals, you need purpose-driven communication designed to drive actions and decisions. Your teams shouldnโ€™t just push information but enable action. That means getting the right people and the right message at the right time, with a clear next step.

If you want your projects to move faster, communication canโ€™t be a formality. When teams, sponsors, and stakeholders know whatโ€™s happening and why it matters, they make decisions faster. You donโ€™t need more status reports. You need communication that drives actions and decisions.

Mistake #6: Driving project goals instead of business outcomes

Most organizations still define the project leadership role around task-focused delivery. Get the project done. Hit the date. Stay on budget. Project managers have been trained to believe that finishing the project as planned is the definition of success. But thatโ€™s not how you define project success.

If you keep project managers out of the conversations about strategy and business goals, theyโ€™ll naturally focus on project outputs instead of business outcomes. This leaves you in the same place you are today. Projects are completed, outputs are delivered, but the business doesnโ€™t always see the impact expected.

IMPACT driver mindset: Transform mindset

When you help your teams instill focus, measure outcomes, perform relentlessly, adapt to thrive, and communicate with purpose, you do more than improve project delivery. You build the foundation for a different kind of leadership.

Shift how you and your organization see the project leadership role. Your project managers are no longer just running projects. Youโ€™re developing strategy navigators who partner with you to guide how strategy gets delivered, and help you see around corners, connect initiatives, and decide where to invest next.

When project managers are trusted to think this way and given visibility into the strategy, they learn how the business really works. They stop chasing project success and start driving business success.

More on project management:

ๅค‰ๅŒ–ใซๅผทใ„ๅŸบ็›คใฅใใ‚Šใงใ‚ฐใƒญใƒผใƒใƒซไผๆฅญใธโ€”โ€”ใƒˆใƒชใƒ‰ใƒผใƒซCIOใŒๆŒ‘ใ‚€ๆ”น้ฉใจใฏ

ใƒ™ใƒณใƒ€ใƒผ็ตŒ้จ“ใ‚’ๆญฆๅ™จใซใ€ไบ‹ๆฅญๆˆ้•ทใ‚’็‰ฝๅผ•ใ™ใ‚‹CIOใธ

โ€”โ€”ใ“ใ‚Œใพใงใฎใ‚ญใƒฃใƒชใ‚ขใซใคใ„ใฆๆ•™ใˆใฆใใ ใ•ใ„ใ€‚

็งใฎใ‚ญใƒฃใƒชใ‚ขใฏๅฏŒๅฃซ้€šใ‹ใ‚‰ๅง‹ใพใ‚Šใพใ—ใŸใ€‚7ๅนด้–“ใ€ไธปใซ่กŒๆ”ฟๅ‘ใ‘ใ‚ทใ‚นใƒ†ใƒ ใฎใ‚ทใ‚นใƒ†ใƒ ใ‚จใƒณใ‚ธใƒ‹ใ‚ขใจใ—ใฆๅƒใใ€็พๅ ดใงๆŠ€่ก“ใ‚’็ฃจใ„ใฆใใพใ—ใŸใ€‚

ใใฎๅพŒใ€2000ๅนดใซใ‚ฝใƒ•ใƒˆใƒใƒณใ‚ฏ๏ผˆ็พ ใ‚ฝใƒ•ใƒˆใƒใƒณใ‚ฏใ‚ฐใƒซใƒผใƒ—๏ผ‰ใธ่ปข่ทใ—ใพใ™ใ€‚ๅฝ“ๆ™‚ใฏๅญซๆญฃ็พฉใ•ใ‚“ใŒใ€Œใ“ใ‚Œใ‹ใ‚‰ใฏใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆใฎๆ™‚ไปฃใ ใ€ใจ็™บไฟกใ—ใฆใ„ใŸ้ ƒใงใ€็คพๅ†…ใงใฏๆฌกใ€…ใจใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆ้–ข้€ฃใฎใƒ™ใƒณใƒใƒฃใƒผใŒ็ซ‹ใกไธŠใŒใฃใฆใ„ใพใ—ใŸใ€‚ใใฎไธ€ใคใŒEใ‚ณใƒžใƒผใ‚นไบ‹ๆฅญใ€็พๅœจใฎใ‚ปใƒ–ใƒณใƒใƒƒใƒˆใ‚ทใƒงใƒƒใƒ”ใƒณใ‚ฐใงใ™ใ€‚็งใฏใ‚ทใ‚นใƒ†ใƒ ่ฒฌไปป่€…ใจใ—ใฆ็ซ‹ใกไธŠใ’ใซ้–ขใ‚ใ‚Šใ€็ด„8ๅนด้–“ใ€ไบ‹ๆฅญใฎๆˆ้•ทใ‚’ๆ”ฏใˆใ‚‹ๅฝนๅ‰ฒใ‚’ๆ‹…ใ„ใพใ—ใŸใ€‚

ๆฌกใซๆŒ‘ๆˆฆใ—ใŸใฎใฏใ€ๅค–้ฃŸITใƒ™ใƒณใƒใƒฃใƒผใฎใ‚ฌใƒซใƒ•ใƒใƒƒใƒˆใงใ™ใ€‚ใƒˆใƒชใƒ‰ใƒผใƒซใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚นใ‚’ใฏใ˜ใ‚ๆœ‰ๅใชๅค–้ฃŸใƒใ‚งใƒผใƒณใ‚’้กงๅฎขใซๆŒใคไผš็คพใงใ€ใ“ใ“ใงใฏ4ๅนด้–“ใ€้–‹็™บ่ฒฌไปป่€…ใจใ—ใฆใ‚ทใ‚นใƒ†ใƒ ้ขใ‚’ใƒชใƒผใƒ‰ใ™ใ‚‹ใ ใ‘ใงใชใใ€ๅ–ถๆฅญ่ฒฌไปป่€…ใ‚‚็ตŒ้จ“ใ—ใพใ—ใŸใ€‚ๆŠ€่ก“ใซๅŠ ใˆใฆใƒ“ใ‚ธใƒใ‚นใฎ็พๅ ดใ‚’ๅ‹•ใ‹ใ™้›ฃใ—ใ•ใจ้ข็™ฝใ•ใ‚’ไฝ“ๆ„ŸใงใใŸใฎใฏๅคงใใชๅŽ็ฉซใงใ—ใŸใ€‚

ใใฎๅพŒใฏๆŠ•่ณ‡ไผš็คพOakใ‚ญใƒฃใƒ”ใ‚ฟใƒซ๏ผˆ็พ UNIVAใƒปOakใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚น๏ผ‰ใซ็งปใ‚Šใ€็ด„8ๅนด้–“ใซใ‚ใŸใฃใฆๆŠ•่ณ‡ๅ…ˆใฎไผๆฅญใซใƒใƒณใ‚บใ‚ชใƒณใง้–ขใ‚ใ‚Šใพใ—ใŸใ€‚็ตŒๅ–ถๅ†ๅปบใ‚„ใƒใƒชใƒฅใƒผใ‚ขใƒƒใƒ—ใ€ๆ™‚ใซใฏ่‡ชใ‚‰็คพ้•ทใซๅฐฑไปปใ™ใ‚‹ใชใฉใ€็ตŒๅ–ถใใฎใ‚‚ใฎใซๆทฑใๅ…ฅใ‚Š่พผใ‚€็ตŒ้จ“ใ‚’็ฉใฟใพใ—ใŸใ€‚ใ“ใฎๆ™‚ๆœŸใซๅŸนใฃใŸใ€Œไบ‹ๆฅญใ‚’ใฉใ†็ซ‹ใฆ็›ดใ—ใ€ๆˆ้•ทใธๅฐŽใใ‹ใ€ใจใ„ใ†่ฆ–็‚นใฏใ€ไปŠใฎ่‡ชๅˆ†ใฎๅคงใใช่ฒก็”ฃใซใชใฃใฆใ„ใพใ™ใ€‚

ใใ—ใฆ2019ๅนดใ€ใƒˆใƒชใƒ‰ใƒผใƒซใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚นใฎCIOใซ็€ไปปใ—ใพใ—ใŸใ€‚ใกใ‚‡ใ†ใฉ6ๅนดใŒ็ตŒ้Žใ—ใŸใจใ“ใ‚ใงใ™ใŒใ€ใ“ใ‚Œใพใงใฎใ‚ญใƒฃใƒชใ‚ขใง็ฉใฟ้‡ใญใฆใใŸใƒ™ใƒณใƒ€ใƒผใจใ—ใฆใฎ็Ÿฅ่ญ˜ใ€ไบ‹ๆฅญไผš็คพใงใฎ็ตŒ้จ“ใ€ใใ—ใฆ็ตŒๅ–ถ่€…ใจใ—ใฆใฎ่ฆ–็‚นใฎใ™ในใฆใ‚’็ทๅ‹•ๅ“กใ—ใ€ไบ‹ๆฅญๆˆ้•ทใ‚’็‰ฝๅผ•ใ™ใ‚‹CIOใจใ—ใฆๆŒ‘ๆˆฆใ‚’็ถšใ‘ใฆใ„ใพใ™ใ€‚

ใ‚ญใƒฃใƒชใ‚ขใ‚’ๅค‰ใˆใŸใ€Œใƒ“ใ‚ธใƒใ‚นใ‚’ใคใใ‚‹ใ€ใจใ„ใ†ๆŒ‘ๆˆฆ

โ€”โ€”ใ“ใ‚Œใพใงใฎ็ตŒๆญดใฎไธญใงใ€็‰นใซๅฐ่ฑกใซๆฎ‹ใฃใฆใ„ใ‚‹ไป•ไบ‹ใฏใ‚ใ‚Šใพใ™ใ‹๏ผŸ

ๆŒฏใ‚Š่ฟ”ใ‚‹ใจใ€ใใ‚Œใžใ‚Œใฎๆฅญ็จฎใ‚„็ซ‹ๅ ดใงๅคงใใชๆŒ‘ๆˆฆใŒใ‚ใ‚Šใพใ—ใŸใ€‚ๆœ€ๅˆใซSIใซๆบใ‚ใฃใฆใ„ใŸ้ ƒใฏใ€ใฉใ‚Œใ ใ‘ใฎ่ฆๆจกใฎใƒ—ใƒญใ‚ธใ‚งใ‚ฏใƒˆใ‚’ๅ›žใ›ใ‚‹ใ‹ใŒ่‡ชๅˆ†ใฎๆˆ้•ทใฎใ‚‚ใฎใ•ใ—ใงใ—ใŸใ€‚ๅฝ“ๆ™‚ใ€800ไบบๆœˆ่ฆๆจกใฎ้–‹็™บใƒ—ใƒญใ‚ธใ‚งใ‚ฏใƒˆใ‚’20ไปฃใงไปปใ•ใ‚Œใฆใ„ใฆใ€ไปŠๆ€ใˆใฐใจใฆใ‚‚ๅคงใใช่ฒฌไปปใ‚’่‹ฅใ„ใ†ใกใซไธŽใˆใฆใใ‚Œใ‚‹ไผš็คพใ ใฃใŸใจๆ€ใ„ใพใ™ใ€‚

ใ‚ฝใƒ•ใƒˆใƒใƒณใ‚ฏใงใฏใ€ๅˆใ‚ใฆใ€Œใƒ“ใ‚ธใƒใ‚นใ‚’ใคใใ‚‹ใ€ใจใ„ใ†ใ“ใจใซๆŒ‘ๆˆฆใ—ใพใ—ใŸใ€‚ๆ‹…ๅฝ“ใ—ใŸใฎใฏใ€็พๅœจใฎใ‚ปใƒ–ใƒณใƒใƒƒใƒˆใ‚ทใƒงใƒƒใƒ”ใƒณใ‚ฐใซใคใชใŒใ‚‹Eใ‚ณใƒžใƒผใ‚นไบ‹ๆฅญใงใ™ใ€‚ๅฃฒไธŠใ‚ผใƒญใ‹ใ‚‰ใ‚นใ‚ฟใƒผใƒˆใ—ใ€ใ‚ทใ‚นใƒ†ใƒ ่ฒฌไปป่€…ใจใ—ใฆ็ด„200ๅ„„ๅ††่ฆๆจกใพใงไบ‹ๆฅญใŒๆˆ้•ทใ™ใ‚‹ใƒ—ใƒญใ‚ปใ‚นใ‚’ๆ”ฏใˆใŸ็ตŒ้จ“ใฏใ€่‡ชๅˆ†ใฎใ‚ญใƒฃใƒชใ‚ขใซใŠใ„ใฆ้žๅธธใซๅคงใใชๆ„ๅ‘ณใ‚’ๆŒใกใพใ—ใŸใ€‚ๅ˜ใชใ‚‹ใ‚ทใ‚นใƒ†ใƒ ้–‹็™บใงใฏใชใใ€ใƒ“ใ‚ธใƒใ‚นใ‚’ๆˆ้•ทใ•ใ›ใ‚‹ใ“ใจใซ็›ด็ตใ™ใ‚‹ไป•ไบ‹ใ ใฃใŸใ‹ใ‚‰ใงใ™ใ€‚

็พ่ทใงใ‚ใ‚‹ใƒˆใƒชใƒ‰ใƒผใƒซใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚นใฎCIOใจใ—ใฆใฎๆœ€ๅˆใฎๅคงไป•ไบ‹ใฏใ€ใ‚ทใ‚นใƒ†ใƒ ใฎๅ…จ้ข็š„ใชใƒขใƒ€ใƒŠใ‚คใ‚บใงใ—ใŸใ€‚็€ไปปใ—ใฆใ‹ใ‚‰6ๅนดใ‚’ใ‹ใ‘ใฆๅ–ใ‚Š็ต„ใ‚“ใงใใŸใฎใงใ™ใŒใ€ใ‚ˆใ†ใ‚„ใใ™ในใฆใฎ็ฝฎใๆ›ใˆใŒๅฎŒไบ†ใ™ใ‚‹ๆฎต้šŽใซใใฆใ„ใพใ™ใ€‚

ๅฝ“ๅˆใฏ3ๅนดใงๅฎŒไบ†ใ•ใ›ใ‚‹ใคใ‚‚ใ‚Šใงใ—ใŸใŒใ€็คพๅ†…ใฎไบ‹ๆƒ…ใ‚„ๆ—ขๅญ˜ใฎไป•็ต„ใฟใ‚’ไธๅฏงใซ่€ƒๆ…ฎใ—ใชใŒใ‚‰้€ฒใ‚ใ‚‹ๅฟ…่ฆใŒใ‚ใ‚Šใ€็ตๆžœใจใ—ใฆๆ™‚้–“ใ‚’ใ‹ใ‘ใฆใงใ‚‚็ขบๅฎŸใซใ‚„ใ‚Šๅˆ‡ใ‚‹ๅฝขใซใชใ‚Šใพใ—ใŸใ€‚

ๅ–ใ‚Š็ต„ใฟใฎใ‚นใ‚ฟใƒผใƒˆใฏใ€Œใ‚ทใ‚นใƒ†ใƒ ใŒใ„ใใคใ‚ใ‚‹ใฎใ‹ใ‚’ๆ•ฐใˆใ‚‹ใ€ใจใ“ใ‚ใ‹ใ‚‰ใงใ—ใŸใ€‚ๆœ€ๅˆใซๆด—ใ„ๅ‡บใ—ใŸๆ™‚็‚นใง180ใปใฉใฎใ‚ทใ‚นใƒ†ใƒ ใŒๅญ˜ๅœจใ—ใฆใ„ใฆใ€ใใ“ใ‹ใ‚‰ๆฅญๅ‹™ใฎ็›ฎ็š„ใซ็ซ‹ใก่ฟ”ใฃใฆๆ•ด็†ใ—ใ€็ตฑๅˆใ‚’้€ฒใ‚ใฆใใพใ—ใŸใ€‚ๆœ€็ต‚็š„ใซใฏ180ใฎใ‚ทใ‚นใƒ†ใƒ ใ‚’ๅคงๅน…ใซ้›†็ด„ใ—ใ€ไปŠใงใฏ40็จ‹ๅบฆใซใพใงๆธ›ใ‚‰ใ™ใ“ใจใŒใงใใฆใ„ใพใ™ใ€‚

ใ“ใ†ใ—ใฆใฟใ‚‹ใจใ€ใ‚ทใ‚นใƒ†ใƒ ใฎๆฃšๅธใ—ใ‹ใ‚‰ใƒขใƒ€ใƒŠใ‚คใ‚บใพใงใ‚’่‡ชๅˆ†ใฎๆ‰‹ใงใƒชใƒผใƒ‰ใ—ใฆใ“ใ‚‰ใ‚ŒใŸใ“ใจใฏใ€CIOใจใ—ใฆๆœ€ๅˆใซๅ–ใ‚Š็ต„ใ‚€ใซใตใ•ใ‚ใ—ใ„ใƒใƒฃใƒฌใƒณใ‚ธใ ใฃใŸใจๆ€ใ„ใพใ™ใ€‚

ใ€Œใ‚ชใƒšใƒฌใƒผใ‚ทใƒงใƒณ้ ˜ๅŸŸใ‚’ๅˆ‡ใ‚Š้›ขใ™ใ€ใจใ„ใ†ๆŒ‘ๆˆฆ

โ€”โ€”ใ“ใ‚Œใพใงใฎใ‚ญใƒฃใƒชใ‚ขใฎไธญใงใ€ๆœ€ใ‚‚ใƒใƒฃใƒฌใƒณใ‚ธใƒณใ‚ฐใ ใฃใŸๅ‡บๆฅไบ‹ใ‚’ๆ•™ใˆใฆใใ ใ•ใ„ใ€‚

ใจใฆใ‚‚็ฅž็ตŒใ‚’ไฝฟใฃใŸใฎใŒใ€ใƒˆใƒชใƒ‰ใƒผใƒซใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚นใงๆ‰‹ใŒใ‘ใŸๆฅญๅ‹™็ต„็น”ๆ”น้ฉใฎๅ–ใ‚Š็ต„ใฟใงใ™ใ€‚

ๅ…ทไฝ“็š„ใซใฏใ€ใƒˆใƒชใƒ‰ใƒผใƒซใ‚ฐใƒซใƒผใƒ—ใฎๆœฌ็คพๆฅญๅ‹™ใ‚’ใ€ๆŒใกๆ ชไผš็คพใจใ‚ทใ‚งใ‚ขใƒผใƒ‰ใ‚ตใƒผใƒ“ใ‚นไผš็คพใซๅˆ†ใ‘ใŸใ†ใˆใงใ€ใ‚ทใ‚งใ‚ขใƒผใƒ‰ใ‚ตใƒผใƒ“ใ‚นไผš็คพใŒๆ‹…ใฃใฆใ„ใ‚‹็ฎก็†้ƒจ้–€ใฎๅฎšๅž‹ๆฅญๅ‹™ใ‚’ใ‚ชใƒ•ใƒใƒฉใƒณใ‚นๅŒ–ใ—ใ€BPOใƒ™ใƒณใƒ€ใƒผใซ็งป็ฎกใ™ใ‚‹ใจใ„ใ†ๅ–ใ‚Š็ต„ใฟใงใ—ใŸใ€‚็คพๅ†…ใงๆ‹…ใฃใฆใ„ใŸๆฅญๅ‹™ใ‚’ๅค–้ƒจใซๅ‡บใ™ใจใ„ใ†ใฎใฏใ€ๅคง่ƒ†ใงใ€้žๅธธใซ็นŠ็ดฐใช่ชฟๆ•ดใ‚’ไผดใ†ใƒ—ใƒญใ‚ธใ‚งใ‚ฏใƒˆใงใ—ใŸใ€‚ใพใšใฏIT้ƒจ้–€ใ‹ใ‚‰็€ๆ‰‹ใ—ใพใ—ใŸใŒใ€ใ“ใ‚ŒใŒๆœ€ใ‚‚ๅคงๅค‰ใ ใฃใŸใจๆ€ใ„ใพใ™ใ€‚

็งใฏๅฝ“ๆ™‚ใ€ใ‚ทใ‚งใ‚ขใƒผใƒ‰ใ‚ตใƒผใƒ“ใ‚นไผš็คพใฎ็คพ้•ทใ‚’ๅ…ผๅ‹™ใ—ใฆใŠใ‚Šใ€ๆœ€ๅคงใง180ไบบใปใฉใฎใƒกใƒณใƒใƒผใ‚’็އใ„ใฆใ„ใพใ—ใŸใ€‚ใใ“ใซใฏIT้‹็”จใฎใƒใƒผใƒ ใ ใ‘ใงใชใใ€็ตŒ็†ใฎ่จ˜ๅธณใ‚’ๆ‹…ใ†ใƒ•ใ‚กใ‚คใƒŠใƒณใ‚น้ƒจ้šŠใ‚„ใ€ไบบไบ‹ใฎ็ตฆไธŽ่จˆ็ฎ—ใ‚’ๆ‹…ๅฝ“ใ™ใ‚‹้ƒจ้šŠใชใฉใ€ใ„ใ‚ใ‚†ใ‚‹ใ‚ชใƒšใƒฌใƒผใ‚ทใƒงใƒณๆฉŸ่ƒฝใŒ้›†็ด„ใ•ใ‚Œใฆใ„ใพใ—ใŸใ€‚ๆˆฆ็•ฅ็ซ‹ๆกˆใฏๆŒใกๆ ชไผš็คพใŒๆ‹…ใ„ใ€ๆ—ฅๅธธใฎใ‚ชใƒšใƒฌใƒผใ‚ทใƒงใƒณใฏไธ€ใคใซๆŸใญใฆ็ฎก็†ใ™ใ‚‹ไฝ“ๅˆถใ‚’ๆ•ดใˆใฆใ„ใŸใฎใงใ™ใ€‚ใใฎๆฅญๅ‹™ใ‚’ๅฐ‘ใ—ใšใคๅˆ‡ใ‚Šๅ‡บใ—ใฆๅค–้ƒจใซ็งปใ™ใจใ„ใ†ใฎใŒใ€ๅฝ“ๆ™‚ใฎ็งใฎๅฝนๅ‰ฒใงใ—ใŸใ€‚

ๅฝ“็„ถใ€ๆ—ขๅญ˜ใฎไป•ไบ‹ใ‚’ๆ‹…ใฃใฆใ„ใŸไบบๆใฎใ€Œๆฌกใฎใ‚ญใƒฃใƒชใ‚ขใ‚’ใฉใ†ใคใใ‚‹ใ‹ใ€ใŒ่ชฒ้กŒใซใชใ‚Šใพใ™ใ€‚ใƒˆใƒชใƒ‰ใƒผใƒซใฏๅ…ตๅบซ็œŒๅŠ ๅคๅทๅธ‚ใงๅ‰ตๆฅญใ—ใ€ใใฎๅพŒๅ…ตๅบซ็œŒ็ฅžๆˆธๅธ‚ใซๆœฌ็คพใ‚’็ฝฎใ„ใฆใ„ใพใ—ใŸใŒใ€ๅฝ“ๆ™‚ใ‚ทใ‚งใ‚ขใƒผใƒ‰ใ‚ตใƒผใƒ“ใ‚นไผš็คพใฎๆ‹ ็‚นใ‚‚็ฅžๆˆธใซใ‚ใ‚Šใพใ—ใŸใ€‚

ๆธ‹่ฐทใฎๆœฌ็คพใธ่ปขๅ‹คๅฏ่ƒฝใชไบบใซใฏใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚นใฎๆฅญๅ‹™ใ‚’ๆ‰“่จบใ—ใพใ—ใŸใŒใ€ๅฎถๅบญใฎไบ‹ๆƒ…ใชใฉใง่ปขๅ‹คใŒ้›ฃใ—ใ„ๆ–นใ‚‚ๅคšใใ„ใพใ—ใŸใ€‚ใใ†ใ—ใŸๆ–นใซใฏใ€BPOใƒ™ใƒณใƒ€ใƒผใธ่ปข็ฑใ—ใฆใ“ใ‚ŒใพใงใจๅŒใ˜ๆฅญๅ‹™ใ‚’็ถ™็ถšใ—ใฆใ‚‚ใ‚‰ใฃใŸใ‚Šใ€ใƒˆใƒชใƒ‰ใƒผใƒซใ‚ฐใƒซใƒผใƒ—ใฎๅบ—่ˆ—ใซๆดป่บใฎๅ ดใ‚’็งปใ—ใฆใ‚‚ใ‚‰ใฃใŸใ‚Šใจใ€ไธ€ไบบใฒใจใ‚Šใจ้ข่ซ‡ใ‚’้‡ใญใฆๆฌกใฎ้“ใ‚’ไธ€็ท’ใซๆฑบใ‚ใฆใ„ใใพใ—ใŸใ€‚

ใ‚‚ใกใ‚ใ‚“ใ€ใ“ใ‚Œใฏ็งใฒใจใ‚Šใงใงใใ‚‹ใ“ใจใงใฏใ‚ใ‚Šใพใ›ใ‚“ใ€‚้ƒจ้•ทใ‚„็ฎก็†่ทใฎใƒกใƒณใƒใƒผใซๅ”ๅŠ›ใ‚’ๅพ—ใฆใ€ๅพ“ๆฅญๅ“กใŸใกใจ็œŸๆ‘ฏใซๅฏพ่ฉฑใ‚’้‡ใญใชใŒใ‚‰้€ฒใ‚ใพใ—ใŸใ€‚ๆœ€็ต‚็š„ใซใฏใ€Œใใ‚Œใžใ‚ŒใŒๆฌกใฎ็’ฐๅขƒใง้•ทใๆดป่บใงใใ‚‹ใ“ใจใ€ใŒใ‚ดใƒผใƒซใงใ—ใŸใ€‚ไผš็คพใจใ—ใฆใฎๆ–น้‡ใฏๆ˜Ž็ขบใซใ‚ใ‚‹ไธ€ๆ–นใงใ€ใงใใ‚‹ใ ใ‘็ดๅพ—ๆ„Ÿใ‚’ๆŒใฃใฆ็€ๅœฐใ•ใ›ใ‚‹ใ“ใจใŒใ€่‡ชๅˆ†ใฎๆœ€ๅคงใฎไฝฟๅ‘ฝใ ใฃใŸใจๆ€ใ„ใพใ™ใ€‚

ๆŠ•่ณ‡ใ‚’ๆƒœใ—ใพใฌใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆใฎ็™บๆƒณใŒใ‚‚ใŸใ‚‰ใ—ใŸๆฐ—ใฅใ

โ€”โ€”ไป•ไบ‹ใ‚’ใ™ใ‚‹ไธŠใงๅฟƒใซๆฎ‹ใฃใฆใ„ใ‚‹่จ€่‘‰ใ‚„ๅ‡บๆฅไบ‹ใฏใ‚ใ‚Šใพใ™ใ‹๏ผŸ

ๅฟƒใซๆฎ‹ใฃใฆใ„ใ‚‹่จ€่‘‰ใฏ2ใคใ‚ใ‚Šใพใ™ใ€‚

ใพใšไธ€ใคใฏใ€ใ‚ปใƒ–ใƒณใƒใƒƒใƒˆใ‚ทใƒงใƒƒใƒ”ใƒณใ‚ฐใฎ็ซ‹ใกไธŠใ’ใซ้–ขใ‚ใฃใฆใ„ใŸ้ ƒใฎใ“ใจใงใ™ใ€‚ๅฝ“ๆ™‚ใ‚ปใƒ–ใƒณ&ใ‚ขใ‚คใƒปใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚นใฎไผš้•ทใ‚’ๅ‹™ใ‚ใฆใ„ใŸ้ˆดๆœจๆ•ๆ–‡ใ•ใ‚“ใฎ่จ€่‘‰ใ‚’ใ€ๅฝ“ๆ™‚ใฎไธŠๅธใงใ‚ใฃใฆไผš้•ทใฎใ”ๅญๆฏใงใ‚ใ‚‹ใ€้ˆดๆœจๅบทๅผ˜ใ•ใ‚“ใ‚ˆใ‚Šๆ•™ใˆใฆใ„ใŸใ ใ„ใŸใ“ใจใŒใ‚ใ‚Šใพใ—ใŸใ€‚

ใ‚ใ‚‹ใจใใ€Œไบบๅ‰ใง่ฉฑใ™ใจใใซใฉใ†ใ™ใ‚Œใฐ็ทŠๅผตใ—ใชใ„ใฎใงใ—ใ‚‡ใ†ใ‹ใ€ใจๅฐ‹ใญใŸใ‚‰ใ€ใ€Œ่ƒŒไผธใณใ›ใšใ€ๅˆ†ใ‹ใ‚‰ใชใ„ใ“ใจใฏ่ฉฑใ•ใšใ€็Ÿฅใฃใฆใ„ใ‚‹ใ“ใจใ ใ‘่ฉฑใ›ใฐ็ทŠๅผตใ—ใชใ„ใ€ใจใŠใฃใ—ใ‚ƒใฃใŸใ‚“ใงใ™ใ€‚็ขบใ‹ใซใ€ๅˆ†ใ‹ใ‚‰ใชใ„ใ“ใจใฏใ€Œๅˆ†ใ‹ใ‚‰ใชใ„ใ€ใจ่จ€ใˆใฐใ‚ˆใ„ใ€‚ใใ†ใ‚„ใฃใฆ็ญ‰่บซๅคงใง่ฉฑใ™ไบบใ“ใใ€ๅฎŸ็ธพใ‚’ๆฎ‹ใ—ใฆใ„ใ‘ใ‚‹ใฎใ ใจๅผทใๆ„Ÿใ˜ใพใ—ใŸใ€‚

ใ‚‚ใ†ไธ€ใคใฏๅŒใ˜ๆ™‚ๆœŸใ€ใ‚ปใƒ–ใƒณใƒใƒƒใƒˆใ‚ทใƒงใƒƒใƒ”ใƒณใ‚ฐใŒใƒคใƒ•ใƒผใฎๅญไผš็คพใฎไบ‹ๆฅญใ ใฃใŸ้ ƒใฎ็ตŒ้จ“ใงใ™ใ€‚ๅฝ“ๆ™‚ใฏใพใ ใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆใŒๆœฌๆ ผ็š„ใชใƒ“ใ‚ธใƒใ‚นใซใชใ‚ŠใใฃใฆใŠใ‚‰ใšใ€ๆ—ฅๆœฌใงใฏใƒคใƒ•ใƒผใŒๅ…ˆ้ง†ใ‘ใฆใ„ใฆใ€GoogleใŒใ‚ˆใ†ใ‚„ใๅ‚ๅ…ฅใ—ใŸใฐใ‹ใ‚Šใฎๆ™‚ๆœŸใงใ—ใŸใ€‚

ใƒฆใƒผใ‚ถใƒผใŒๆ€ฅๅข—ใ™ใ‚‹ใจใ‚ตใƒผใƒใŒๆททใฟๅˆใ„ใ€ใ‚ทใ‚นใƒ†ใƒ ใŒ้€ผ่ฟซใ™ใ‚‹ๅ ด้ขใ‚‚ๅคšใ‹ใฃใŸใฎใงใ™ใŒใ€ใใฎๆ™‚ใซๅฝ“ๆ™‚ใƒคใƒ•ใƒผใฎ็คพ้•ทใงใ‚ใฃใŸไบ•ไธŠ้›…ๅšใ•ใ‚“ใ‹ใ‚‰ใ€Œใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆใƒ“ใ‚ธใƒใ‚นใจใ„ใ†ใฎใฏใƒฆใƒผใ‚ถใƒผใฎใ‚ขใ‚ฏใ‚ปใ‚นใŒๅข—ใˆใŸใ‚‰ใ‚ตใƒผใƒใ‚’่ฟฝๅŠ ใ™ใ‚‹ใฎใŒใ‚ฒใƒผใƒ ใฎใƒซใƒผใƒซใชใ‚“ใ ใ€‚ใ€ใจ่จ€ใ‚ใ‚ŒใŸใ‚“ใงใ™ใ€‚ใใฎ่จ€่‘‰ใซใƒใƒƒใจใ—ใพใ—ใŸใ€‚

ๅพ“ๆฅใฎใ‚จใƒณใ‚ฟใƒผใƒ—ใƒฉใ‚คใ‚บใฎไธ–็•Œใงใฏใ€้ซ˜ไพกใชใƒชใ‚ฝใƒผใ‚นใ‚’ใฉใ†ๆœ€้ฉๅŒ–ใ—ใฆไฝฟใ„ๅˆ‡ใ‚‹ใ‹ใ€ใจใ„ใ†็™บๆƒณใŒๅŸบๆœฌใงใ—ใŸใ€‚็ง่‡ช่บซใ‚‚ใ€Œ้™ใ‚‰ใ‚ŒใŸ่ณ‡ๆบใ‚’ๅคงไบ‹ใซๆดป็”จใ™ใ‚‹ใ€ใ“ใจใ‚’ๅฝ“ใŸใ‚Šๅ‰ใ ใจๆ€ใฃใฆใ„ใŸใฎใงใ™ใ€‚

ใ—ใ‹ใ—ใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆใฎไธ–็•Œใงใฏใ€Œๅฎ‰ไพกใชใ‚ตใƒผใƒใ‚’ไธฆในใ‚Œใฐใ„ใ„ใ€ใจใ„ใ†็™บๆƒณใŒไธปๆตใงใ€ๆŠ•่ณ‡ใ‚’ๅ‰ๆใซใ—ใŸใ‚นใ‚ฑใƒผใƒซใ‚ขใ‚ฆใƒˆใฎๆ–‡ๅŒ–ใŒๆ นใฅใ„ใฆใ„ใพใ—ใŸใ€‚ใ‚‚ใ—่ฟฝๅŠ ๆŠ•่ณ‡ใŒใงใใชใ„ใฎใงใ‚ใ‚Œใฐใ€ใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆใƒ“ใ‚ธใƒใ‚น่‡ชไฝ“ใŒๆˆใ‚Š็ซ‹ใŸใชใ„ใจใ„ใ†่€ƒใˆๆ–นใงใ™ใ€‚

ใ“ใฎ่€ƒใˆๆ–นใฎ้•ใ„ใฏ่กๆ’ƒใงใ—ใŸใ€‚ใ‚จใƒณใ‚ฟใƒผใƒ—ใƒฉใ‚คใ‚บใฎใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใจใ€ใ‚คใƒณใ‚ฟใƒผใƒใƒƒใƒˆใฎใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใจใฎๅคงใใช้•ใ„ใ‚’ใพใ–ใพใ–ใจๆ„Ÿใ˜ใŸ็žฌ้–“ใงใ—ใŸใ—ใ€ใใฎ้•ใ„ใฏใ„ใพใชใŠใ€ไธ–ใฎไธญใงใฏๅฎŒๅ…จใซ่žๅˆใ—ใใ‚Œใฆใ„ใชใ„้ƒจๅˆ†ใŒๆฎ‹ใฃใฆใ„ใ‚‹ใจๆ„Ÿใ˜ใฆใ„ใพใ™ใ€‚

ๅค‰ๅŒ–ใซๅผทใ„ๅŸบ็›คใฅใใ‚Šใ“ใCIOใฎๆœ€ๅคงใฎใ‚„ใ‚ŠใŒใ„

โ€”โ€”CIOใจใ—ใฆใ€ใฉใฎใ‚ˆใ†ใชใจใ“ใ‚ใซใ‚„ใ‚ŠใŒใ„ใ‚’ๆ„Ÿใ˜ใพใ™ใ‹๏ผŸ

็งใซใจใฃใฆCIOใฎใ‚„ใ‚ŠใŒใ„ใฏใ€ใ€Œไผš็คพใŒ็›ฎๆŒ‡ใ™ๆ–นๅ‘ๆ€งใ‚’ๅŠ ้€Ÿใ•ใ›ใ‚‹ๅŸบ็›คใ‚’ใฉใ†ใ‚„ใฃใฆใคใใ‚‹ใ‹ใ€ใซๅฐฝใใ‚‹ใจๆ€ใฃใฆใ„ใพใ™ใ€‚

ๅฝ“็คพใฎใƒŸใƒƒใ‚ทใƒงใƒณใฏใ€ŒใŠๅฎขใ•ใพใซๆ„Ÿๅ‹•ไฝ“้จ“ใ‚’ๅฑŠใ‘ใ‚‹ใ“ใจใ€ใงใ™ใ€‚ใใฎๆœ€ๅ‰็ทšใซ็ซ‹ใฃใฆใ„ใ‚‹ใฎใฏๅบ—่ˆ—ใฎใ‚นใ‚ฟใƒƒใƒ•ใงใ‚ใ‚Šใ€ใใ‚Œใ‚’ๆ”ฏใˆใ‚‹ใƒžใƒใ‚ธใƒกใƒณใƒˆๅฑคใงใ™ใ€‚

ใจใฏใ„ใˆใ€ไบบใ ใ‘ใซ้ ผใ‚‹ใฎใซใฏ้™็•ŒใŒใ‚ใ‚Šใพใ™ใ‹ใ‚‰ใ€ใใ“ใงใ€Œ่ฃๅดใ‹ใ‚‰ๅฝผใ‚‰ใ‚’ใฉใ†ๆ”ฏใˆใ‚‹ใ‹ใ€ใŒ้‡่ฆใซใชใ‚Šใพใ™ใ€‚ๅค‰ๅŒ–ใซ็ด ๆ—ฉใๅฏพๅฟœใงใใ‚‹ใƒ“ใ‚ธใƒใ‚นๅŸบ็›คใ‚’ๆ•ดใˆใ‚‹ใ“ใจใ“ใใ€CIOใจใ—ใฆใฎ้†้†ๅ‘ณใ ใจๆ€ใ„ใพใ™ใ€‚

IT้ƒจ้–€ใŒ่‡ชๅˆ†ใŸใกใฎ่ซ–็†ใ ใ‘ใงๅ‹•ใ„ใฆใ„ใฆใ‚‚้ข็™ฝใใฏใชใ‚Šใพใ›ใ‚“ใ€‚ๅคงไบ‹ใชใฎใฏใ€Œใƒ“ใ‚ธใƒใ‚นใซใฉใ‚Œใ ใ‘่ฒข็Œฎใงใใฆใ„ใ‚‹ใ‹ใ€ใ€Œๅค‰ๅŒ–ใซใฉใ‚Œใ ใ‘ๆŸ”่ปŸใซๅฏพๅฟœใงใใ‚‹ๅŸบ็›คใ‚’็ฏ‰ใ‘ใŸใ‹ใ€ใจใ„ใ†ใ“ใจใงใ™ใ€‚

ไพ‹ใˆใฐไบ‹ๆฅญใฎใ‚นใ‚ฑใƒผใƒซใ‚’่€ƒใˆใ‚‹ใจใใ€ใ€Œๆฅญๆ…‹ใŒๅข—ใˆใŸใ‚‰ไธ€ใคใฎไป•็ต„ใฟใง่ณ„ใ†ใฎใ‹ใ€ใใ‚Œใจใ‚‚่ค‡ๆ•ฐใ‚’็ต„ใฟๅˆใ‚ใ›ใ‚‹ใฎใ‹ใ€ใจใ„ใฃใŸ่จญ่จˆๆ€ๆƒณใŒๅ•ใ‚ใ‚Œใพใ™ใ€‚ใพใŸใ€Œใ‚ตใƒผใƒๅฐๆ•ฐใ‚’ๅข—ใ‚„ใ™ใฎใ‹ใ€ไธ€ๅฐใ‚’ๅคง่ฆๆจกๅŒ–ใ™ใ‚‹ใฎใ‹ใ€ใจใ„ใ†ใ‚นใ‚ฑใƒผใƒซใ‚ขใ‚ฆใƒˆ๏ผใ‚นใ‚ฑใƒผใƒซใ‚ขใƒƒใƒ—ใฎๅˆคๆ–ญใ‚‚ๅฟ…่ฆใซใชใ‚Šใพใ™ใ€‚ใ“ใ†ใ—ใŸใ‚ขใƒผใ‚ญใƒ†ใ‚ฏใƒใƒฃใฎๆคœ่จŽใฏ้žๅธธใซ้ข็™ฝใ„้ƒจๅˆ†ใงใ™ใ€‚

ใ•ใ‚‰ใซใ€ไปŠใฎใ‚ˆใ†ใซๅค‰ๅŒ–ใฎๆฟ€ใ—ใ„ๆ™‚ไปฃใงใฏใ€็ตŒๅ–ถ้™ฃใŒใ€Œใ‚„ใฃใฑใ‚Šใ‚„ใ‚ใ‚ˆใ†ใ€ใจๆ–น้‡ใ‚’่ปขๆ›ใ™ใ‚‹ใ“ใจใฏๅฟ…ใš่ตทใ“ใ‚Šใพใ™ใ€‚ใใ‚“ใชใจใใซใ€Œๅคš้กใฎๆŠ•่ณ‡ใ‚’ใ—ใฆใ—ใพใฃใŸใ‹ใ‚‰ใ‚ทใ‚นใƒ†ใƒ ใ‚’ๆจใฆใ‚‰ใ‚Œใชใ„ใ€ใจใ„ใ†ใฎใงใฏๅ›ฐใ‚‹ใ‚ใ‘ใงใ™ใ€‚

ใ ใ‹ใ‚‰ใ“ใใ€็งใฏใชใ‚‹ในใใ‚ตใƒ–ใ‚นใ‚ฏใƒชใƒ—ใ‚ทใƒงใƒณใ€ใคใพใ‚ŠSaaSใ‚’ๆดป็”จใ—ใฆใ„ใพใ™ใ€‚็‰นใซใƒใƒƒใ‚ฏใ‚ชใƒ•ใ‚ฃใ‚นใฎใ‚ˆใ†ใซๆŸ”่ปŸๆ€งใŒๆฑ‚ใ‚ใ‚‰ใ‚Œใ‚‹้ ˜ๅŸŸใฏใ€SaaSใ‚’็ต„ใฟๅˆใ‚ใ›ใŸๆ–นใŒใƒชใ‚นใ‚ฏใ‚’ๆŠ‘ใˆใ‚‰ใ‚Œใพใ™ใ€‚

ใ“ใ†ใ—ใŸๅˆคๆ–ญใ‚’ๆ”ฏใˆใฆใ„ใ‚‹ใฎใฏใ€ใ‚จใƒณใ‚ธใƒ‹ใ‚ขใจใ—ใฆใฎ็ตŒ้จ“ใจใ€ไบ‹ๆฅญ็ตŒๅ–ถใซๆบใ‚ใฃใŸ็ตŒ้จ“ใฎไธกๆ–นใงใ™ใ€‚ใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใซ็ฒพ้€šใ—ใฆใ„ใชใ„ใจๆœ€้ฉใช้ธๆŠžใฏใงใใพใ›ใ‚“ใ—ใ€็ตŒๅ–ถใฎ่ฆ–็‚นใŒใชใ‘ใ‚Œใฐใ€Œใƒ“ใ‚ธใƒใ‚นใ‚’ใฉใ†ๆ”ฏใˆใ‚‹ใ‹ใ€ใจใ„ใ†็ญ”ใˆใ‚‚ๅ‡บใ›ใพใ›ใ‚“ใ€‚ใใฎไธกๆ–นใ‚’ๆดปใ‹ใ—ใฆ่€ƒใˆใ‚‰ใ‚Œใ‚‹ใฎใฏใ€CIOใจใ—ใฆใฎไธ€็•ชใฎๆฅฝใ—ใ•ใ ใจๆ€ใฃใฆใ„ใพใ™ใ€‚

ๅฎŸใฏ็งใฏITใƒ™ใƒณใƒ€ใƒผๆ™‚ไปฃใ‹ใ‚‰ใ€Œใ“ใ‚Œใ‹ใ‚‰ใฏSaaSใŒๅฟ…้ ˆใซใชใ‚‹ใ€ใจ่€ƒใˆใฆใ„ใพใ—ใŸใ€‚ๅฝ“ๆ™‚ใฏๆๆกˆใ—ใฆใ‚‚ใƒฆใƒผใ‚ถใƒผไผๆฅญใŒๆŽก็”จใ—ใชใ‘ใ‚Œใฐๅฝขใซใชใ‚Šใพใ›ใ‚“ใงใ—ใŸใŒใ€CIOใฎ็ซ‹ๅ ดใซใชใฃใฆๅˆใ‚ใฆใ€Œ่‡ชๅˆ†ใŒๆฑบใ‚ใ‚ŒใฐๅฎŸ่กŒใงใใ‚‹ใ€ใจๅฎŸๆ„Ÿใ—ใพใ—ใŸใ€‚ใ“ใ‚Œใฏ้žๅธธใซๅคงใใช้•ใ„ใงใ‚ใ‚Šใ€ไบ‹ๆฅญไผš็คพๅดใซ็งปใฃใŸใ‹ใ‚‰ใ“ใๆŒ‘ๆˆฆใงใใฆใ„ใ‚‹ใ“ใจใงใ™ใ€‚

ใƒˆใƒชใƒ‰ใƒผใƒซใ‚ฐใƒซใƒผใƒ—ใฏๅค‰ๅŒ–ใ‚’ๆใ‚Œใšใซ้€ฒๅŒ–ใ‚’็ถšใ‘ใฆใใŸไผš็คพใงใ™ใ€‚ใ ใ‹ใ‚‰ใ“ใๆ€ฅๆˆ้•ทใ—ใฆใ“ใ‚‰ใ‚ŒใŸใ—ใ€ๆ™‚ไปฃใฎ่’ๆณขใซใ‚‚ๆฒˆใพใšใซๅฏพๅฟœใ—ใฆใใพใ—ใŸใ€‚ใ“ใฎๅผทใฟใฏ็ตถๅฏพใซๅคฑใฃใฆใฏใ„ใ‘ใชใ„ใงใ™ใ‹ใ‚‰ใ€ใใฎใŸใ‚ใซใ‚‚ใ€ใ‚ทใ‚นใƒ†ใƒ ๅŸบ็›คใ‚’ๅ…จ้ข็š„ใซSaaSใซใ™ใ‚‹ๅ–ใ‚Š็ต„ใฟใ‚’้€ฒใ‚ใฆใใพใ—ใŸใ€‚

SaaSใƒ™ใƒณใƒ€ใƒผใฎ่ฃฝๅ“ใฎ่ฃใซใฏๅ„ช็ง€ใชใ‚จใƒณใ‚ธใƒ‹ใ‚ขใŒๆ•ฐๅคšใใ„ใฆใ€่€ƒใˆๆ–นใซใ‚ˆใฃใฆใฏๅฝผใ‚‰ๅ…จๅ“กใŒ็งใŸใกใ‚’ๆ”ฏใˆใฆใใ‚Œใฆใ„ใ‚‹ๅญ˜ๅœจใจใ‚‚่จ€ใˆใพใ™ใ€‚่‡ช็คพใฎๅŠ›ใ ใ‘ใงใฏใชใใ€ๅค–้ƒจใฎๅŠ›ใ‚’ใฉใ†็ต„ใฟๅˆใ‚ใ›ใ‚‹ใ‹ใ€‚ใใ‚Œใ‚’่จญ่จˆใงใใ‚‹ใ“ใจใ“ใใŒCIOใฎๅฝนๅ‰ฒใงใ‚ใ‚Šใ€็งใซใจใฃใฆใฎใ‚„ใ‚ŠใŒใ„ใชใฎใงใ™ใ€‚

โ€”โ€”AIๆดป็”จใซใคใ„ใฆใฏใ„ใ‹ใŒใงใ™ใ‹๏ผŸ

ไธ–ใฎไธญใงใฏ็”ŸๆˆAIใฐใ‹ใ‚ŠใŒๆณจ็›ฎใ•ใ‚Œใฆใ„ใพใ™ใŒใ€็งใŸใกใŒๆณจๅŠ›ใ—ใฆใ„ใ‚‹ใฎใฏใ€Œ็พๅ ดใฎ็”Ÿ็”ฃๆ€งใ‚’้ซ˜ใ‚ใ‚‹AIๆดป็”จใ€ใงใ™ใ€‚็”ŸๆˆAIใฏใƒ›ใƒฏใ‚คใƒˆใ‚ซใƒฉใƒผใฎๆฅญๅ‹™ๅŠน็އๅŒ–ใซใฏๆœ‰ๅŠนใงใ™ใŒใ€็งใŸใกใฎไบ‹ๆฅญใซ็›ด็ตใ™ใ‚‹็พๅ ดๆฅญๅ‹™ใงใฏใ€ใ‚‚ใฃใจๅฎŸๅ‹™็š„ใชAIใฎๅŠ›ใŒๅฟ…่ฆใ ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ใใฎไปฃ่กจไพ‹ใŒ้œ€่ฆไบˆๆธฌใงใ™ใ€‚ๅฃฒไธŠใ‚„ๆฅๅบ—ๅฎขๆ•ฐใ‚’AIใงไบˆๆธฌใ™ใ‚‹ใ“ใจใงใ€ใ€Œๆ˜Žๆ—ฅใฏไฝ•ไบบใฎใ‚นใ‚ฟใƒƒใƒ•ใ‚’้…็ฝฎใ™ในใใ‹ใ€ใ€Œใฉใ‚Œใ ใ‘้ฃŸๆใ‚’ไป•ๅ…ฅใ‚Œใ‚‹ในใใ‹ใ€ใจใ„ใฃใŸๅบ—่ˆ—ใƒžใƒใ‚ธใƒกใƒณใƒˆใฎ่จˆ็”ปใ‚’ๅŠน็އๅŒ–ใงใใพใ™ใ€‚ใ“ใ‚Œใซใ‚ˆใ‚Šใ€็พๅ ดใฎ่ฒ ๆ‹…ใ‚’ๅคงๅน…ใซ่ปฝๆธ›ใ™ใ‚‹ใ“ใจใŒใงใใพใ—ใŸใ€‚

ใ‚‚ใ†ไธ€ใคใฏ้ก”่ช่จผใ‚’ๆดป็”จใ—ใŸๅ‹คๆ€ ็ฎก็†ใงใ™ใ€‚ๅฝ“็คพใซใฏๅคšใใฎใƒ‘ใƒผใƒˆใƒปใ‚ขใƒซใƒใ‚คใƒˆใ‚นใ‚ฟใƒƒใƒ•ใŒๅƒใ„ใฆใŠใ‚Šใ€ใใฎๆ‰“ๅˆปไฝœๆฅญใฏๅคงใใช่ชฒ้กŒใงใ—ใŸใ€‚ๅพ“ๆฅใฎๆŒ‡็ด‹ใ‚„้™่„ˆ่ช่จผใงใฏๆฐดไป•ไบ‹ใ‚„ๅฏ’ใ•ใงไพ‹ๅค–ใŒ็™บ็”Ÿใ—ใŒใกใงใ—ใŸใŒใ€้ก”่ช่จผใซๅˆ‡ใ‚Šๆ›ฟใˆใฆใ‹ใ‚‰ใฏไพ‹ๅค–ใ‚ผใƒญใ€‚ใ—ใ‹ใ‚‚ๆ‰“ๅˆปใ‚นใƒ”ใƒผใƒ‰ใ‚‚้€Ÿใใ€ใƒžใ‚นใ‚ฏใ‚’ใ—ใฆใ„ใฆใ‚‚็žฌๆ™‚ใซ่ช่จผใงใใ‚‹ใŸใ‚ใ€็พๅ ดใ‹ใ‚‰ใ€Œๅ‹คๆ€ ใŒใ‚นใƒ ใƒผใ‚บใซใชใฃใŸใ€ใจๅฅฝ่ฉ•ใงใ™ใ€‚

ๆดพๆ‰‹ใ•ใฏใ‚ใ‚Šใพใ›ใ‚“ใŒใ€ใ“ใ†ใ—ใŸๅ–ใ‚Š็ต„ใฟใŒ็พๅ ดใฎ็”Ÿ็”ฃๆ€งใ‚’็€ๅฎŸใซๅผ•ใไธŠใ’ใฆใ„ใพใ™ใ€‚ใ“ใ‚Œใ“ใใŒใ€็งใŸใกใŒ็›ฎๆŒ‡ใ™AIๆดป็”จใฎๆœฌ่ณชใ ใจๆ€ใฃใฆใ„ใพใ™ใ€‚

CIOใซๅฟ…่ฆใชใฎใฏใ€Œใƒ“ใ‚ธใƒงใƒณใ‚’่ชžใ‚‹ใ“ใจใ€ใจใ€Œใ‚„ใ‚ŠๆŠœใ่ฆšๆ‚Ÿใ€

โ€”โ€”CIOใซๅฟ…่ฆใช่ณ‡่ณชใจใฏไฝ•ใงใ—ใ‚‡ใ†ใ‹๏ผŸ

็งใŒๆœ€ใ‚‚ๅคงไบ‹ใ ใจๆ€ใ†ใฎใฏใ€Œ่ฆšๆ‚Ÿใ€ใงใ™ใ€‚ใ‚‚ใกใ‚ใ‚“ใ€Œๆฑบใ‚ใŸใ“ใจใ‚’ใ‚„ใ‚Šๅˆ‡ใ‚‹ใ€ใ“ใจใ‚‚้‡่ฆใงใ™ใŒใ€ใใฎๅ‰ใซใ€Œไฝ•ใ‚’็›ฎๆŒ‡ใ™ใฎใ‹ใ€ใ‚’ใฏใฃใใ‚Šใจๆ‰“ใกๅ‡บใ•ใชใ‘ใ‚Œใฐใชใ‚Šใพใ›ใ‚“ใ€‚ๆœชๆฅใฎ็ตตใ‚’ๆใ„ใŸใ‚‰ใ€ใ€Œใ“ใฎๆ–นๅ‘ใธไผš็คพใ‚’ๅฐŽใ„ใฆใ„ใใ€ใจๅฎฃ่จ€ใ™ใ‚‹ใ€‚ใใฎๅฎฃ่จ€่‡ชไฝ“ใŒใ€CIOใซใจใฃใฆใฎ่ฆšๆ‚Ÿใฎ่จผใ ใจๆ€ใฃใฆใ„ใพใ™ใ€‚

็ง่‡ช่บซใ‚‚ใ€ŒDXใƒ“ใ‚ธใƒงใƒณใ€ใ‚’็คพๅค–ใซๅ…ฌ่กจใ—ใŸใ“ใจใงใ€ใ€Œใ‚‚ใ†็ตถๅฏพใซใ‚„ใ‚Šๅˆ‡ใ‚‹ใ—ใ‹ใชใ„ใ€ใจ่…นใŒๆฑบใพใ‚Šใพใ—ใŸใ€‚ใใ†ใ™ใ‚‹ใ“ใจใงใ€็คพๅ“กใ‚‚ใƒ™ใƒณใƒ€ใƒผใ‚‚ใ€Œใƒˆใƒชใƒ‰ใƒผใƒซใ‚ฐใƒซใƒผใƒ—ใฏใ“ใ†ใ„ใ†ๅงฟใ‚’็›ฎๆŒ‡ใ—ใฆใ„ใ‚‹ใฎใ ใ€ใจ็†่งฃใ—ใ€ๅŒใ˜ๆ–นๅ‘ใ‚’ๅ‘ใ‘ใ‚‹ใ‚ˆใ†ใซใชใ‚‹ใฎใงใ™ใ€‚ใ“ใ‚Œใฏ้žๅธธใซๅคงใใชๆ„ๅ‘ณใ‚’ๆŒใกใพใ™ใ€‚

CIOใซใฏใ€็›ฎๆŒ‡ใ™ๅงฟใ‚’็ตตใจใ—ใฆ็คบใ—ใ€ใใฎใƒ“ใ‚ธใƒงใƒณใซๅ‘ใ‹ใฃใฆใฒใŸใ™ใ‚‰็ชใ้€ฒใ‚€ๅŠ›ใŒๆฑ‚ใ‚ใ‚‰ใ‚Œใพใ™ใ€‚ใใฎ้š›ใ€ใƒใƒƒใ‚ฏใ‚ญใƒฃใ‚นใƒˆใฎ็™บๆƒณใŒๆฌ ใ‹ใ›ใพใ›ใ‚“ใ€‚ใ€Œใ“ใฎใ‚ดใƒผใƒซใซๅˆฐ้”ใ™ใ‚‹ใŸใ‚ใซใ€ไปŠไฝ•ใ‚’ใ™ในใใ‹ใ€ใ‚’้€†็ฎ—ใ—ใฆ่€ƒใˆใ‚‹ใฎใงใ™ใ€‚ใƒ•ใ‚ฉใ‚ขใ‚ญใƒฃใ‚นใƒˆใ€ใคใพใ‚Š็พ็Šถใฎๅปถ้•ท็ทšไธŠใง่ชฒ้กŒ่งฃๆฑบใ‚’็ฉใฟ้‡ใญใ‚‹ใ ใ‘ใงใฏใ€ๆ–ฐใ—ใ„ไพกๅ€คใฏ็”Ÿใพใ‚Œใพใ›ใ‚“ใ€‚

ใ‚‚ใกใ‚ใ‚“ใ€ไธ€ๅฎšใฎๅฎ‰ๅฎšๆœŸใซๅ…ฅใ‚Œใฐใƒ•ใ‚ฉใ‚ขใ‚ญใƒฃใ‚นใƒˆ็š„ใชๆ”นๅ–„ใงๅๅˆ†ใชใ“ใจใ‚‚ใ‚ใ‚Šใพใ™ใ€‚ใ—ใ‹ใ—ใ€ๅคงใใชๅค‰้ฉใ‚’่ตทใ“ใ™ๆ™‚ใซใฏใ€ใƒใƒƒใ‚ฏใ‚ญใƒฃใ‚นใƒˆใงๅคง่ƒ†ใซ้“็ญ‹ใ‚’ๆใๅฟ…่ฆใŒใ‚ใ‚Šใพใ™ใ€‚

ใใ—ใฆใ€ใจใใซๅคงใใชใ‚ฎใƒฃใƒƒใƒ—ใŒ็”Ÿใ˜ใŸใ‚‰ใ€Œ้•ใ†ใ€ใ“ใกใ‚‰ใซ่ˆตใ‚’ๅˆ‡ใ‚‹ใžใ€ใจๆžœๆ–ญใซๆ–นๅ‘่ปขๆ›ใงใใ‚‹โ€”โ€”ใ€‚ใ“ใ‚Œใ“ใใŒCIOใซๆฑ‚ใ‚ใ‚‰ใ‚Œใ‚‹่ณ‡่ณชใ ใจ็งใฏ่€ƒใˆใฆใ„ใพใ™ใ€‚

ใƒ‡ใ‚ธใ‚ฟใƒซๆ™‚ไปฃใฎใƒชใƒผใƒ€ใƒผใŒ่บซใซใคใ‘ใ‚‹ในใใ€Œไธ‰ๆœฌๆŸฑใ€ใจใฏ

โ€”โ€”ใ“ใ‚Œใ‹ใ‚‰CIOใ‚’็›ฎๆŒ‡ใ™ไบบๆใซๆฑ‚ใ‚ใ‚‰ใ‚Œใ‚‹ใ‚นใ‚ญใƒซใฏไฝ•ใงใ—ใ‚‡ใ†ใ‹๏ผŸ

็ง่‡ช่บซใ€ใƒใƒผใƒ ใฎใƒกใƒณใƒใƒผใซใฏใ€Œๅฐ†ๆฅใฏCIOใ‚„CTOใ€ใ‚ใ‚‹ใ„ใฏCDOใจใ„ใฃใŸๅฝนๅ‰ฒใ‚’ๆ‹…ใˆใ‚‹ไบบๆใซใชใฃใฆใปใ—ใ„ใ€ใจๅธธใ€…ไผใˆใฆใ„ใพใ™ใ€‚ๆ—ฅๆœฌใซใฏใพใ ใใ†ใ—ใŸไบบๆใŒๅๅˆ†ใซ่‚ฒใฃใฆใ„ใพใ›ใ‚“ใ€‚ใ ใ‹ใ‚‰ใ“ใใ€ๅคšใใฎไผๆฅญใงใƒ‡ใ‚ธใ‚ฟใƒซใ‚’ใƒ“ใ‚ธใƒใ‚นใซ็ตใณใคใ‘ใ‚‹ๆฉ‹ๆธกใ—ๅฝนใจใชใ‚Œใ‚‹ไบบใ‚’ๅข—ใ‚„ใ™ๅฟ…่ฆใŒใ‚ใ‚‹ใจๆ€ใฃใฆใ„ใพใ™ใ€‚่‹ฅใ„ไบบใ‚‚ใ€ๆœ€ๅˆใ‹ใ‚‰ใ“ใฎๅฝนๅ‰ฒใ‚’็›ฎๆŒ‡ใ—ใฆใ‚ญใƒฃใƒชใ‚ขใ‚’็ฉใ‚“ใงใปใ—ใ„ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ใใฎใŸใ‚ใซๅฟ…่ฆใชใฎใฏๅคงใใไธ‰ใคใฎๅŠ›ใงใ™ใ€‚

ใพใšใฏๅŸบ็คŽ็š„ใชๆŠ€่ก“ๅŠ›ใงใ™ใ€‚ใ‚ณใƒผใƒ‰ใ‚’ๆ›ธใ‘ใชใ„ITใƒชใƒผใƒ€ใƒผใ‚‚ใ„ใพใ™ใŒใ€ๆ›ธใ‘ใ‚‹ใซ่ถŠใ—ใŸใ“ใจใฏใ‚ใ‚Šใพใ›ใ‚“ใ€‚็ง่‡ช่บซใ‚‚ไธญๅญฆ็”Ÿใฎ้ ƒใ‹ใ‚‰ใ‚ณใƒผใƒ‰ใ‚’ๆ›ธใ„ใฆใใพใ—ใŸใ€‚ใƒ—ใƒญใ‚ฐใƒฉใƒŸใƒณใ‚ฐ่จ€่ชžใ‚‚ไธ€ใคใงใฏใชใใ€ไบŒใคไปฅไธŠๅญฆใถใ“ใจใงๆฏ”่ผƒใŒใงใใ€ใ‚ˆใ‚Šๆทฑใ„็†่งฃใซใคใชใŒใ‚Šใพใ™ใ€‚ใ“ใ‚Œใฏ่ปข่ทใ‚’็ตŒ้จ“ใ™ใ‚‹ใจๆ–ฐใ—ใ„ไธ–็•ŒใŒ่ฆ‹ใˆใ‚‹ใฎใจๅŒใ˜ใงใ€่ค‡ๆ•ฐใฎ่ฆ–็‚นใ‚’ๆŒใคใ“ใจใŒ้‡่ฆใ ใจๆ€ใ„ใพใ™ใ€‚

ๆฌกใซๅฟ…่ฆใชใฎใฏใ‚ขใƒผใ‚ญใƒ†ใ‚ฏใƒˆใจใ—ใฆใฎๅŠ›ใงใ™ใ€‚ใƒฆใƒผใ‚ถใƒผไผๆฅญใฎCIOใฏใ€Œๆ—ขๅญ˜ใฎๆŠ€่ก“ใ‚’ใฉใ†็ต„ใฟๅˆใ‚ใ›ใ€่‡ช็คพใฎใƒ“ใ‚ธใƒใ‚นใซๆœ€้ฉใชๆง‹้€ ใ‚’ใคใใ‚‹ใ‹ใ€ใ‚’ๅธธใซ่€ƒใˆใชใ‘ใ‚Œใฐใชใ‚Šใพใ›ใ‚“ใ€‚CTOใฎๅฝนๅ‰ฒใซ่ฟ‘ใ„้ƒจๅˆ†ใงใ‚‚ใ‚ใ‚Šใพใ™ใŒใ€ใƒใƒƒใƒˆใƒฏใƒผใ‚ฏใ‚„ใ‚คใƒณใƒ•ใƒฉใ€ใ‚ฏใƒฉใ‚ฆใƒ‰ใจใ„ใฃใŸๅŸบ็คŽใ‚’็†่งฃใ—ใฆใ„ใชใ„ใจใ€ๆœ€้ฉใช็ต„ใฟๅˆใ‚ใ›ใ‚’ๅˆคๆ–ญใงใใพใ›ใ‚“ใ€‚ใ‚ทใ‚นใƒ†ใƒ ใ‚ขใƒผใ‚ญใƒ†ใ‚ฏใƒˆใจใ—ใฆใฎ็Ÿฅ่ญ˜ใจ็™บๆƒณใฏๅฟ…้ ˆใ ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ใใ—ใฆๆœ€ๅพŒใฏใ‚ณใƒŸใƒฅใƒ‹ใ‚ฑใƒผใ‚ทใƒงใƒณๅŠ›ใงใ™ใ€‚ใƒ—ใƒญใ‚ธใ‚งใ‚ฏใƒˆใŒใ†ใพใใ„ใ‹ใชใ„ๅŽŸๅ› ใฎๅคšใใฏใ€ๆŠ€่ก“ๅŠ›ไธ่ถณใ‚ˆใ‚Šใ‚‚ใ‚ณใƒŸใƒฅใƒ‹ใ‚ฑใƒผใ‚ทใƒงใƒณไธ่ถณใซใ‚ใ‚Šใพใ™ใ€‚็งใฏ1on1ใ‚’ใ‚ˆใใ‚„ใ‚Šใพใ™ใŒใ€็›ธๆ‰‹ใฏ็คพ้•ทใ‹ใ‚‰ใ‚ฐใƒซใƒผใƒ—ไผš็คพใฎๅฝนๅ“กใ€ไบ‹ๆฅญไผš็คพใฎๅนน้ƒจใพใงๅน…ๅบƒใ„ใงใ™ใ€‚ๅฝผใ‚‰ใŒใ€Œไฝ•ใ‚’ใ‚„ใ‚ŠใŸใ„ใฎใ‹ใ€ใ‚’็†่งฃใ—ใชใ‘ใ‚Œใฐใ€ๅ…ˆใ‚’่ฆ‹ๆฎใˆใŸใ‚ทใ‚นใƒ†ใƒ ่จญ่จˆใฏใงใใพใ›ใ‚“ใ—ใ€ไฟก้ ผใงใใ‚‹็›ธ่ซ‡็›ธๆ‰‹ใซใชใ‚Œใชใ‘ใ‚Œใฐ่‰ฏใ„ๆˆๆžœใ‚‚ๅ‡บใ›ใพใ›ใ‚“ใ€‚ใ“ใ‚Œใฏ่‡ชๅˆ†ใ ใ‘ใงใชใใ€้ƒจ้•ทใ‚ฏใƒฉใ‚นใฎใƒกใƒณใƒใƒผใซใ‚‚ๆฑ‚ใ‚ใฆใ„ใพใ™ใ€‚

ๅŸบ็คŽ็š„ใชๆŠ€่ก“ๅŠ›ใ€ใ‚ขใƒผใ‚ญใƒ†ใ‚ฏใƒˆใจใ—ใฆใฎๆง‹็ฏ‰ๅŠ›ใ€ใใ—ใฆใ‚ณใƒŸใƒฅใƒ‹ใ‚ฑใƒผใ‚ทใƒงใƒณๅŠ›โ€”โ€”ใ€‚ใ“ใฎไธ‰ใคใฏCIOใ‚’็›ฎๆŒ‡ใ™ไธŠใงๆฌ ใ‹ใ›ใชใ„่ณ‡่ณชใงใ™ใ€‚BtoBไผๆฅญใชใ‚‰็‰นใซใ€ใƒ‘ใƒผใƒˆใƒŠใƒผไผๆฅญใจใฎ้–ขไฟ‚ใŒ้‡่ฆใงใ™ใ‹ใ‚‰ใ€่‹ฅใ„ใ†ใกใ‹ใ‚‰ๅผทใๆ„่ญ˜ใ—ใฆใปใ—ใ„ใจๆ€ใฃใฆใ„ใพใ™ใ€‚

็›ฎๆŒ‡ใ™ใฏใ€Œไธ–็•Œใซ้€šใ˜ใ‚‹ๅค–้ฃŸไผๆฅญใ€โ€•โ€•ใ‚ฐใƒญใƒผใƒใƒซใƒ–ใƒฉใƒณใƒ‰ใธใฎๆŒ‘ๆˆฆ

โ€”โ€”ไปŠๅพŒใฎๅฑ•ๆœ›ใซใคใ„ใฆๆ•™ใˆใฆใใ ใ•ใ„ใ€‚

ๅฝ“็คพใฏใ€Œใ‚ฐใƒญใƒผใƒใƒซใƒ•ใƒผใƒ‰ใ‚ซใƒณใƒ‘ใƒ‹ใƒผใ€ใ‚’ไผๆฅญใƒ“ใ‚ธใƒงใƒณใซๆŽฒใ’ใฆใ„ใพใ™ใ€‚็›ฎๆŒ‡ใ—ใฆใ„ใ‚‹ใฎใฏใ€ๆœ‰ๅใชใƒใƒณใƒใƒผใ‚ฌใƒผใƒใ‚งใƒผใƒณใ‚„ใ‚ณใƒผใƒ’ใƒผใƒใ‚งใƒผใƒณใจ่‚ฉใ‚’ไธฆในใ‚‹ใ€ๆ—ฅๆœฌๅˆใฎใ€Œไธ–็•Œใซ้€šใ˜ใ‚‹ๅค–้ฃŸไผๆฅญใ€ใซใชใ‚‹ใ“ใจใงใ™ใ€‚

ใƒˆใƒชใƒ‰ใƒผใƒซใ‚ฐใƒซใƒผใƒ—ใฏใ™ใงใซ30ใ‚ซๅ›ฝไปฅไธŠใซๅฑ•้–‹ใ—ใฆใ„ใพใ™ใŒใ€ใ™ในใฆใฎๅ›ฝใงๆ—ฅๆœฌใจๅŒใ˜ใ‚ฏใ‚ชใƒชใƒ†ใ‚ฃใƒผใ‚’ๅฎŸ็พใงใใฆใ„ใ‚‹ใ‹ใจใ„ใˆใฐใ€ใพใ ่ชฒ้กŒใŒๆฎ‹ใฃใฆใ„ใพใ™ใ€‚ใ“ใ“ใ‚’ใฉใ†ๅบ•ไธŠใ’ใ™ใ‚‹ใ‹ใŒใ€ใ“ใ‚Œใ‹ใ‚‰ใฎๅคงใใชใƒ†ใƒผใƒžใงใ™ใ€‚็งใฏใƒ‡ใ‚ธใ‚ฟใƒซใฎๅŠ›ใงๆฐดๆบ–ใ‚’ใใ‚ใˆใ€ใ•ใ‚‰ใซๆ–ฐใ—ใ„ๅ›ฝใธๅฑ•้–‹ใ—ใ‚„ใ™ใ„็’ฐๅขƒใ‚’ๆ•ดใˆใ‚‹ใ“ใจใŒใ€ใƒ“ใ‚ธใƒใ‚นใฎๅŠ ้€ŸใซใคใชใŒใ‚‹ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ใ“ใ‚Œใพใงใฏๆ—ฅๆœฌๅธ‚ๅ ดใซๆณจๅŠ›ใ—ใฆใใพใ—ใŸใŒใ€ไปŠๅพŒใฏใ‚ฐใƒญใƒผใƒใƒซใฎๅญไผš็คพใ‚„ใƒ•ใƒฉใƒณใƒใƒฃใ‚คใ‚บใƒ‘ใƒผใƒˆใƒŠใƒผใซๅฏพใ—ใฆใ€ใ‚ˆใ‚Š็ฉๆฅต็š„ใซๆ”ฏๆดใ—ใฆใ„ใใŸใ„ใจๆ€ใฃใฆใ„ใพใ™ใ€‚

ใ‚‚ใกใ‚ใ‚“ใ€ใ™ในใฆใ‚’ไธ€ๅพ‹ใฎไป•็ต„ใฟใซๅฝ“ใฆใฏใ‚ใ‚‹ใฎใฏ็พๅฎŸ็š„ใงใฏใ‚ใ‚Šใพใ›ใ‚“ใ€‚่ฃฝ้€ ๆฅญใฎใ‚ˆใ†ใซๅ…จไธ–็•ŒใงๅŒใ˜ใ‚ทใ‚นใƒ†ใƒ ใ‚’ๅฑ•้–‹ใ™ใ‚‹ใ‚ขใƒ—ใƒญใƒผใƒใ‚‚ใ‚ใ‚Šใพใ™ใŒใ€็งใŸใกๅค–้ฃŸ็”ฃๆฅญใงใฏใ€Œ็พๅœฐใฎไบบใซ้ฃŸในใฆใ‚‚ใ‚‰ใฃใฆๅˆใ‚ใฆไพกๅ€คใŒใ‚ใ‚‹ใ€ใ‚ใ‘ใงใ™ใ‹ใ‚‰ใ€ไธ€ๅฎšใฎ่‡ช็”ฑๅบฆใ‚’ๆฎ‹ใ—ใคใคใ€ใ€Œใƒˆใƒชใƒ‰ใƒผใƒซใ‚ฐใƒซใƒผใƒ—ใจใ—ใฆ็ตถๅฏพใซๅฎˆใฃใฆใปใ—ใ„ๅŸบๆบ–ใ€ใ‚’ใฉใ†ๆตธ้€ใ•ใ›ใ‚‹ใ‹ใŒ้‡่ฆใซใชใ‚Šใพใ™ใ€‚

ใใ“ใงๆœ‰ๅŠนใชใฎใŒใƒ‡ใ‚ธใ‚ฟใƒซๅŸบ็›คใงใ™ใ€‚ไป•็ต„ใฟใซ็ต„ใฟ่พผใ‚“ใงใ—ใพใˆใฐใ€ๆ„่ญ˜ใ›ใšใจใ‚‚่‡ช็„ถใซๅŸบๆบ–ใŒๆ‹…ไฟใ•ใ‚Œใ‚‹ใ€‚ใใ†ใ—ใŸไป•ๆŽ›ใ‘ใ‚’ๅข—ใ‚„ใ—ใฆใ„ใใŸใ„ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ใŸใ ใ—ใ‚„ใ‚Šใ™ใŽใ‚‹ใจใ€ๅฝ“็คพใฎๅผทใฟใงใ‚ใ‚‹ใ€Œๆ‰‹ใฅใใ‚ŠใƒปใงใใŸใฆใ€ใฎใ“ใ ใ‚ใ‚ŠใŒ่–„ใ‚Œใฆใ—ใพใ†ใƒชใ‚นใ‚ฏใ‚‚ใ‚ใ‚Šใพใ™ใ€‚ใใฎ็ทšๅผ•ใใ‚’ใฉใ†ใ™ใ‚‹ใ‹ใฏ้›ฃใ—ใ„่ชฒ้กŒใงใ™ใŒใ€ใ‚€ใ—ใ‚ใใ“ใซ้ข็™ฝใ•ใŒใ‚ใ‚‹ใจๆ„Ÿใ˜ใฆใ„ใพใ™ใ€‚

ใƒˆใƒƒใƒ—ใ‚„ไบ‹ๆฅญไผš็คพใฎ่ฒฌไปป่€…ใจไธ€็ท’ใซ่ญฐ่ซ–ใ‚’้‡ใญใ€็พๅœฐใซๅˆใฃใŸๆœ€้ฉใชใƒใƒฉใƒณใ‚นใ‚’่ฆ‹ใคใ‘ใฆใ„ใใ€‚ใใ†ใ—ใŸๅ–ใ‚Š็ต„ใฟใ‚’ใ‚ฐใƒญใƒผใƒใƒซใซๅบƒใ’ใฆใ„ใใŸใ„ใจๆ€ใฃใฆใ„ใพใ™ใ€‚

6 maxims for todayโ€™s digital leader playbook

Modern CIOs and tech leaders carry responsibility not only for an organizationโ€™s technology but, as key partners, for its entire business success. So having access to readily transferable lessons is critical in order to solve real business challenges, and lead with clarity, confidence, and purpose.

As a jumping off point, Iโ€™ve distilled here some of my favourite maxims from different business functions.

Maxim 2: Try to be human

Youโ€™re more interesting than you think. Try to be human. I realize this is a tough ask for us classic IT introvert types, but with many interactions now conducted remotely, itโ€™s even more important to find opportunities to meet in person.

Letting people know what makes you tick personally is of more interest than you could probably imagine. Colleagues are interested in you as a whole person, not simply as the person they work with. So donโ€™t be afraid to bring yourself to work, as the phrase goes. This allows others to do the same, and to talk about their own feelings and circumstances.

As an INTP (an introverted, intuitive, thinking, and perceiving type from the Myers-Briggs personality assessment), social events arenโ€™t my natural environment. And weโ€™ve probably all experienced how work and socializing sometimes donโ€™t mix. Is an orchestrated corporate event all that comfortable for anyone? But try to show up and meet people, relax a bit, and have some fun.

Maxim 6: Beware the IT cultural cringe

IT people often prefer to vent about the technology-ignorant business rather than stand up and explain the tech. Instead of declaring somethingโ€™s bad for the company or a dead-end, they shrug and say the business just doesnโ€™t get it.

No matter how great your strategy is, your plans will fail without a company culture that encourages people to implement it. I know from speaking to other CIOs that a frequent role for them is standing up for IT and defending their teams in a culture where the business blames IT for its failures.

Itโ€™s therefore vital to coach your teams to deal on equal terms with their internal business customers. Key to this is talking in business terms, not IT jargon. The reason for not adopting a nonstandard piece of tech is itโ€™ll inflate future company running costs, not that it doesnโ€™t neatly fit the IT estate. So stand up and be counted on a matter of tech principle, and win the debate.

Maxim 8: There are no IT projects, only business projects.

When IT projects fail, itโ€™s often because of a lack of ownership by the business.

The entire purpose of your IT department is to move the organization forward. So any investment must deliver on quantifiable financial targets or defined business objectives. If it doesnโ€™t, move on. This is fundamental. Forgetting to do so is easy when under pressure, as others press you with their own agendas, but dangerous for you and the business.

Everything Iโ€™ve learned and seen reinforces this. Without this focus, youโ€™re just an IT supplier taking orders, not the executive IT partner of the business. Question any actions by your team that canโ€™t be linked back to the companyโ€™s core objectives.

It all comes down to building relationships based on trust with your business colleagues who recognize that you understand what the business needs and can afford, so challenge projects not owned by the business leaders.

Maxim 10: The CIO as the personification of IT

Be vocal about your teamโ€™s successes and be honest about your mistakes. As CIO, youโ€™re the face of the IT function in your organization, and you set the tone for everyone in IT.

Try not to talk about the business and IT as separate entities. You and your team are just as integral to the company as sales, operations, or finance. Always talk about our business needs and what we should do.

Remember, youโ€™re accountable for all the IT. These days, we talk about being authentic, so being honest about your slip-ups, and how you feel about them, is important in establishing your reputation, both internally and externally.

Explain a success to others in the organization and why it worked. Bring out how collaboration between their teams and IT, working to aligned plans and objectives, made good things happen for everyone involved.

Maxim 36: Join up digital and IT

Digital natives need to work together with old techies. Advances of the last decade have been delivered by fast-moving digital startups, financed by deep-pocketed investors. Unsurprisingly, this has spawned organizational impatience with the costs and time taken by traditional or legacy IT functions. This frustration can then translate into setting up a completely separate digital department under a CDO, charged with implementing the new and faster-moving business.

Your current business is built on long-established ways of working, and processes that remain necessary, unless youโ€™re going to build them all a second time for the new digital channel. If not, then new components, including services and products, will have to interface with existing systems, as well as firmly established and mission-critical business processes. So with this dynamic, ensure that both traditional IT and new digital report to you.

Maxim 56: AI is a tech-driven business revolution

AI is the most overhyped bandwagon in technology, more than bitcoin, big data, and augmented and virtual reality. Nevertheless, itโ€™s the most far-reaching tech-driven change since the advent of the internet. In a matter of months, AI and AI agents are doing to white-collar jobs what production line robots did to blue-collar jobs 20 years ago.

AI is transforming the world and weโ€™re just at the beginning of this revolution. So what are you doing about it?

Your challenge as CIO is that AI has cut through to your board and executive leadership like nothing before. Furthermore, all your partners and suppliers are building AI agents into their software and services. Plus, all your best digital innovators in the business, and definitely all your recent grad hires, are using Chat GPT and bespoke AI tools in their day jobs. As CIO, you hold the keys to AI working well by effectively wielding the data in your systems. After all, you and your team are the ones who best understand how the AI works as the means to achieve business value.

New US CIO appointments, January 2026

Movers & Shakers is where you can keep up with new CIO appointments and gain valuable insight into the job market and CIO hiring trends. As every company becomes a technology company, CEOs and corporate boards are seeking multi-dimensional CIOs and IT leaders with superior skills in technology, communications, business strategy, and digital innovation. The role is more challenging than ever before โ€” but even more exciting and rewarding! If you have CIO job news to share, please email me!

Nationwide appoints Michael Carrel as CTO

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Michael Carrel, Nationwide

Nationwide

Nationwide provides a full range of insurance and financial services products across the US. Its insurance portfolio includes car, motorcycle, homeowners, pet, farm, life, and commercial policies. The company also offers annuities, mutual funds, retirement, plans and specialty health services. Carrel brings more than 30 years of experience within Nationwide Technology. Most recently, he served as SVP and CTO for Nationwide Financial where he was responsible for all tech solutions supporting Nationwideโ€™s financial services businesses. He earned a BS from Bowling Green State University and an MBA from the University of Dayton.

Anand Varadarajan named CTO for Starbucks

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Anand Varadarajan, Starbucks

Starbucks

Starbucks Coffee Company is a roaster and retailer of specialty coffee, and an American multinational chain, with cafes and stores around the globe. Varadarajan was most recently with Amazon, where he led technology and supply chain efforts for the Worldwide Grocery Stores business. Earlier in his career, he held software engineering roles at Oracle and contributed to several early-stage tech companies.ย Varadarajan earned a B. Tech from the Indian Institute of Technology and an MS from Purdue and from the University of Washington.

Goodyear welcomes Raman Mehta as CIO

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Raman Mehta Goodyear

Goodyear

The Goodyear Tire & Rubber Company, together with its subsidiaries, develops, manufactures, distributes, and sells tires, and related products and services worldwide. Most recently, Mehta served as SVP and CIO at Johnson Electric, where he led enterprise-wide transformation across ERP, PLM, smart manufacturing, analytics, and AI. His prior leadership experience includes CIO roles at Visteon Corporation, Fabrinet, Fiat Chrysler Automobiles, and a senior role at Oracle where he drove large-scale IT modernization, software-led transformation, and operational resilience across global automotive and manufacturing ecosystems.

Jim Fowler joins Lumen as CTPO

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Jim Fowler, Lumen

Lumen

Lumen Technologies isย a global tech company providing network, cloud, security, and IT services.Fowler joins from Nationwide Insurance, where he served as EVP and CTO, responsible for modernizing core tech capabilities, driving digital transformation of business operations, and scaling intelligent automation across the enterprise. Prior to Nationwide, Fowler held senior tech leadership roles at GE, including Global CIO, where he led the internal digital transformation strategy and operations. Fowler holds a BS from Miami University and an MBA from Xavier University.

DXC Technology appoints Russell Jukes as CDIO

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Russell Jukes, DXC Technology

DXC

DXC Technology is an enterprise tech and innovation partner delivering software, services, and solutions to global enterprises and public sector organizations. Jukes joined in 2017 and has played a pivotal role in shaping DXCโ€™s digital strategy and global technology capabilities. Before joining, he held senior roles across global tech organizations at HP and HPE, where he led modernization, enterprise engineering,ย and digital operations programs.

Dana Haggas named CIO for Emory University

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Dana Haggas, Emory University

Emory University

Emory University, in Atlanta, Georgia, is a private research university founded in 1836 and offers a wide range of undergraduate, graduate, and professional programs. Haggas joined as an application developer and has served in various IT leadership positions there, including manager of PeopleSoft applications, senior director, interim deputy CIO, and associate CIO in enterprise applications. She received a BS from the University of Georgia.

Associa appoints Michelle Johnson as chief information and transformation officer

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Michelle Johnson, Associa

Associa

Associa is a community association management firm, serving more than five million members. Most recently, Johnson served as a senior partner at Fortium Partners. Before that, she was EVP and CIO at Freeman Company, leading global technology strategy and teams of more than 200 employees and partners. Johnson has also held tech and business leadership positions at FedEx Office, Deloitte Consulting, and JCPenney. She earned a BA from St. Ambrose University and an MBA from the University of Kansas School of Business. ย 

Laura Fultz announced as CDIO for Emory Healthcare

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Laura Fultz, Emory Healthcare

Emory Healthcare

Emory Healthcare is a comprehensive healthcare system that offers 11 hospitals, the Emory Clinic, more than 250 provider locations, and more than 2,800 physicians specializing in 70 different medical subspecialties. Fultz joined as an application solution analyst and held several leadership roles as manager and corporate director, associate CIO and VP of applications and digital experience for Emory Healthcare. Fultz holds a BBA from the University of Georgia.

1-800-FLOWERS.COM, Inc. taps Alex Zelikovsky as CIO

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Alex Zelikovsky, 1-800-FLOWERS, Inc.

1-800-FLOWERS, Inc.

Founded in 1976, 1-800-FLOWERS.COM provides gifts for various occasions. The companyโ€™s portfolio includes more than 18 premium brands, such as 1-800-Flowers.com, Harry & David, PersonalizationMall.com, and Things Remembered. Most recently, Zelikovsky served as EVP and Global CIO at Pitney Bowes. Before that, he held divisional CIO and head of digital tech roles at Kimberly-Clark for both EMEA and Latin America, where he executed IT transformation strategies that drove business turnarounds and operating profit growth. He holds a bachelorโ€™s degree fromย Brooklynย College, and an MBA from the University ofย Chicagoโ€™sย Booth School of Business.

Westfield welcomes Lloyd Scholz as CIO

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Lloyd Scholz, Westfield

Westfield

Westfield is a property and casualty insurance company that underwrites commercial, personal, surety, and specialty lines of coverage. Most recently, Scholz served as senior managing director and CTO at Markel, where he led global teams supporting business operations across North America, Europe, the Middle East, and Asia-Pacific. Prior to that, he held progressive leadership roles focused on data engineering, analytics platforms, cloud strategy, and enterprise technology transformation at Capital One.

Christopher Mackie promoted to CIO at McGuireWoods

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Christopher Mackie, McGuireWoods

McGuireWoods

McGuireWoods represents financial services institutions, fintech company investment advisers, broker-dealers in litigation, and transactional and regulatory matters. Mackie was previously CTO at McGuireWoods, and managed a team of 70 professionals, oversaw the firmโ€™s IT budget, collaborated with the firmโ€™s AI and innovation team, and led a data governance initiative that reduced high-risk file exposures, and helped scale the firmโ€™s remote work capabilities during the COVID-19 pandemic. Before coming to McGuireWoods, Mackie held senior roles at Winston & Strawn LLP and Huron Consulting Group, leading IT teams in the legal, healthcare and higher education sectors.

Kendall Knight joins Intermodal Tank Transport as CIO

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Kendall Knight, Intermodal Tank Transport

Intermodal Tank Transport

Intermodal Tank Transport (ITT) is a global tank container logistics and transportation company. Knight arrives at Intermodal from Loomis where he served as CIO. His prior roles include CTO at Ceva Logistics, senior director enterprise applications at Hertz, and senior director of IT at Johnson Controls. Knight earned a BBA from the University of Kentucky and an MS from Houston Baptist University โ€“ Archie W. Dunham College of Business.

New CIO appointments, December 2025

Intel appoints Cindy Stoddard as CIO

John Hancock names Kartik Sakthivel CIO

Ameet Shetty joins RaceTrac as CIO

Guidehouse taps Ron White as CIO

AmeriLife names Sulabh Srivastava CIO

Tim Farris joins Clancy & Theys Construction Company as CIO

Ronald McDonald House Charities welcomes Jarrod Bell as CIO

Devang Patel joins Devereux as CIO

MIB promotes Daniel Gortze to CIO

New CIO appointments, November 2025

New York Life appoints Deepa Soni as CIO

Rohit Kapoor joins Whataburger as CDTTO

A.O. Smith taps Chris Howe as CDIO

Soma Venkat named CITAIO for Cooper Standard

Wella Company welcomes Julia Anderson as CDIO

Anthony Spangenberg joins MSPCA-Angell as CIO

Cengage Group welcomes Ken Grady as CIO

Marc Rubel joins Mirion as CIO

Smith names Mike Mercado CIO

Gregg Cottage promoted to CIO and CISO at NN, Inc.

CFA Institute taps Eliot Pikoulis as CIO

New CIO appointments, October 2025

State Farm names Joe Park as CDIO

Steve Bronson announced as CIO for Southern Glazerโ€™s Wine & Spirits

Bridge Specialty Group appoints Steve Emmons as CIO

Dawn-Marie Hutchinson joins Reynolds American as CIO

Amway welcomes Ryan Talbott as CTO

Randy Dougherty promoted to CIO for Trellix

Shayne Mehringer joins Redwood Services as CIO

Kratos promotes Brian Shepard to CIO

Ravi Soin named CIO and CISO for Smartsheet

Infoblox appoints Justin Kappers as CIO

Manu Narayan named CIO for GitLab

Boomi appoints Keyur Ajmera as CIO

Eric Skinner promoted to CIO for Citadel Credit Union

CONA Services appoints Francesco Quinterno as CIO

New CIO appointments, September 2025

Bank of America names Hari Gopalkrishnan CTIO

Vishal Talwar appointed CDIO for FedEx

Highmark Health announces Alistair Erskine as CIDO

Steven Dee joins Kohlโ€™s as CTO

AI Fire welcomes Mike Marchetti as CIO

Ted Doering joins Ball Corporation as CIO

SpartanNash names Ed Rybicki as CIO

Tara Long named CIO for FM

Trimble announces Jim Palermo as CIO

Bradley Lontz named CIO for CSAA Insurance Group

EchoStor Technologies welcomes Cale Anjoorian as CIO

Corey Farrell joins Peloton as CIO

AWP Safety appoints Craig Young as CIO

Georgeo Pulikkathara joins iMerit as CIO and CISO

Pathward appoints Charles Ingram as CIOO

Ardent Mills appoints Ryan Kelley as CIO

New CIO appointments, August 2025

Neal Sample joins Best Buy as CDTO

Southern Company names Hans Brown CITO

Tim Langley-Hawthorne named CTO of Loveโ€™s Travel Stops

QXO appoints Eric Nelson as CIO

Gaspare LoDuca named CIO for MIT

University of Wisconsin-Madison welcomes Didier Contis as CIO

Matt Keen joins Old National Bancorp as CIO

CHG Healthcare names Theresa Oโ€™Leary as CIO

Bill Poirier named CIO at the University of Central Florida

Avalara announces Shahan Parshad as CIO

Rajeev Khanna named CIO for Trucordia

Cottage Health Welcomes Ganesh Persad as CIO

Tara Cook joins Hinshaw & Culbertson as CIO

The tech leadership realizing more than the sum of parts

Waiting on replacement parts can be more than just an inconvenience. It can be a matter of sharp loss of income and opportunity. This is especially true for those who depend on industrial tools and equipment for agriculture and construction. So to keep things run as efficiently as possible, Parts ASAP CIO John Fraser makes sure end customer satisfaction is the highest motivation to get the tech implementation and distribution right.

โ€œWhat it comes down to, in order to achieve that, is the team,โ€ he says. โ€œI came into this organization because of the culture, and the listen first, act later mentality. Itโ€™s something I believe in and Iโ€™m going to continue that culture.โ€

Bringing in talent and new products has been instrumental in creating a stable e-commerce model, so Fraser and his team can help digitally advertise to customers, establish the right partnerships to drive traffic, and provide the right amount of data.

โ€œOnce youโ€™re a customer of ours, we have to make sure weโ€™re a needs-based business,โ€ he says. โ€œWe have to be the first thing that sticks in their mind because itโ€™s not about a track on a Bobcat that just broke. Itโ€™s $1,000 a day someoneโ€™s not going to make due to a piece of equipment thatโ€™s down.โ€

Ultimately, this strategy helps and supports customers with a collection of highly-integrated tools to create an immersive experience. But the biggest challenge, says Fraser, is the variety of marketplace channels customers are on.

โ€œSome people prefer our website,โ€ he says. โ€œBut some are on Walmart or about 20 other commercial channels we sell on. Each has unique requirements, ways to purchase, and product descriptions. On a single product, we might have 20 variations to meet the character limits of eBay, for instance, or the brand limitations of Amazon. So weโ€™ve built out our own product information management platform. It takes the right talent to use that technology and a feedback loop to refine the process.โ€

Of course, AI is always in the conversation since people canโ€™t write updated descriptions for 250,000 SKUs.

โ€œAI will fundamentally change what everybodyโ€™s job is,โ€ he says. โ€œI know I have to prepare for it and be forward thinking. We have to embrace it. If you donโ€™t, youโ€™re going to get left behind.โ€

Fraser also details practical AI adoption in terms of pricing, product data enhancement, and customer experience, while stressing experimentation without over-dependence. Watch the full video below for more insights, and be sure to subscribe to the monthly Center Stage newsletter by clicking here.

On consolidating disparate systems: You certainly run into challenges. People are on the same ERP system so they have some familiarity. But even within that, you have massive amounts of customization. Sometimes thatโ€™s very purpose-built for the type of process an organization is running, or that unique sales process, or whatever. But in other cases, itโ€™s very hard. Weโ€™ve acquired companies with their own custom built ERP platform, where they spent 20 years curating it down to eliminate every button click. Those donโ€™t go quite as well, but you start with a good culture, and being transparent with employees and customers about whatโ€™s happening, and you work through it together. The good news is it starts with putting the customer first and doing it in a consistent way. Tell people change is coming and build a rapport before you bring in massive changes. There are some quick wins and efficiencies, and so people begin to trust. Then, youโ€™re not just dragging them along but bringing them along on the journey.

On AI: Everybodyโ€™s talking it, but thereโ€™s a danger to that, just like there was a danger with blockchain and other kinds of immersive technologies. You have to make sure you know why youโ€™re going after AI. You canโ€™t just use it because itโ€™s a buzzword. You have to bake it into your strategy and existing use cases, and then leverage it. Weโ€™re doing it in a way that allows us to augment our existing strategy rather than completely and fundamentally change it. So for example, weโ€™re going to use AI to help influence what our product pricing should be. We have great competitive data, and a great idea of what our margins need to be and where the market is for pricing. Some companies are in the news because theyโ€™ve gone all in on AI, and AI is doing some things that are maybe not so appropriate in terms of automation. But if you can go in and have it be a contributing factor to a human still deciding on pricing, thatโ€™s where we are rather than completely handing everything over to AI.

On pooling data: We have a 360-degree view of all of our customers. We know when theyโ€™re buying online and in person. If theyโ€™re buying construction equipment and material handling equipment, weโ€™ll see that. But when somebodyโ€™s buying a custom fork for a forklift, thatโ€™s very different than someone needing a new water pump for a John Deere tractor. And having a manufacturing platform that allows us to predict a two and a half day lead time on that custom fork is a different system to making sure that water pump is at your door the next day. Trying to do all that in one platform just hasnโ€™t been successful in my experience in the past. So weโ€™ve chosen to take a bit of a hybrid approach where you combine the data but still have best in breed operational platforms for different segments of the business.

On scaling IT systems: The key is weโ€™re not afraid to have more than one operational platform. Today, in our ecosystem of 23 different companies, weโ€™re manufacturing parts in our material handling business, and thatโ€™s a very different operational platform than, say, purchasing overseas parts, bringing them in, and finding a way to sell them to people in need, where you need to be able to distribute them fast. Itโ€™s an entirely different model. So weโ€™re not establishing one core platform in that case, but the right amount of platforms. Itโ€™s not 23, but itโ€™s also not one. So as we think about being able to scale, itโ€™s also saying that if you try to be all things to all people, youโ€™re going to be a jack of all trades and an expert in none. So we want to make sure when we have disparate segments that have some operational efficiency in the back end โ€” same finance team, same IT teams โ€” weโ€™ll have more than one operational platform. Then through different technologies, including AI, ensure we have one view of the customer, even if theyโ€™re purchasing out of two or three different systems.

On tech deployment: Experiment early and then make certain not to be too dependent on it immediately. We have 250,000 SKUs, and more than two million parts that we can special order for our customers, and you canโ€™t possibly augment that data with a world-class description with humans. So we selectively choose how to make the best product listing for something on Amazon or eBay. But weโ€™re using AI to build enhanced product descriptions for us, and instead of having, say, 10 people curating and creating custom descriptions for these products, weโ€™re leveraging AI and using agents in a way that allow people to build the content. Now humans are simply approving, rejecting, or editing that content, so weโ€™re leveraging them for the knowledge they need to have, and if this going to be a good product listing or not. We know there are thousands of AI companies, and for us to be able to pick a winner or loser is a gamble. Our approach is to make it a bit of a commoditized service. But weโ€™re also pulling in that data and putting it back into our core operational platform, and there it rests. So if weโ€™re with the wrong partner, or they get acquired, or go out of business, we can switch quickly without having to rewrite our entire set of systems because we take it in, use it a bit as a commoditized service, get the data, set it at rest, and then we can exchange that AI engine. Weโ€™ve already changed it five times and weโ€™re okay to change it another five until we find the best possible partner so we can stay bleeding edge without having all the expense of building it too deeply into our core platforms.

Bitwise CIO Defends Bitcoin In 401(k)s Amid Sen. Warrenโ€™s New Warning

While a senator presses the Securities and Exchange Commission (SEC) against Bitcoin (BTC) and other cryptocurrencies in 401(k) plans, Bitwiseโ€™s CEO has defended the Trump administrationโ€™s push to allow digital assetsโ€™ inclusion in retirement funds.

Hougan Slams Bitcoin Restrictions In 401(k)s

On Monday, Bitwise CIO Matt Hougan discussed whether 2026 will be the year investors can own Bitcoin and other cryptocurrencies in 401(k) plans, as the inclusion of digital assets is becoming more common in individual retirement accounts (IRAs).

In an interview, the executive argued that providers are โ€œslow to move,โ€ but noted that the Trump administrationโ€™s pro-crypto shift, which removed โ€œwhat was effectively a ban on Bitcoin from 401(k)s,โ€ has opened the doors.

Hougan pointed out that large firms like Vanguard had strong restrictions but have recently relaxed their stance on Bitcoin investments. He argued that these bans are โ€œridiculous,โ€ calling BTC โ€œjust another assetโ€ that is no more volatile than stocks, such as those of Nvidia.

Does it go up and down? Absolutely. Is there risk in it? Absolutely. But itโ€™s actually less volatile over the last year than Nvidia stock. And you donโ€™t see any rules about banning 401k providers from offering Nvidia stock. Thatโ€™s not that would seem ridiculous.

Recent K33 Research data showed that Bitcoin recorded the least volatile year in the assetโ€™s history in 2025. Notably, BTC registered its lowest volatility level last year, with just 2.24%.

โ€œSo, I donโ€™t know if the 401(k) providers will get all the way to the point of actually putting it in this year. These are very slow moving institutions, but weโ€™re moving in that direction and eventually itโ€™ll be normalized like other assets, which is how it should be treated,โ€ he concluded.

Senator Warren Issues New Warning

Bitwise CEOโ€™s remarks came as Democratic Senator Elizabeth Warren reached out directly to SEC chairman Paul Atkins to question how the Commission intends to protect investors from potential financial risks now that crypto investments are allowed in retirement plans.

As reported by Bitcoinist, the Department of Labor (DOL) rescinded in May a 2022 guidance that discouraged fiduciaries from including cryptocurrency investments in 401(k) retirement plans.

Months later, US President Donald Trump signed an Executive Order (EO) that aimed to allow more private equity, real estate, cryptocurrency, and other alternative assets in 401(k) retirement accounts.

The EO, signed on August 7, 2025, directed the DOL and the SEC to reduce regulatory barriers that prohibited investments in alternative assets in their defined contribution retirement plans.

In a new letter, the anti-crypto senator shared her concerns, cautioning that allowing Bitcoin and other crypto assets into these accounts could enable significant risks. She listed the โ€œvolatility associated with cryptocurrencies, the lack of market transparency, and potential conflicts of interestโ€ as reasons to be cautious about introducing these assets into retirement plans.

She also emphasized that 401(k) plans are a vital source of retirement security for most Americans. Therefore, they should not be treated as a โ€œplayground for financial riskโ€ that could put investors in vulnerable positions.

Despite Warrenโ€™s warnings, multiple US lawmakers have supported the Trump Administrationโ€™s efforts. In September, nine House members asked Atkins to provide โ€œswift assistanceโ€ in implementing the presidentโ€™s executive order and work with the DOL to protect workers.

Later, House of Representatives member Troy Downing proposed a bill to codify Trumpโ€™s directive, giving โ€œthe force and effect of lawโ€ and making it easier for investors to access Bitcoin and other alternative assets in their 401(k) retirement plans.

bitcoin, btc, btcusdt

Southeast Asia CIOs Top Predictions on 2026: A Year of Maturing AI, Data Discipline, and Redefined Work

As 2026 begins, my recent conversations with Chief Information Officers across Southeast Asia provided me with a grounded view of how digital transformation is evolving. While their perspectives differ in nuance, they converge on several defining shifts: the maturation of artificial intelligence, the emergence of autonomous systems, a renewed focus on data governance, and a reconfiguration of work. These changes signal not only technological advancement but a rethinking of how Southeast Asia organizations intend to compete and create value in an increasingly automated economy.

For our CIOs, the year ahead represents a decisive moment as AI moves beyond pilots and hype cycles. Organizations are expected to judge AI by measurable business outcomes rather than conceptual promise. AI capabilities will become standard features embedded across applications and infrastructure, fundamental rather than differentiating. The real challenge is no longer acquiring AI technology but operationalizing it in ways that align with strategic priorities.

Among the most transformative developments is the rise of agentic AI โ€“ autonomous agents capable of performing tasks and interacting across systems. CIOs anticipate that organizations will soon manage not a single AI system but networks of agents, each with distinct logic and behaviour. This shift ushers in a new strategic focus, agentic AI orchestration. Organizations will need platforms that coordinate multiple agents, enforce governance, manage digital identity, and ensure trust across heterogeneous technology environments. As AI ecosystems grow more complex, the CIOโ€™s role evolves from integrator to orchestrator who directs a diverse array of intelligent systems.

As AI becomes more central to operations, data governance emerges as a critical enabler. Technology leaders expect 2026 to expose the limits of weak data foundations. Data quality, lineage, access controls, and regulatory compliance determine whether AI initiatives deliver value. Organizations that have accumulated โ€œdata debtโ€ will be unable to scale, while those that invest early will move with greater speed and confidence.

Automation in physical environments is also set to accelerate as CIOs expect robotics to expand across healthcare, emergency services, retail, and food and beverage sectors. Robotics will shift from specialised deployments to routine service delivery, supporting productivity goals, standardizing quality, and addressing persistent labour constraints.

Looking ahead, our regionโ€™s CIOs point to the early signals of quantum computingโ€™s relevance. While still emerging, quantum technologies are expected to gain visibility through evolving products and research. In my view, for Southeast Asia organizations, the priority is not immediate adoption but proactive monitoring, particularly in cybersecurity and long-term data protection, without undertaking premature architectural shifts.

IDGConnect_quantum_quantumcomputing_shutterstock_1043301451_1200x800

Shutterstock

Perhaps the most provocative prediction concerns the nature of work. As specialised AI agents take on increasingly complex task chains, one CIO anticipates the rise of โ€œcognitive supply chainsโ€ in which work is executed largely autonomously. Traditional job roles may fragment into task-based models, pushing individuals to redefine their contributions. Workplace identity could shift from static roles to dynamic capabilities, a broader evolution in how people create value in an AI-native economy.

One CIOs spotlight the changing nature of software development where natural-language-driven โ€œvibe codingโ€ is expected to mature, enabling non-technical teams to extend digital capabilities more intuitively. This trend will not diminish the relevance of enterprise software as both approaches will coexist to support different organizational needs.

CIO ASEAN Editorial final take:

Collectively, these perspectives shared by Southeast Asiaโ€™s CIO community point to Southeast Asia preparing for a structurally different digital future, defined by embedded AI, scaled autonomous systems, and disciplined data practices. The opportunity is substantial, but so is the responsibility placed on technology leaders.

As 2026 continue to unfold, the defining question will not simply be who uses AI, but who governs it effectively, integrates it responsibly, and shapes its trajectory to strengthen long-term enterprise resilience. Enjoy reading these top predictions for 2026 by our regionโ€™s most influential CIOs who are also our CIO100 ASEAN & Hong Kong Award 2025 winners:

Ee Kiam Keong
Deputy Chief Executive (Policy & Development)
concurrent Chief Information Officer
InfoComm Technology Division
Gambling Regulatory Authority Singapore
ย 
Prediction 1
AI continue to lead its edge esp. Agentic AI would be getting more popular and used, and AI Governance in terms AI risks and ethnics would get more focused
ย 
Prediction 2
Quantum Computing related products should start to evolve and more apparent.
ย 
Prediction 3
Deployment of robotic applications would be widened esp. in medical, emergency response and casual activities such retail, and food and beverage etc.
Ng Yee Pern,
Chief Technology Officer
Far East Organization
ย 
Prediction 4
AI deployments will start to mature, as enterprises confront the disconnect between the inflated promises of AI vendors and the actual value delivered.
ย 
Prediction 5
Vibe coding will mature and grow in adoption, but enterprise software is not going away. There is plenty of room for both to co-exist.
Athikom Kanchanavibhu
Executive Vice President, Digital & Technology Transformation
& Chief Information Security Officer

Mitr Phol Group
ย 
Prediction 6
The Next Vendor Battleground: Agentic AI Orchestration
By 2026, AI will no longer be a differentiator, it will be a default feature, embedded as standard equipment across modern digital products. As every vendor develops its own Agentic AI, enterprises will manage not one AI, but an orchestra of autonomous agents, each optimized for its own ecosystem.
ย 
The new battleground will be Agentic AI Orchestration where platforms can coordinate, govern, and securely connect agentic AIs across vendors and domains. 2026 wonโ€™t be about smarter agents, but about who can conduct the symphony best-safely, at scale, and across boundaries.
ย 
Prediction 7
Enterprise AI Grows Up: Data Governance Takes Center Stage
2026 will mark the transition from AI pilots to AI in production. While out-of-the-box AI will become common, true competitive advantage will come from applying AI to enterprise-specific data and context. Many organizations will face a sobering realization: AI is only as good as the data it is trusted with.
ย 
As AI moves into core business processes, data governance, management, and security will become non-negotiable foundations. Data quality, access control, privacy, and compliance will determine whether AI scales or stalls. In essence, 2026 will be the year enterprises learn that governing data well is the quiet superpower behind successful AI.
Jackson Ng
Chief Technology Officer and Head of Fintech
Azimut Group
ย 
Prediction 8
In 2026, organizations will see AI seeking power while humans search for purpose. Cognitive supply chains of specialized AI agents will execute work autonomously, forcing individuals to redefine identity at work, in service, and in society. Roles will disintegrate, giving way to a task-based, AI-native economy
Big data technology and data science. Data flow. Querying, analyzing, visualizing complex information. Neural network for artificial intelligence. Data mining. Business analytics.

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2026ๅนดใฎITใƒˆใƒฌใƒณใƒ‰ใ‚’่ชญใ‚€๏ผšๅ›ฝๅ†…ใƒˆใƒƒใƒ—ITใƒชใƒผใƒ€ใƒผใฎๆ่จ€

2026ๅนดใ€ไผๆฅญใฎITๆˆฆ็•ฅใฏใ‹ใคใฆใชใ„ใ‚นใƒ”ใƒผใƒ‰ใง้€ฒๅŒ–ใ—ใฆใ„ใพใ™ใ€‚็”ŸๆˆAIใฎๆ™ฎๅŠใ€ใ‚ตใ‚คใƒใƒผใ‚ปใ‚ญใƒฅใƒชใƒ†ใ‚ฃใฎ้ซ˜ๅบฆๅŒ–ใ€ใƒ‡ใƒผใ‚ฟๆดป็”จใฎๆทฑๅŒ–ใชใฉใ€ๅค‰้ฉใฎๆณขใฏ็ตŒๅ–ถใฎๆ นๅนนใซใพใงๅŠใ‚“ใงใ„ใพใ™ใ€‚ใ“ใ†ใ—ใŸ็’ฐๅขƒไธ‹ใงใ€CIOใ‚’ใฏใ˜ใ‚ใจใ™ใ‚‹ITใƒชใƒผใƒ€ใƒผใซใฏใ€ใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใจใƒ“ใ‚ธใƒใ‚นใ‚’่žๅˆใ•ใ›ใ€ๆŒ็ถš็š„ใช็ซถไบ‰ๅŠ›ใ‚’็”Ÿใฟๅ‡บใ™ๆˆฆ็•ฅใŒๆฑ‚ใ‚ใ‚‰ใ‚Œใฆใ„ใพใ™ใ€‚

CIO.com Japanใงใฏใ€ๅ›ฝๅ†…ใ‚’ไปฃ่กจใ™ใ‚‹CIOใ€CTOใ€CAIOใ‚’ใฏใ˜ใ‚ใจใ™ใ‚‹ITใƒชใƒผใƒ€ใƒผใซใ€Œ2026ๅนดใซๆณจ็›ฎใ™ในใITใƒˆใƒฌใƒณใƒ‰ใ€ใจใใฎ่ƒŒๆ™ฏใซใคใ„ใฆใ‚ณใƒกใƒณใƒˆใ‚’ใ„ใŸใ ใใพใ—ใŸใ€‚

ๆœฌ่จ˜ไบ‹ใงใฏใ€ๅ›ฝๅ†…ใƒˆใƒƒใƒ—ITใƒชใƒผใƒ€ใƒผใŒ่ชžใ‚‹ใ€Œๆฌกใฎไธ€ๆ‰‹ใ€ใ‚’้€šใ˜ใฆใ€2026ๅนดใฎITๆˆฆ็•ฅใฎๆ–นๅ‘ๆ€งใ‚’ๆŽขใ‚Šใพใ™ใ€‚

ๆ ชๅผไผš็คพใƒชใ‚ณใƒผ
ใ‚ณใƒผใƒใƒฌใƒผใƒˆไธŠๅธญๅŸท่กŒๅฝนๅ“กCTO
ใ‚ปใ‚ญใƒฅใƒชใƒ†ใ‚ฃ็ตฑๆ‹ฌๆ‹…ๅฝ“
ๆŠ€่ก“็ตฑๆ‹ฌ้ƒจ ้ƒจโพงใ€ใƒ‡ใ‚ธใ‚ฟใƒซๆˆฆ็•ฅ้ƒจ ้ƒจโพง
้‡Žๆฐด ๆณฐไน‹ ๆฐ

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Richo

AI้ง†ๅ‹•ๅž‹ใƒ—ใƒญใ‚ปใ‚นๆœ€้ฉๅŒ–ใŒไผๆฅญ็ซถไบ‰ๅŠ›ใ‚’ๆฑบใ‚ใ‚‹

2026ๅนดใฏใ‚จใƒผใ‚ธใ‚งใƒณใƒˆๅž‹AIใฎๆœฌๆ ผๅฐŽๅ…ฅใŒ้€ฒใฟใ€ใ€ŒAI้ง†ๅ‹•ๅž‹ใƒ—ใƒญใ‚ปใ‚นๆœ€้ฉๅŒ–ใ€ใจใใฎใŸใ‚ใฎใ€Œใƒ‡ใƒผใ‚ฟๆดป็”จๅŸบ็›คใƒปใƒ‡ใƒผใ‚ฟๆ•ดๅ‚™ๅผทๅŒ–ใ€ใŒๅŠ ้€Ÿใ—ใพใ™ใ€‚

ใƒชใ‚ณใƒผใงใฏERPใฎๅˆทๆ–ฐใ‚’้€ฒใ‚ใฆใ„ใพใ™ใŒใ€ๅˆทๆ–ฐใซไผดใ„ๆฅญๅ‹™ใƒ—ใƒญใ‚ปใ‚นใ‚’AI้ง†ๅ‹•ๅž‹ใซๅ†่จญ่จˆใ—ใชใŒใ‚‰้–‹็™บใƒป้‹็”จใฎ่‡ชๅ‹•ๅŒ–ใ‚’้€ฒใ‚ใพใ™ใ€‚

ๅŒๆ™‚ใซAIๆดป็”จๅผทๅŒ–ใฎใŸใ‚ใซไบˆ้˜ฒๅž‹ใ‚ปใ‚ญใƒฅใƒชใƒ†ใ‚ฃใธใฎ้€ฒๅŒ–ใ€AIใ‚ฌใƒใƒŠใƒณใ‚นใƒปใƒชใ‚นใ‚ฏใƒžใƒใ‚ธใƒกใƒณใƒˆใฎๅผทๅŒ–ใ‚’้€ฒใ‚ใฆใ„ใใพใ™ใ€‚

ๆ ชๅผไผš็คพ่ๅŽŸ่ฃฝไฝœๆ‰€
ๅŸท่กŒๅฝน CIO๏ผˆๆœ€้ซ˜ๆƒ…ๅ ฑ่ฒฌไปป่€…)
ๅฐๅ’Œ็€ฌ ๆตฉไน‹ ๆฐ

ๆ ชๅผไผš็คพ่ๅŽŸ่ฃฝไฝœๆ‰€ ๅŸท่กŒๅฝน CIO๏ผˆๆœ€้ซ˜ๆƒ…ๅ ฑ่ฒฌไปป่€…๏ผ‰ ๅฐๅ’Œ็€ฌ ๆตฉไน‹ ๆฐ

EBREA

AIๆ™‚ไปฃใฎๆœฌ่ณชใฏใ€Œไบบๆๅ†้…็ฝฎใ€ใจใƒ—ใƒญใ‚ปใ‚นๅ†่จญ่จˆ

ๆ˜จไปŠๅ ฑ้“ใ•ใ‚Œใ‚‹AIๅฐŽๅ…ฅไฟƒ้€ฒใซใ‚ˆใ‚‹ๅพ“ๆฅญๅ“กๆ•ฐใฎๆ•ด็†ใŒๅคงใใๅ ฑ้“ใ•ใ‚Œใพใ™ใŒใ€็”Ÿ็”ฃๆ€งๅ‘ไธŠใจใ„ใ†ใ‚ˆใ‚Šใฏใ€ๆ–ฐใŸใชAIๅŽ็›Šๆบใธใฎใ€Œไบบๆใฎๆˆฆ็•ฅ็š„ๅ†้…็ฝฎใ€ใ ใจใฟใฆใ„ใพใ™ใ€‚

ๆˆ‘ใ€…ใฏAIใซใ‚ˆใ‚‹็œŸใฎ็”Ÿ็”ฃๆ€งๅ‘ไธŠใ‚’ๅฎŸ็พใ—ใ€ROIใ‚’้ซ˜ใ‚ใ‚‹ใŸใ‚ใซใฏใ€ๆฉŸ่ƒฝใƒ—ใƒญใ‚ปใ‚นใฎๅพนๅบ•็š„ใชๅ†่จญ่จˆใƒปๅ†็ทจๆˆใŒๅฟ…้ ˆใงใ‚ใ‚Šใ€ใใฎๅŠดๅŠ›ใฏAIๆŠ€่ก“ๅฐŽๅ…ฅใ‚ˆใ‚Šใ‚‚ไธ€ๅฑคใฎๅŠดๅŠ›ใ‚’่ฆใ™ใ‚‹ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ๆ ชๅผไผš็คพๅšๅ ฑๅ ‚DYใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚น
ๅŸท่กŒๅฝนๅ“ก
CAIO
ๆฃฎ ๆญฃๅผฅ ๆฐ

ๆ ชๅผไผš็คพๅšๅ ฑๅ ‚DYใƒ›ใƒผใƒซใƒ‡ใ‚ฃใƒณใ‚ฐใ‚น ๅŸท่กŒๅฝนๅ“ก CAIO ๆฃฎ ๆญฃๅผฅ ๆฐ

Hakuhodo

AIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆๆ™‚ไปฃใฎๅˆฐๆฅ๏ผšๅ‰ต้€ ๆ€งใจๅŠน็އๅŒ–ใฎไธก็ซ‹ใŒ้ต

2026ๅนดใฏใ€AIใŒๅ˜ใชใ‚‹็”Ÿๆˆใƒ„ใƒผใƒซใ‹ใ‚‰่‡ชๅพ‹็š„ใซใ€Œ่€ƒใˆใ€ๅ‹•ใใ€ใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใธใจ้€ฒๅŒ–ใ—ใ€ๅฎŸๅ‹™ใธใฎๆตธ้€ใŒๅฎš็€ใ™ใ‚‹ใƒ•ใ‚งใƒผใ‚บใซๅ…ฅใ‚‹ใจไบˆๆƒณใ•ใ‚Œใพใ™ใ€‚ๅŒๆ™‚ใซใ€AIใธใฎ้Žๅบฆใชไพๅญ˜ใซใ‚ˆใ‚‹ใ‚ขใ‚ฆใƒˆใƒ—ใƒƒใƒˆใฎๅ‡่ณชๅŒ–ใ‚„ใ€ๅพ“ๆฅญๅ“กใฎๅ‰ต้€ ๆ€งใŒๆใชใ‚ใ‚Œใ‚‹ใƒชใ‚นใ‚ฏใ‚‚ๆŒ‡ๆ‘˜ใ•ใ‚Œใฆใ„ใพใ™ใ€‚ๅ˜ใชใ‚‹ๅŠน็އๅŒ–ใซใจใฉใพใ‚‰ใšใ€็พๅ ดใฎๆš—้ป™็Ÿฅใ‚„่‡ช็คพใชใ‚‰ใงใฏใฎๅ‰ต้€ ๆ€งใ‚’AIใจใ„ใ‹ใซ่žๅˆใ•ใ›ใ‚‹ใ‹ใ‚’ๅฟต้ ญใซใ€็ต„็น”ใƒ‡ใ‚ถใ‚คใƒณใ‚„ๆฅญๅ‹™ใƒ—ใƒญใ‚ปใ‚นใ€ใƒ‡ใƒผใ‚ฟใฎAI-ReadyๅŒ–ใ‚’้€ฒใ‚ใ‚‹ใ“ใจใŒ้‡่ฆใช็ตŒๅ–ถ่ชฒ้กŒใจใชใ‚‹ใจ่€ƒใˆใพใ™ใ€‚

IT้ ˜ๅŸŸใซใŠใ„ใฆใฏใ€ใ€ŒVibe Codingใ€ใซไปฃ่กจใ•ใ‚Œใ‚‹AI้ง†ๅ‹•ๅž‹ใฎ้–‹็™บๆ‰‹ๆณ•ใŒๅบƒใŒใ‚Šใ€ใ‚ทใ‚นใƒ†ใƒ ๆง‹็ฏ‰ใฎใ‚ขใƒ—ใƒญใƒผใƒใใฎใ‚‚ใฎใŒๅค‰ๅฎนใ—ใคใคใ‚ใ‚Šใพใ™ใ€‚ใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใซใ‚ˆใ‚‹ใ‚ทใ‚นใƒ†ใƒ ้–“้€ฃๆบใ‚„ใƒ•ใ‚ฃใ‚ธใ‚ซใƒซAIใจใ„ใฃใŸๆ–ฐใŸใชๆŠ€่ก“ๆฝฎๆตใธใฎๅฏพๅฟœใ‚‚่ฆ‹ๆฎใˆใ€ๅค‰ๅŒ–ใซๆŸ”่ปŸใซ้ฉๅฟœใงใใ‚‹ใ‚ขใƒผใ‚ญใƒ†ใ‚ฏใƒใƒฃใธใฎๅˆทๆ–ฐใ‚’่จˆ็”ป็š„ใซ้€ฒใ‚ใฆใ„ใใ“ใจใŒๅคงๅˆ‡ใงใ™ใ€‚

ไผŠ่—คๅฟ ๅ•†ไบ‹ๆ ชๅผไผš็คพ
ๅ‡†ๅŸท่กŒๅฝนๅ“กใ€€ITใƒปใƒ‡ใ‚ธใ‚ฟใƒซๆˆฆ็•ฅ้ƒจ้•ทใ€€
ๆตฆไธŠ ๅ–„ไธ€้ƒŽ ๆฐ

ไผŠ่—คๅฟ ๅ•†ไบ‹ๆ ชๅผไผš็คพ ๅ‡†ๅŸท่กŒๅฝนๅ“กใ€€ITใƒปใƒ‡ใ‚ธใ‚ฟใƒซๆˆฆ็•ฅ้ƒจ้•ทใ€€ ๆตฆไธŠ ๅ–„ไธ€้ƒŽ ๆฐ

Itochu

AIใƒˆใƒฉใƒณใ‚นใƒ•ใ‚ฉใƒผใƒกใƒผใ‚ทใƒงใƒณใŒ็ตŒๅ–ถใฎๆœ€ๅคงใƒ†ใƒผใƒžใซใชใ‚‹ๅนด

2026ๅนดใฎITใƒˆใƒฌใƒณใƒ‰ใฏใ€AIใ‚’ใ€Œ็”Ÿ็”ฃๆ€งๅ‘ไธŠใฎใŸใ‚ใฎ้“ๅ…ทใ€ใจใ—ใฆ่ฆ‹ใ‚‹ๆฎต้šŽใ‹ใ‚‰ใ€ใ€Œไผš็คพใฎ็ซถไบ‰ๅŠ›ใ‚’ๆ”ฏใˆใ‚‹ๅœŸๅฐใ€ใจใ—ใฆๆ‰ใˆ็›ดใ™ๆตใ‚ŒใŒไธ€ๆฐ—ใซ้€ฒใ‚€ๅนดใซใชใ‚‹ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ใ“ใ‚Œใซไผดใ„ใ€IT็ตŒๅ–ถๅŸบ็›คใฎๅฝนๅ‰ฒใ‚‚ๅคงใใๅค‰ใ‚ใ‚Šใพใ™ใ€‚ๅŸบๅนนใ‚ทใ‚นใƒ†ใƒ ใฏๅ˜ใชใ‚‹ๆฅญๅ‹™ๅ‡ฆ็†ใฎไป•็ต„ใฟใ‹ใ‚‰ใ€AIใŒๆดป็”จใ—ใ‚„ใ™ใ„ใƒ‡ใƒผใ‚ฟใ‚’่“„็ฉใ™ใ‚‹ใ€ŒAIใ‚’ๅ‰ๆใจใ—ใŸๅŸบ็›คใ€ใธใจ้€ฒๅŒ–ใ—ใ€ใใ‚Œใ‚‰ใ‚’ๆ”ฏใˆใ‚‹ใ‚ชใƒณใƒ—ใƒฌใƒŸใ‚นใจ่ค‡ๆ•ฐใ‚ฏใƒฉใ‚ฆใƒ‰ใฎไธ€ไฝ“็š„ใช้‹็”จใ€ใ™ใชใ‚ใกใ€Œใƒใ‚คใƒ–ใƒชใƒƒใƒ‰ใ‚ฏใƒฉใ‚ฆใƒ‰็ฎก็†ใ€ใฎ้‡่ฆๆ€งใŒใ“ใ‚ŒใพใงไปฅไธŠใซ้ซ˜ใพใฃใฆใ„ใใงใ—ใ‚‡ใ†ใ€‚

ใ“ใ†ใ—ใŸๅŸบ็›คใฎไธŠใงใƒ“ใ‚ธใƒใ‚นใ‚’็‰ฝๅผ•ใ™ใ‚‹ใฎใŒใ€่‡ชๅพ‹็š„ใซๆฅญๅ‹™ใ‚’้€ฒใ‚ใ‚‹AIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใ‚„ใ€็พๅ ดใงใƒชใ‚ขใƒซใ‚ฟใ‚คใƒ ใซๅˆคๆ–ญใ‚’ไธ‹ใ™ใ‚จใƒƒใ‚ธAIใจใ„ใฃใŸๆŠ€่ก“ใงใ™ใ€‚ใ—ใ‹ใ—ใ€AIใŒๆฅญๅ‹™ใฎไธญๆžขใซๅ…ฅใ‚Š่พผใ‚€ใปใฉใ€ใ€ŒใฉใฎAIใซไฝ•ใ‚’ไปปใ›ใ€็ตๆžœใ‚’ใฉใ†่ชฌๆ˜Žใ™ใ‚‹ใ‹ใ€ใจใ„ใ†AIใ‚ฌใƒใƒŠใƒณใ‚นใ‚„ใ€็”ŸๆˆAIใ‚’ๆ‚ช็”จใ—ใŸๆ”ปๆ’ƒใซๅฏพๆŠ—ใ™ใ‚‹ๅคšๅฑค็š„ใชใ‚ตใ‚คใƒใƒผใ‚ปใ‚ญใƒฅใƒชใƒ†ใ‚ฃๅฏพ็ญ–ใจใ„ใฃใŸใ€Œๅฎˆใ‚Šใ€ใฎไป•็ต„ใฟใ‚‚ๆฌ ใ‹ใ›ใชใใชใ‚Šใพใ™ใ€‚

ๆœ€็ต‚็š„ใซใฏใ€ๅ˜ใซใƒ„ใƒผใƒซใ‚’ๅฐŽๅ…ฅใ™ใ‚‹ใ ใ‘ใงใชใใ€ใƒ“ใ‚ธใƒใ‚นใƒขใƒ‡ใƒซใ‚„ๆ„ๆ€ๆฑบๅฎšใฎใ‚ใ‚Šๆ–นใใฎใ‚‚ใฎใ‚’AIๅ‰ๆใซๅ†ๆง‹็ฏ‰ใ™ใ‚‹ใ€ŒAIใƒˆใƒฉใƒณใ‚นใƒ•ใ‚ฉใƒผใƒกใƒผใ‚ทใƒงใƒณ๏ผˆAIX๏ผ‰ใ€ใ‚’ใ€ๅ…จ็คพใจใ—ใฆใฉใ†ๅฎŸ็พใ—ใฆใ„ใใ‹ใ€‚ใ“ใ‚ŒใŒใ€2026ๅนดใฎ็ตŒๅ–ถใซใŠใ‘ใ‚‹ๆœ€ๅคงใฎใƒ†ใƒผใƒžใซใชใ‚‹ใจ่ฆ‹ใฆใ„ใพใ™ใ€‚

ๆฅฝๅคฉใ‚ฐใƒซใƒผใƒ—ๆ ชๅผไผš็คพ
ๅฐ‚ๅ‹™ๅŸท่กŒๅฝนๅ“ก Group CIO๏ผˆChief Information Officer๏ผ‰& Group CTO๏ผˆChief Technology Officer๏ผ‰
้ป’ไฝ ๆ˜ญไป ๆฐ

ๆฅฝๅคฉใ‚ฐใƒซใƒผใƒ—ๆ ชๅผไผš็คพ ๅฐ‚ๅ‹™ๅŸท่กŒๅฝนๅ“ก Group CIO๏ผˆChief Information Officer๏ผ‰& Group CTO๏ผˆChief Technology Officer๏ผ‰ ้ป’ไฝ ๆ˜ญไป ๆฐ

Rakuten

AIใฎๆฐ‘ไธปๅŒ–ใฎๆ™‚ไปฃ๏ผšไผๆฅญ็ซถไบ‰ๅŠ›ใฏใƒ‡ใƒผใ‚ฟ่ณ‡็”ฃใƒปAIใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใƒปๅ€ซ็†่ฆณใŒ้ตใซ

2026 ๅนดใฏใ€AIใ‚’ไฝฟ็”จใ—ใฆใ„ใ‚‹ใจใ„ใ†่ช่ญ˜ใ™ใ‚‰ใชใใชใฃใฆใ„ใใปใฉใ€AIใŒๆ—ฅๅธธใฎใ€Œๅฝ“ใŸใ‚Šๅ‰ใ€ใซใชใ‚‹ใงใ—ใ‚‡ใ†ใ€‚ใ“ใ‚Œใฏใพใ•ใซใ€ๆฅฝๅคฉใ‚ฐใƒซใƒผใƒ—ใŒ็›ฎๆŒ‡ใ™ใ€ŒAI ใฎๆฐ‘ไธปๅŒ–ใ€ใฎๅงฟใงใ™ใ€‚ใ“ใฎAIๆ™‚ไปฃใฎ็ซถไบ‰ใซใŠใ„ใฆใฏใ€ไผๆฅญใฎๆŒใคใƒ‡ใƒผใ‚ฟ่ณ‡็”ฃใ€AIใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใ€ใใ—ใฆๅ€ซ็†่ฆณ ใฎ๏ผ“ใคใŒๅคงใใชใ‚ญใƒผใƒฏใƒผใƒ‰ใซใชใ‚‹ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

ๆฅฝๅคฉใ‚ฐใƒซใƒผใƒ—ใงใฏใ€่“„็ฉใ•ใ‚ŒใŸๅ„ใƒ‰ใƒกใ‚คใƒณใฎ่†จๅคงใชใƒ‡ใƒผใ‚ฟใ‚’ใ€ๅฝ“็คพ็‹ฌ่‡ชใฎ AI ใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใซใ‚ˆใ‚Š 70 ไปฅไธŠใฎใ‚ตใƒผใƒ“ใ‚นใซ้€ฃๆบใ•ใ›ใ€ใŠๅฎขๆง˜ไธ€ไบบใฒใจใ‚Šใซๆœ€้ฉๅŒ–ใ•ใ‚ŒใŸไฝ“้จ“ใ‚’ๆไพ›ใ—ใฆใ„ใใ“ใจใงใ€ใ€Œๆฅฝๅคฉใ‚จใ‚ณใ‚ทใ‚นใƒ†ใƒ ๏ผˆ็ตŒๆธˆๅœ๏ผ‰ใ€ใฎ้€ฒๅŒ–ใ‚’็›ฎๆŒ‡ใ—ใฆใ„ใพใ™ใ€‚้กงๅฎขไฝ“้จ“ใ‚’ AI ใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใงๅ†ๆง‹็ฏ‰ใ—ใ€ใ‚ˆใ‚Šไพฟๅˆฉใงๅฎ‰ๅ…จใชใ‚ตใƒผใƒ“ใ‚นใ‚’ๆไพ›ใงใใ‚‹ใ‚ˆใ†ใ€ไปŠๅพŒใ‚‚ๅŠชใ‚ใฆใพใ„ใ‚Šใพใ™ใ€‚

How tech and strategy align at Videojet

Legacy manufacturing environments are inherently complex. Deep technical expertise, global operations, and precision processes create a level of interdependence that makes transformation challenging to orchestrate. For CIOs, the task isnโ€™t just about deploying new technologies, but untangling that complexity and evolving from old and deeply embedded ways of working.

When Aroon Sehgal joined Videojet Technologies as CIO last year, he became part of an organization with decades of technical excellence and a proud engineering culture. Videojet, a global leader in coding, marking, and printing solutions for product traceability, had long operated as part of healthcare company Danaher. Now, as a key business within Veralto, a $5 billion global tech leader focused on environmental and product quality solutions, Sehgal saw an opportunity to position technology as a source of differentiation and growth.

โ€œWhen we were part of Danaher, Videojet was a rounding error,โ€ Sehgal says. โ€œNow under Veralto, weโ€™re a meaningful part of the portfolio. That creates both visibility and accountability, and leadership is laser-focused on using technology to drive business outcomes.โ€

Tech moves to the center of strategy

Following Videojetโ€™s most recent strategic planning cycle, one of the companyโ€™s top enterprise-wide initiatives focused on commercial excellence is being led by Sehgal himself. It marks the first time in company history that a technology executive has been chosen to lead one of its most critical strategic programs.

โ€œHistorically, these initiatives were owned by product or operations leaders,โ€ Sehgal says. โ€œThe fact that technology is now seen as a primary driver of growth says everything about how the organizationโ€™s mindset has shifted.โ€

When he arrived, IT was viewed largely as a service provider. His first move was to rebrand the organization, both in name and purpose. IT became digital and technology solutions, or DTS, a deliberate signal that the function would no longer operate in the background. โ€œWe needed to recast technology,โ€ he adds. โ€œThat meant aligning to our three most important outcomes: growth, margin expansion, and productivity.โ€

Embedding tech in the business

To make that shift real, Sehgal restructured how technology partners with the business. His team introduced geography-based business engagement leads, each embedded with regional leadership to ensure direct input into business decisions instead of hearing technology needs second or third hand. He also elevated leaders to run new centers of excellence around Videojetโ€™s most strategic capabilities, including data and AI, e-commerce and web, and ERP transformation.

โ€œItโ€™s about being deliberate,โ€ Sehgal says. โ€œYou canโ€™t extract long-term value from AI or automation without first fixing your data strategy and governance. Weโ€™re laying the foundation for what I call the multi-agentic future, where workflows are increasingly autonomous.โ€

Laying the foundation for AI and automation

That foundation is already producing results. In partnership with Sehgalโ€™s team, Videojet is piloting AI and ML applications across multiple fronts. In operations, theyโ€™re deploying ML to optimize production scheduling, and improve inventory forecasting and planning. The goal is to digitize their sales and operations planning process using a unified data set.

On the commercial side, Videojet has implemented AI-powered translation tools to create marketing content at scale across global markets, and is working with a startup to design an AI-first ERP system that automates order intake. At the same time, tools like Microsoft Copilot and ChatGPT Enterprise are being deployed widely to improve productivity across the organization.

โ€œWeโ€™re not limiting experimentation,โ€ Sehgal says. โ€œTeams across R&D and operations are exploring large language models, and our job is to make sure they have the right data and governance in place to scale.โ€

Speaking the language of business

Still, Sehgal knows that even the most elegant technology story wonโ€™t land unless itโ€™s translated into business terms. โ€œYou canโ€™t walk into a leadership meeting and talk about APIs and architectures,โ€ he said. โ€œYou have to talk about how technology contributes to growth and profitability.โ€

Every initiative under his watch is evaluated through a commercial lens, with clear visibility into how it supports both the customer and the companyโ€™s strategic and financial goals. Sehgal and his team also forecast how their programs will translate to earnings per share, giving leadership a tangible measure of technologyโ€™s targeted contribution to enterprise value. โ€œWhen we model the impact of our initiatives, we express that impact in business terms that everyone in the organization understands,โ€ he says. โ€œThatโ€™s how technology earns its credibility.โ€

Lessons for tech leaders in legacy industries

For Sehgal, Videojetโ€™s vision for technology holds lessons for every CIO navigating a legacy environment. His advice, shaped by leadership roles held at manufacturing giants Terex, ESAB, and ITT Inc., begins with identifying the business pain points where tech can drive the greatest impact. โ€œIn manufacturing, you have to know what holds the business back: labor intensity, asset dependency, supply chain complexity,โ€ he says. โ€œThen, pinpoint where technology can make a difference.โ€

Building credibility early is equally essential. โ€œThe business has to see you as a peer, not a service provider,โ€ he adds. โ€œAnd you canโ€™t have your CFO reading about a breakthrough before you do.โ€

Above all, Sehgal believes technology leaders have to be willing to take risks. โ€œIn manufacturing or any legacy organization, you have to put skin in the game,โ€ he says. โ€œIf you want to drive change, you need to be willing to take on the tough initiatives, own them, and deliver results.โ€ In an industry where efficiency often surpasses innovation, Sehgal is positioning technology to be at the core of a strategy that blends Videojetโ€™s track record of operational rigor with forward-looking ambition, grounded in the language of the business, and aimed squarely at customer growth and innovation. โ€œUltimately, our success will be measured not by how digital we are, but by how much we move the business forward,โ€ he says.

DLAโ€™s foundation to use AI is built on training, platforms

The Defense Logistics Agency is initially focusing its use of artificial intelligence across three main mission areas: operations, demand planning and forecasting, and audit and transparency.

At the same time, DLA isnโ€™t waiting for everyone to be trained or for its data to be perfect.

Adarryl Roberts, the chief information officer at DLA, said by applying AI tools to their use cases, employees can actually clean up the data more quickly.

Adarryl Roberts is the chief information officer at the Defense Logistics Agency. (Photo courtesy of DLA).

โ€œYou donโ€™t have a human trying to analyze the data and come up with those conclusions. So leveraging AI to help with data curation and ensuring we have cleaner data, but then also not just focusing on ChatGPT and things of that nature,โ€ Roberts said on Ask the CIO. โ€œI know thatโ€™s the buzzword, but for an agency like DLA, ChatGPT does not solve our strategic issues that weโ€™re trying to solve, and so thatโ€™s why thereโ€™s a heavier emphasis on AI. For us in those 56 use cases, thereโ€™s a lot of that was natural language processing, a lot around procurement, what I would consider more standardized data, what weโ€™re moving towards with generative AI.โ€

A lot of this work is setting DLA up to use agentic AI in the short-to-medium term. Roberts said by applying agentic AI to its mission areas, DLA expects to achieve the scale, efficiency and effectiveness benefits that the tools promise to provide.

โ€œAt DLA, thatโ€™s when weโ€™re able to have digital employees work just like humans, to make us work at scale so that weโ€™re not having to redo work. Thatโ€™s where you get the loss in efficiency from a logistics perspective, when you have to reorder or re-ship, thatโ€™s more cost to the taxpayer, and that also delays readiness to the warfighter,โ€ Roberts said at the recent DLA Industry Collider day. โ€œFrom a research and development perspective, itโ€™s really looking at the tools we have. We have native tools in the cloud. We have SAP, ServiceNow and others, so based upon our major investments from technology, what are those gaps from a technology perspective that weโ€™re not able to answer from a mission perspective across the supply chain? Then we focus on those very specific use cases to help accelerate AI in that area. The other part of that is architecting it so that it seamlessly plugs back into the ecosystem.โ€

He added that this ensures the technology doesnโ€™t end up becoming a data stovepipe and can integrate into the larger set of applications to be effective and not break missions.

A good example of this approach leading to success is DLAโ€™s use of robotics process automation (RPA) tools. Roberts said the agency currently has about 185 unattended bots that are working 24/7 to help DLA meet mission goals.

โ€œThrough our digital citizen program, government people actually are building bots. As the CIO, I donโ€™t want to be a roadblock as a lot of the technology has advanced to where if you watch a YouTube video, you can pretty much do some rudimentary level coding and things of that nature. You have high school kids building bots today. So I want to put the technology in the hands of the experts, the folks who know the business process the best, so itโ€™s a shorter flash to bang in order to get that support out to the warfighter,โ€ Roberts said.

The success of the bots initiative helped DLA determine that the approach of adopting commercial platforms to implement AI tools was the right one. Roberts said all of these platforms reside under its DLA Connect enterprisewide portal.

โ€œThatโ€™s really looking at the technology, the people, our processes and our data, and how do we integrate that and track that schematically so that we donโ€™t incur the technical debt we incurred about 25 years ago? Thatโ€™s going to result in us having architecture laying out our business processes, our supply chain strategies, how that is integrated within those business processes, overlaying that with our IT and those processes within the IT space,โ€ he said. โ€œThe business processes, supply chain, strategies and all of that are overlapping. You can see that integration and that interoperability moving forward. So we are creating a single portal where, if youโ€™re a customer, an industry partner, an actual partner or internal DLA, for you to communicate and also see whatโ€™s happening across DLA.โ€

Training every employee on AI

He said that includes questions about contracts and upcoming requests for proposals as well as order status updates and other data driven questions.

Of course, no matter how good the tools are, if the workforce isnโ€™t trained on how to use the AI capabilities or knows where to find the data, then the benefits will be limited.

Roberts said DLA has been investing in training from online and in person courses to creating a specific โ€œinnovation navigators courseโ€ that is focused on both the IT and how to help the businesses across the agency look at innovation as a concept.

โ€œEveryone doesnโ€™t need the same level of training for data acumen and AI analytics, depending on where you sit in the organization. So working with our human resources office, we are working with the other executives in the mission areas to understand what skill sets they need to support their day-to-day mission. What are their strategic objectives? Whatโ€™s that population of the workforce and how do we train them, not just online, but in person?โ€ Roberts said. โ€œWeโ€™re not trying to reinvent how you learn AI and data, but how do we do that and incorporate whatโ€™s important to DLA moving forward? We have a really robust plan for continuous education, not just take a course, and youโ€™re trained, which, I think, is where the government has failed in the past. We train people as soon as they come on board, and then you donโ€™t get additional training for the next 10-15 years, and then the technology passes you by. So weโ€™re going to stay up with technology, and itโ€™s going to be continuous education moving forward, and that will evolve as our technology evolves.โ€

Roberts said the training is for everyone, from the director of DLA to senior leaders in the mission areas to the logistics and supply chain experts. The goal is to help them answer and understand how to use the digital products, how to prompt AI tools the best way and how to deploy AI to impact their missions.

โ€œYou donโ€™t want to deploy AI for the sake of deploying AI, but we need to educate the workforce in terms of how it will assist them in their day to day jobs, and then strategically, from a leadership perspective, how are we structuring that so that we can achieve our objectives,โ€ he said. โ€œAcross DLA, weโ€™ve trained over 25,000 employees. All our employees have been exposed, at least, to an introductory level of data acumen. Then we have some targeted courses that weโ€™re having for senior leaders to actually understand how you manage and lead when you have a digital-first concept. Weโ€™re actually going to walk through some use cases, see those to completion for some of the priorities that we have strategically, that way we can better lead the workforce and their understanding of how to employ it at echelon within our organization, enhancing IT governance and operational success.โ€

The courses and training has helped DLA โ€œlay the foundation in terms of what we need to be a digital organization, to think digital first. Now weโ€™re at the point of execution and implementation, putting those tools to use,โ€ Roberts said.

The post DLAโ€™s foundation to use AI is built on training, platforms first appeared on Federal News Network.

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2026ๅนดใฎITใƒˆใƒฌใƒณใƒ‰ใ‚’่ชญใ‚€๏ผšๅ›ฝๅ†…ใƒˆใƒƒใƒ—ITใƒชใƒผใƒ€ใƒผใฎๆ่จ€

2026ๅนดใ€ไผๆฅญใฎITๆˆฆ็•ฅใฏใ‹ใคใฆใชใ„ใ‚นใƒ”ใƒผใƒ‰ใง้€ฒๅŒ–ใ—ใฆใ„ใพใ™ใ€‚็”ŸๆˆAIใฎๆ™ฎๅŠใ€ใ‚ตใ‚คใƒใƒผใ‚ปใ‚ญใƒฅใƒชใƒ†ใ‚ฃใฎ้ซ˜ๅบฆๅŒ–ใ€ใƒ‡ใƒผใ‚ฟๆดป็”จใฎๆทฑๅŒ–ใชใฉใ€ๅค‰้ฉใฎๆณขใฏ็ตŒๅ–ถใฎๆ นๅนนใซใพใงๅŠใ‚“ใงใ„ใพใ™ใ€‚ใ“ใ†ใ—ใŸ็’ฐๅขƒไธ‹ใงใ€CIOใ‚’ใฏใ˜ใ‚ใจใ™ใ‚‹ITใƒชใƒผใƒ€ใƒผใซใฏใ€ใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใจใƒ“ใ‚ธใƒใ‚นใ‚’่žๅˆใ•ใ›ใ€ๆŒ็ถš็š„ใช็ซถไบ‰ๅŠ›ใ‚’็”Ÿใฟๅ‡บใ™ๆˆฆ็•ฅใŒๆฑ‚ใ‚ใ‚‰ใ‚Œใฆใ„ใพใ™ใ€‚

CIO.com Japanใงใฏใ€ๅ›ฝๅ†…ใ‚’ไปฃ่กจใ™ใ‚‹CIOใ€CTOใ€CAIOใ‚’ใฏใ˜ใ‚ใจใ™ใ‚‹ITใƒชใƒผใƒ€ใƒผใซใ€Œ2026ๅนดใซๆณจ็›ฎใ™ในใITใƒˆใƒฌใƒณใƒ‰ใ€ใจใใฎ่ƒŒๆ™ฏใซใคใ„ใฆใ‚ณใƒกใƒณใƒˆใ‚’ใ„ใŸใ ใใพใ—ใŸใ€‚

ๆœฌ่จ˜ไบ‹ใงใฏใ€ๅ›ฝๅ†…ใƒˆใƒƒใƒ—ITใƒชใƒผใƒ€ใƒผใŒ่ชžใ‚‹ใ€Œๆฌกใฎไธ€ๆ‰‹ใ€ใ‚’้€šใ˜ใฆใ€2026ๅนดใฎITๆˆฆ็•ฅใฎๆ–นๅ‘ๆ€งใ‚’ๆŽขใ‚Šใพใ™ใ€‚

ใ‚ผใƒใƒฉใƒซใƒขใƒผใ‚ฟใƒผใ‚บใƒปใ‚ธใƒฃใƒ‘ใƒณๆ ชๅผไผš็คพ

General Mortors (GM)_CIO_Mr. Buniu

General Motors

ใ‚ผใƒใƒฉใƒซใƒขใƒผใ‚ฟใƒผใ‚บใƒปใ‚ธใƒฃใƒ‘ใƒณๆ ชๅผไผš็คพ
ใ‚นใƒˆใƒฉใƒ†ใ‚ธใƒƒใ‚ฏใƒžใƒผใ‚ฑใƒƒใƒˆ ใ‚ขใƒฉใ‚คใ‚ขใƒณใ‚น๏ผ†ใƒ‡ใ‚ฃใ‚นใƒˆใƒชใƒ“ใƒฅใƒผใ‚ฟใƒผใ€€ใƒชใƒผใ‚ธใƒงใƒณCIO
่ฑŠไธน็”Ÿ ไฟก้š† ๆฐ

AIๅ‰ๆๆ™‚ไปฃใฎITๆˆฆ็•ฅ๏ผšใ‚ฌใƒใƒŠใƒณใ‚นใจๆŸ”่ปŸๆ€งใŒ้ต

AIใฎๆดป็”จใ‚’ๅ‰ๆใจใ—ใŸใƒ“ใ‚ธใƒใ‚นใƒขใƒ‡ใƒซใŒไธ€่ˆฌๅŒ–ใ™ใ‚‹ไธญใ€็›ฎ็š„ใซๅฟœใ˜ใŸAIใฎไฝฟใ„ๅˆ†ใ‘ใŒ้€ฒใฟใใ†ใงใ™ใ€‚ใใฎไธŠใงใƒ“ใ‚ธใƒใ‚นใธใฎAI้ฉ็”จใซใฏ้€ๆ˜Žๆ€งใ‚„ๅ€ซ็†ๆ€งใ‚’ๅฎˆใ‚‹ใŸใ‚ใฎใ‚ฌใƒใƒŠใƒณใ‚นใฎๅผทๅŒ–ใŒไธ€ใคใฎใƒ†ใƒผใƒžใงใ™ใ€‚ๅ€‹ไบบใฎ็”Ÿ็”ฃๆ€งใ‚„ๅ‰ต้€ ๆ€งๅ‘ไธŠใซๅฏ„ไธŽใ™ใ‚‹ใŸใ‚ใฎAI้ฉ็”จใฏใชใ‚‹ในใ่‡ช็”ฑใซใใฎๅˆฉ็”จใŒใงใใ‚‹็’ฐๅขƒใ‚’ๆ•ดๅ‚™ใ—ใฆใ„ใไธ€ๆ–นใ€ๅ…ฌ็งใฎใƒใƒฉใƒณใ‚นใ‚’ใจใ‚‹ใŸใ‚ใซๅ…ทไฝ“็š„ใชๅˆถๅบฆๅŒ–ใจๆ•™่‚ฒใŒ้‡่ฆใช่ชฒ้กŒใจ่€ƒใˆใพใ™ใ€‚

ไธ€ๆ–นใ€ITใซใŠใ„ใฆใฏAIๆดป็”จใ‚’ๅ‰ๆใจใ—ใŸใƒ—ใƒฉใƒƒใƒˆใƒ•ใ‚ฉใƒผใƒ ใ‹ใ‚‰ใ‚ขใƒ—ใƒชใ‚ฑใƒผใ‚ทใƒงใƒณใพใงๅ„ๅฑคใฎๅฎš็พฉใ€่ฆ‹็›ดใ—ใŒๆ€ฅๅ‹™ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚ไปŠๅพŒๅ„ใ‚ตใƒผใƒ“ใ‚นใฎไป•ๆง˜ใ‚„ๆง‹ๆˆ่ฆ็ด ใŒๅค‰ใ‚ใฃใฆใ„ใใจใ„ใ†่ช่ญ˜ใฎใ‚‚ใจใ€ๆŸ”่ปŸๆ€งใ‚’ๆฎ‹ใ—ใŸๅฝขใงใใ‚Œใžใ‚Œใฎใ‚ตใƒผใƒ“ใ‚นๅˆทๆ–ฐใ‚’่จˆ็”ป็š„ใซ่กŒใฃใฆใ„ใไบˆๅฎšใงใ™ใ€‚

ๅ–็ท ๅฝนๅ…ผๅธธๅ‹™ๅŸท่กŒๅฝนๅ“กใ€ICTๆŽจ้€ฒๆœฌ้ƒจ้•ท ๆฉ‹็ˆช ๅฎ—ไฟก ๆฐ

Kanadevia

ใ‚ซใƒŠใƒ‡ใƒ“ใ‚ขๆ ชๅผไผš็คพ
ๅ–็ท ๅฝนๅ…ผๅธธๅ‹™ๅŸท่กŒๅฝนๅ“กใ€ICTๆŽจ้€ฒๆœฌ้ƒจ้•ท
ๆฉ‹็ˆช ๅฎ—ไฟก ๆฐ

่ฃฝ้€ ๆฅญใ‚‚ใƒ›ใƒฏใ‚คใƒˆใ‚ซใƒฉใƒผใ‚‚ๅค‰ใˆใ‚‹ใ€AIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆ้ฉๅ‘ฝ

2026ๅนดใฎๆœ€ใ‚‚้‡่ฆใชใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใฏAIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใฎใ€Œไฝฟใ„ใ“ใชใ—ๆŠ€่ก“ใ€ใจ่€ƒใˆใฆใ„ใพใ™ใ€‚็”ŸๆˆAIใฎ่ถ…้€ฒๅŒ–ใฏ่จ€ใ†ใพใงใ‚‚็„กใใ€ๅผŠ็คพใฎใ‚ˆใ†ใช่ฃฝ้€ ๆฅญใงใ‚‚ๆฅตใ‚ใฆ้‡่ฆใซใชใฃใฆใใฆใ„ใพใ™ใ€‚ๅ€‹ใ€…ใฎๅ ด้ขใง็”ŸๆˆAIใ‚’็”จใ„ใŸใƒ‡ใ‚ธใ‚ฟใƒซๅฟœ็”จใฎๅ“่ณชใ€ๅฎ‰ๅ…จใ€็”Ÿ็”ฃๆ€งๅ‘ไธŠใฎๅ€‹ๅˆฅใ‚ทใ‚นใƒ†ใƒ ใŒ็”ฃใพใ‚Œใฆใใพใ™ใŒใ€็ทๅ‹™ใ€ไบบไบ‹ใ€็ตŒ็†ใชใฉใฎใƒ›ใƒฏใ‚คใƒˆใ‚ซใƒฉใƒผใฎ่ทๅ“กใ‚‚ๅซใ‚ใŸๅƒใๆ–นใ€ไป•ไบ‹ใฎ็”Ÿ็”ฃๆ€งใ‚’ๆŠœๆœฌ็š„ใซๅค‰้ฉใ™ใ‚‹AIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใ‚’ๅ…จ็คพใงไฝฟใ„ใ“ใชใ›ใ‚‹็คพๅ†…ๆดป็”จใƒ—ใƒฉใƒƒใƒˆใƒ•ใ‚ฉใƒผใƒ ใฎๆง‹็ฏ‰ใŒๆœ€้‡่ฆ่ชฒ้กŒใงใ€ๅ„็คพใŒใใ‚Œใ‚‰ใฎใƒ—ใƒฉใƒƒใƒˆใƒ•ใ‚ฉใƒผใƒ ใซ้ฉใ—ใŸITใ‚ฝใƒชใƒฅใƒผใ‚ทใƒงใƒณใ‚’ๆŽขใใ†ใจๅ‹•ใใจไบˆๆƒณใ—ใฆใ„ใพใ™ใ€‚ๅฝ“็„ถๅผŠ็คพใ‚‚ใใฎๆ–นๅ‘ใงใ™ใ€‚

้–ข่ฅฟ้›ปๅŠ›ๆ ชๅผไผš็คพ  ็†ไบ‹ใ€ITๆˆฆ็•ฅๅฎค้•ท ไธŠ็”ฐ ๆ™ƒ็ฉ‚ ๆฐ

Kansai Electric Power

้–ข่ฅฟ้›ปๅŠ›ๆ ชๅผไผš็คพ
็†ไบ‹ใ€ITๆˆฆ็•ฅๅฎค้•ท
ไธŠ็”ฐ ๆ™ƒ็ฉ‚ ๆฐ

2026ๅนดใฏใ€ŒAIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใ€ใ‹ใ‚‰ใ€ŒAIใƒ‘ใƒผใƒˆใƒŠใƒผใ€ใธ้€ฒๅŒ–ใฎๅนด

2025ๅนดใฏใ€ŒAIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใ€ๅ…ƒๅนดใงใ—ใŸใŒใ€2026ๅนดใฏใ€Œใƒ’ใƒˆใจAIใจใฎๅ”ๅƒใจใฏไฝ•ใ‹๏ผŸใ€ใ€ใคใพใ‚ŠAIใซไฝ•ใ‚’ไปปใ›ใ€ใƒ’ใƒˆใฏไฝ•ใซ็‰นๅŒ–ใ™ใ‚‹ใฎใ‹ใ‚’ๅพนๅบ•็š„ใซ่€ƒใˆใ€ใ€ŒAIใƒ‘ใƒผใƒˆใƒŠใƒผใ€ๅŒ–ใ‚’้€ฒใ‚ใ‚‹ๅนดใซใชใ‚Šใพใ™ใ€‚ๆฅญ็•Œใƒปๆฅญๅ‹™ใ€ๅ„็คพใฎDXใฎ้€ฒๅฑ•ๅบฆใซใ‚ˆใฃใฆใ€Œใƒ’ใƒˆใจAIใจใฎๅ”ๅƒใ€ใฎไป•ๆ–นใฏๆง˜ใ€…ใงใ™ใ€‚่‡ช็คพใซๆœ€้ฉใชใ€Œใƒ’ใƒˆใจAIใจใฎๅ”ๅƒใ€ใ‚’่ฆ‹ใคใ‘ๅฎŸ่กŒใ™ใ‚‹ใƒ’ใƒˆใƒปไผš็คพใŒ็ซถไบ‰ๅ„ชไฝใ‚’็ขบ็ซ‹ใ—็”Ÿใๆฎ‹ใ‚‹ใ‚‚ใฎใจ่€ƒใˆใฆใ„ใพใ™ใ€‚

J. ใƒ•ใƒญใƒณใƒˆ ใƒชใƒ†ใ‚คใƒชใƒณใ‚ฐๆ ชๅผไผš็คพ ๅŸท่กŒๅฝนใ€€DXๆŽจ้€ฒ้ƒจ้•ท ้‡Žๆ‘ ๆณฐไธ€ ๆฐ

J. Front Retailing

J. ใƒ•ใƒญใƒณใƒˆ ใƒชใƒ†ใ‚คใƒชใƒณใ‚ฐๆ ชๅผไผš็คพ
ๅŸท่กŒๅฝนใ€€DXๆŽจ้€ฒ้ƒจ้•ท
้‡Žๆ‘ ๆณฐไธ€ ๆฐ

AIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆๆ™‚ไปฃใฎๅ‹ๆ•—ใฏใ€Œใƒ‡ใƒผใ‚ฟๆ•ดๅ‚™ๅŠ›ใ€ใงๆฑบใพใ‚‹

ใƒ“ใ‚ธใƒใ‚นใ‚ทใƒผใƒณใซใŠใ‘ใ‚‹AIใฎๆดป็”จใŒไธ€ๅฑคๅŠ ้€Ÿใ™ใ‚‹ใ“ใจใซใชใ‚Šใใ†ใงใ™ใ€‚ๅ€‹ไบบๅˆฉ็”จใ ใ‘ใงใชใใ€ๆฅญๅ‹™่ชฒ้กŒใ‚„ๆˆฆ็•ฅๅฎŸ็พใจใ„ใฃใŸ็ต„็น”ใƒ†ใƒผใƒžใซๅฏพใ—ใฆใ‚‚ไบ‹ไพ‹ใŒๅคšใ็™ปๅ ดใ™ใ‚‹ใ“ใจใซใชใ‚Šใพใ™ใ€‚ไธญใงใ‚‚AIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใฏๆณจ็›ฎใ•ใ‚Œใ‚‹ใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใจๆ€ใ„ใพใ™ใŒใ€ใใฎๅˆฉ็”จใซใ‚ใŸใฃใฆใฏ็คพๅ†…ใƒ‡ใƒผใ‚ฟใฎ็’ฐๅขƒใ‚’ใ„ใ‹ใซๆ•ดใˆใฆใใŸใฎใ‹ใจใ„ใ†ไผๆฅญใจใ—ใฆใฎๆบ–ๅ‚™ใฎๅทฎใŒ่กจๅ‡บใ™ใ‚‹ใ“ใจใซใชใ‚‹ใฎใงใฏใจๆ€ใ„ใพใ™ใ€‚

ใƒ“ใ‚ธใƒใ‚นใ‚ทใƒผใƒณใซใŠใ‘ใ‚‹AIใฎๆดป็”จใŒไธ€ๅฑคๅŠ ้€Ÿใ™ใ‚‹ใ“ใจใซใชใ‚Šใใ†ใงใ™ใ€‚ๅ€‹ไบบๅˆฉ็”จใ ใ‘ใงใชใใ€ๆฅญๅ‹™่ชฒ้กŒใ‚„ๆˆฆ็•ฅๅฎŸ็พใจใ„ใฃใŸ็ต„็น”ใƒ†ใƒผใƒžใซๅฏพใ—ใฆใ‚‚ไบ‹ไพ‹ใŒๅคšใ็™ปๅ ดใ™ใ‚‹ใ“ใจใซใชใ‚Šใพใ™ใ€‚ไธญใงใ‚‚AIใ‚จใƒผใ‚ธใ‚งใƒณใƒˆใฏๆณจ็›ฎใ•ใ‚Œใ‚‹ใƒ†ใ‚ฏใƒŽใƒญใ‚ธใƒผใจๆ€ใ„ใพใ™ใŒใ€ใใฎๅˆฉ็”จใซใ‚ใŸใฃใฆใฏ็คพๅ†…ใƒ‡ใƒผใ‚ฟใฎ็’ฐๅขƒใ‚’ใ„ใ‹ใซๆ•ดใˆใฆใใŸใฎใ‹ใจใ„ใ†ไผๆฅญใจใ—ใฆใฎๆบ–ๅ‚™ใฎๅทฎใŒ่กจๅ‡บใ™ใ‚‹ใ“ใจใซใชใ‚‹ใฎใงใฏใจๆ€ใ„ใพใ™ใ€‚  ใ‚ขใ‚คใƒชใ‚นใ‚ชใƒผใƒคใƒžๆ ชๅผไผš็คพ ๅŸท่กŒๅฝนๅ“ก ใƒญใƒœใƒ†ใ‚ฃใ‚ฏใ‚นไบ‹ๆฅญ้ƒจ ไบ‹ๆฅญ้ƒจ้•ทใ€€ ๆ ชๅผไผš็คพใ‚ขใ‚คใƒชใ‚นใƒญใƒœใƒ†ใ‚ฃใ‚ฏใ‚น ๅ–็ท ๅฝน็คพ้•ท ๅ‰็”ฐ ่ฑŠ ๆฐ

IRIS

ใ‚ขใ‚คใƒชใ‚นใ‚ชใƒผใƒคใƒžๆ ชๅผไผš็คพ
ๅŸท่กŒๅฝนๅ“ก ใƒญใƒœใƒ†ใ‚ฃใ‚ฏใ‚นไบ‹ๆฅญ้ƒจ ไบ‹ๆฅญ้ƒจ้•ท
ๆ ชๅผไผš็คพใ‚ขใ‚คใƒชใ‚นใƒญใƒœใƒ†ใ‚ฃใ‚ฏใ‚น ๅ–็ท ๅฝน็คพ้•ท
ๅ‰็”ฐ ่ฑŠ ๆฐ

ใƒ•ใ‚ฃใ‚ธใ‚ซใƒซAIๆ™‚ไปฃใฎๅน•้–‹ใ‘๏ผšใƒญใƒœใƒƒใƒˆใŒ็พๅ ดใ‚’ๅค‰ใˆใ‚‹

2026ๅนดใฏAIใจใƒญใƒœใƒ†ใ‚ฃใ‚ฏใ‚นใŒไผๆฅญ็ซถไบ‰ๅŠ›ใ‚’ๆฑบๅฎšใฅใ‘ใ‚‹ๅนดใงใ™ใ€‚ไบบๅฃๆธ›ๅฐ‘ใจๅŠดๅƒๅŠ›ไธ่ถณใ‚’่ƒŒๆ™ฏใซใ€ๆ”ฟๅบœใฏ็พๅ ดDXใจใƒญใƒœใƒƒใƒˆๅฐŽๅ…ฅใ‚’ๅพŒๆŠผใ—ใ—ใ€ๅ›ฝๅฎถๆˆฆ็•ฅๆŠ€่ก“ใจใ—ใฆAIใƒปๅ…ˆ็ซฏใƒญใƒœใƒƒใƒˆใ‚’้‡็‚นๆ”ฏๆดใ—ใพใ™ใ€‚่ฃฝ้€ ใƒป็‰ฉๆตใƒปๅŒป็™‚ใชใฉๅคšๆง˜ใช็พๅ ดใงใƒญใƒœใƒƒใƒˆใฏ็œไบบๅŒ–ใ‹ใ‚‰็”Ÿ็”ฃๆ€งๅ‘ไธŠใฎใƒ‘ใƒผใƒˆใƒŠใƒผใธ้€ฒๅŒ–ใ€ๅฝ“็คพใ‚‚AIๆญ่ผ‰ใƒญใƒœใƒƒใƒˆใงใƒ•ใ‚ฃใ‚ธใ‚ซใƒซAIใฎ็คพไผšๅฎŸ่ฃ…ใ‚’ๅŠ ้€Ÿใ—ใพใ™ใ€‚

7 changes to the CIO role in 2026

Everything is changing, from data pipelines and technology platforms, to vendor selection and employee training โ€” even core business processes โ€” and CIOs are in the middle of it to guide their companies into the future.

In 2024, tech leaders asked themselves if this AI thing even works and how do you do it. Last year, the big question was what the best use cases are for the new technology. This year will be all about scaling up and starting to use AI to fundamentally transform how employees, business units, or even entire companies actually function.

So whatever IT was thought of before, itโ€™s now a driver of restructuring. Here are seven ways the CIO role will change in the next 12 months.

Enough experimenting

The role of the CIO will change for the better in 2026, says Eric Johnson, CIO at incident management company PagerDuty, with a lot of business benefit and opportunity in AI.

โ€œItโ€™s like having a mine of very valuable minerals and gold, and youโ€™re not quite sure how to extract it and get full value out of it,โ€ he says. Now, he and his peers are being asked to do just that: move out of experimentation and into extraction.

โ€œWeโ€™re being asked to take everything weโ€™ve learned over the past couple of years and find meaningful value with AI,โ€ he says.

What makes this extra challenging is the pace of change is so much faster now than before.

โ€œWhat generative AI was 12 months ago is completely different to what it is today,โ€ he says. โ€œAnd the business folks watching that transformation occur are starting to hear of use cases they never heard of months ago.โ€

From IT manager to business strategist

The traditional role of a companyโ€™s IT department has been to provide technology support to other business units.

โ€œYou tell me what the requirements are, and Iโ€™ll build you your thing,โ€ says Marcus Murph, partner and head of technology consulting at KPMG US.

But the role is changing from back-office order taker to full business partner working alongside business leaders to leverage innovation.

โ€œMy instincts tell me that for at least the next decade, weโ€™ll see such drastic change in technology that they wonโ€™t go back to the back office,โ€ he says. โ€œWeโ€™re probably in the most rapid hyper cycle of change at least since the internet or mobile phones, but almost certainly more than that.โ€

Change management

As AI transforms how people do their jobs, CIOs will be expected to step up and help lead the effort.

โ€œA lot of the conversations are about implementing AI solutions, how to make solutions work, and how they add value,โ€ says Ryan Downing, VP and CIO of enterprise business solutions at Principal Financial Group. โ€œBut the reality is with the transformation AI is bringing into the workplace right now, thereโ€™s a fundamental change in how everyone will be working.โ€

This transformation will challenge everyone, he says, in terms of roles, value proposition of whatโ€™s been done for years, and expertise.

โ€œThe technology weโ€™re starting to bring into the workplace is really shaping the future of work, and we need to be agents of change beyond the tech,โ€ he says.

That change management starts within the IT organization itself, adds Matt Kropp, MD and senior partner and CTO at Boston Consulting Group.

โ€œThereโ€™s quite a lot of focus on AI for software development because itโ€™s maybe the most advanced, and the tools have been around for a while,โ€ he says. โ€œThereโ€™s a very clear impact using AI agents for software developers.โ€

The lessons that CIOs learn from managing this transformation can be applied in other business units, too, he says.

โ€œWhat we see happening with AI for software development is a canary in the coal mine,โ€ he adds. And itโ€™s an opportunity to ensure the company is getting the productivity gains itโ€™s looking for, but also to create change management systems that can be used in other parts of the enterprise. And it starts with the CIO.

โ€œYou want the top of the organization saying they expect everyone to use AI because they use it, and can demonstrate how they use it as part of their work,โ€ he says. Leaders need to lead by example that the use of AI is allowed, accepted, and expected.

CIOs and other executives can use AI to create first drafts of memos, organize meeting notes, and help them think through strategy. And any major technology initiative will include a change management component, yet few technologies have had as dramatic an impact on work as AI is having, and is expected to have.

Deploying AI at scale in an enterprise, however, is a very contentious issue, says Ari Lightman, a professor at Carnegie Mellon University. Companies have spent a lot of time focusing on understanding the customer experience, he says, but few focus on the employee experience.

โ€œWhen you roll out enterprise-wide AI systems, youโ€™re going to have people who are supportive and interested, and people who just want to blow it up,โ€ he says. Without addressing the issues that employees have, AI projects can grind to a halt.

Cleaning up the data

As AI projects scale up, so will their data requirements. Instead of limited, curated data sets, enterprises will need to modernize their data stacks if they havenโ€™t already, and make the data ready and accessible for AI systems while ensuring security and compliance.

โ€œWeโ€™re thinking about data foundations and making sure we have the infrastructure in place so AI is something we can leverage and get value out of,โ€ says Aaron Rucker, VP of data at Warner Music.

The security aspect is particularly important as AI agents gain the ability to autonomously seek out and query data sources. This was much less of a concern with small pilot projects or RAG embedding, where developers carefully curated the data that was used to augment AI prompts. And before gen AI, data scientists, analysts, and data engineers were the ones accessing data, which offered a layer of human control that might diminish or completely vanish in the agentic age. That means the controls will need to move closer to the data itself.

โ€œWith AI, sometimes you want to move fast, but you still want to make sure youโ€™re setting up data sources with proper permissions so someone canโ€™t just type in a chatbot and get all the family jewels,โ€ says Rucker.

Make build vs buy decisions

This year, the build or buy decisions for AI will have dramatically bigger impacts than they did before. In many cases, vendors can build AI systems better, quicker, and cheaper than a company can do it themselves. And if a better option comes along, switching is a lot easier than when youโ€™ve built something internally from scratch. On the other hand, some business processes represent core business value and competitive advantage, says Rucker.

โ€œHR isnโ€™t a competitive advantage for us because Workday is going to be better positioned to build something thatโ€™s compliantโ€ he says. โ€œIt wouldnโ€™t make sense for us to build that.โ€

But then there are areas where Warner Music can gain a strategic advantage, he says, and itโ€™s going to be important to figure out what this advantage is going to be when it comes to AI.

โ€œWe shouldnโ€™t be doing AI for AIโ€™s sake,โ€ says Rucker. โ€œWe should attach it to some business value as a reflection of our company strategy.โ€

If a company uses outside vendors for important business processes, thereโ€™s a risk the vendor will come to understand an industry better than the existing players.

Digitizing a business process creates behavioral capital, network capital, and cognitive capital, says John Sviokla, executive fellow at the Harvard Business School and co-founder of GAI Insights. It unlocks something that used to be exclusively inside the minds of employees.

Companies have already traded their behavioral capital to Google and Facebook, and network capital to Facebook and LinkedIn.

โ€œTrading your cognitive capital for cheap inference or cheap access to technology is a very bad idea,โ€ says Sviokla. Even if the AI company or hyperscaler isnโ€™t currently in a particular line of business, this gives them the starter kit to understand that business. โ€œOnce they see a massive opportunity, they can put billions of dollars behind it,โ€ he says.

Platform selection

As AI moves from one-off POCs and pilot projects to deployments at scale, companies will have to come to grips with choosing an AI platform, or platforms.

โ€œWith things changing so fast, we still donโ€™t know whoโ€™s going to be the leaders in the long term,โ€ says Principalโ€™s Downing. โ€œWeโ€™re going to start making some meaningful bets, but I donโ€™t think the industry is at the point where we pick one and say thatโ€™s going to be it.โ€

The key is to pick platforms that have the ability to scale, but are decoupled, he says, so enterprises can pivot quickly, but still get business value. โ€œRight now, Iโ€™m prioritizing flexibility,โ€ he says.

Bret Greenstein, chief AI officer at management consulting firm West Monroe Partners, recommends CIOs identify aspects of AI that are stable, and those that change rapidly, and make their platform selections accordingly.

โ€œKeep your AI close to the cloud because the cloud is going to be stable,โ€ he says. โ€œBut the AI agent frameworks will change in six months, so build to be agnostic in order to integrate with any agent frameworks.โ€

Progressive CIOs are building the enterprise infrastructure of tomorrow and have to be thoughtful and deliberate, he adds, especially around building governance models.

Revenue generation

AI is poised to massively transform business models across every industry. This is a threat to many companies, but also an opportunity for others. By helping to create new AI-powered products and services, CIOs can make IT a revenue generator instead of just a cost center.

โ€œYouโ€™re going to see this notion of most IT organizations directly building tech products that enable value in the marketplace, and change how you do manufacturing, provide services, and how you sell a product in a store,โ€ says KPMGโ€™s Murph.

That puts IT much closer to the customer than it had been before, raising its profile and significance in the organization, he says.

โ€œIn the past, IT was one level away from the customer,โ€ he says. โ€œThey enabled the technology to help business functions sell products and services. Now with AI, CIOs and IT build the products, because everything is enabled by technology. They go from the notion of being services-oriented to product-oriented.โ€

One CIO already doing this is Amith Nair at Vituity, a national physician group serving 13.8 million patients.

โ€œWeโ€™re building products internally and providing them back to the hospital system, and to external customers,โ€ he says.

For example, doctors spend hours a day transcribing conversations with patients, which is something AI can help with. โ€œWhen a patient comes in, they can just have a conversation,โ€ he says. โ€œInstead of looking at the computer and typing, they look at and listen to the patient. Then all of their charting, medical decision processes, and discharge summaries are developed using a multi-agent AI platform.โ€

The tool was developed in-house, custom-built on top of the Microsoft Azure platform, and is now a startup running on its own, he says.

โ€œWeโ€™ve become a revenue generator,โ€ he says.

How Black & Veatch is democratizing AI expertise across its employee owners

Black & Veatchโ€™s AI strategy demonstrates how thoughtful implementation can drive rapid, meaningful adoption across a large organization. Rather than deploying AI tools companywide and hoping for results, itโ€™s built a cohort-based program thatโ€™s driven active and specific AI work usage to nearly half of its employee owners in just one year. The approach addresses the human factors that often derail AI initiatives by building champion networks, eliminating friction, and converting employee passion into tangible workplace and business benefits. By also combining partner-provided AI capabilities with proprietary tools trained on 110 years of engineering data, Black & Veatch is creating a multiplier effect that enables safety improvement, profitability, and increased resource capacity.

How is AI making its way into your business strategy?

We anchor our AI opportunities to three areas: safety, resourcing improvements, and profitable returns for our employee owners. With market demand increasing, particularly the power needs of data centers, weโ€™re using AI to democratize knowledge across our engineers so Black & Veatch can deliver more strategic and accelerated solutions.

How are you embedding this strategy?

Weโ€™ve defined our AI capabilities continuum as foundational, differentiating, and enduring with a focus on four themes across gen AI, agentic AI, and MLOps.

The first theme is iterative innovation, which lowers the barriers to effective use of AI for all by driving adoption of Microsoftโ€™s integrated gen AI capabilities.

Second is placing strategic bets on platforms for engineering, construction, HR, sales, and marketing while leveraging our strategic partnersโ€™ platform-specific generative and agentic AI strategies. We want the big providers to bring the models to us, so when an employee asks to use Claude, Perplexity AI, or ChatGPT, itโ€™s fine to use a governed user experience like Microsoft 365 Copilot to bring those models to the user.

Third is disruptive innovation, which focuses less on provider AI and more on our own data. Weโ€™re rich in unstructured, natural language data from 110 years of documentation to engineer and deliver critical infrastructure. Our new BV ASK platform applies generative models against data, democratizing and improving functional expertise across engineering disciplines. So weโ€™re leveraging AI and our data to create that multiplier effect of expertise.

Our fourth theme is in the MLOps space, turning our project sites into trillions of data points that train models to advance our work. Weโ€™re advancing plans to collect telemetry from job site equipment, employee wearables for safety monitoring, geofencing technology, and drones with computer vision to create multivariate models that can help predict the success and profitability of new projects. Rather than turn down good work, weโ€™re creating an AI-driven feedback loop to increase our margins.

The human factor is the sticking point in driving AI adoption. How are you changing minds and behaviors?

Iโ€™ve seen CIOs give everybody Microsoft 365 Copilot and watch adoption hover at five to 10%. Instead, we started by using early successes with Copilot to build a champion network to influence more adoption. We picked a few powerful use cases, identified personas whoโ€™d benefit from those use cases, and created a cohort of early adopters. Then we found another set of use cases and created another cohort, so today, approximately 5,000 employee owners engage in AI cohorts at Black & Veatch, with 97% active usage of our core AI capabilities.

Curriculum within each cohort includes hands-on training and spark sessions to encourage growth and engagement within the community itself. In a few months, we expect to have about 7,500 of our employee owners through a program cohort, and 75% of our employee base actively using generative AI to support their work.

We ask our cohorts for three things: to actively incorporate AI into your daily job, participate enthusiastically in the cohort community, and be a net producer for the community versus a net consumer. The cohorts not only increase AI skill development, but drive a whole new level of collaboration across departments.

Whatโ€™s your advice for CIOs who need to balance AI innovation and data security?

Just as access to the internet and social media platforms took some time to govern in corporations, AI is bringing similar consumer-driven urgency that we need to understand and use to drive efficiencies. People see that AI provides a tangible way to improve their personal lives, so when our teams come into our offices, they expect to have the same access to AI platforms to improve their work efficiency.

My first piece of advice is to educate your teams about the need for innovation and guardrails. We set up an AI governance committee and launched several campaigns coupled with cybersecurity awareness month to outline what weโ€™re doing to deliver experiences using BV data, but within secure and safe guardrails. We also have a technology showcase every year where we educate ourselves on the why and how: why we need the guardrails and how to use the tools. Rather than restricting access, the approach weโ€™re taking is to eliminate friction and frustration while establishing clear guidance and data security controls.

Also, establish a formal process to increase the overall AI acumen across the entire company. AI is different from the innovations of Metaverse and blockchain. People understand AI because itโ€™s so tangible. They can use natural language to create interesting things, so the barriers to innovation are low.

And of course, use every opportunity to shift mindsets. When people express interest in AI tools, I ask them to send me an email with the answer to two questions: Why is this new capability interesting to you, and how will it allow you to do your job better? If the response is thoughtful, we pull them into an earlier cohort immediately. This removes potential frustration by converting their passion into a benefit of a cohort where they can apply their ideas.

Whatโ€™s the key motivation behind this cohort program?

The most critical factor in AI-driven transformation, and in society, is the human element. Our program helps build a level playing field to enable all Black & Veatch creators to do what they do best โ€” create! This new but foundational knowledge across the company allows us to pursue more advanced opportunities with AI. As collective knowledge increases, this opens even more to further advance AI enablement within engineering, and even out in the field. Weโ€™re beginning to see it already.

โ€œ๊ธฐ์ˆ  ๋ถ€์ฑ„๋ถ€ํ„ฐ ์„€๋„์šฐ IT, ํ•™์Šต ๋ถ€์žฌ๊นŒ์ง€โ€ ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜๋ฅผ ์ฃฝ์ด๋Š” IT์˜ 7๊ฐ€์ง€ ํŒจํ„ด

๋Œ€๋ถ€๋ถ„ CIO๋Š” ์ž์‹ ์˜ ์—ญํ• ์ด ์‹œ์Šคํ…œ ๊ฐ€๋™๋ฅ  ๊ฐ™์€ ์šด์˜ ์ง€ํ‘œ๋ณด๋‹ค ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜๋ฅผ ์ œ๊ณตํ•˜๋Š” ์ผ์ด๋ผ๋Š” ์ ์„ ์ด๋ฏธ ์ดํ•ดํ•˜๊ณ  ์žˆ๋‹ค. 2๋…„๋งˆ๋‹ค ์ƒˆ๋กœ์šด ํ˜์‹ ์˜ ๊ธฐํšŒ๊ฐ€ ๋“ฑ์žฅํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด์ œ ๋ฌธ์ œ๋Š” IT๊ฐ€ ์ผ๊ด€๋˜๊ฒŒ ๊ฐ€์น˜๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋Š”์ง€์ด๋‹ค.

์• ์ž์ผ, ๋ฐ๋ธŒ์˜ต์Šค, ITSM ํ”„๋ž™ํ‹ฐ์Šค๋Š” ๋”œ๋ฆฌ๋ฒ„๋ฆฌ ์—ญ๋Ÿ‰๊ณผ ์„œ๋น„์Šค ์—ญ๋Ÿ‰์„ ๊ฐœ์„ ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๊ฐ ๋ฐฐํฌ๊ฐ€ ์„ฑ๊ณตํ• ์ˆ˜๋ก ์ดํ•ด๊ด€๊ณ„์ž์˜ ๊ธฐ๋Œ€์น˜๋Š” ๋” ๋†’์•„์ง„๋‹ค. ํ•˜์ง€๋งŒ, ๊ฐ€์น˜ ์ œ๊ณต์„ ์ผ๊ด€๋˜๊ฒŒ ์œ ์ง€ํ•˜๊ธฐ๋Š” ์‰ฝ์ง€ ์•Š์œผ๋ฉฐ, ์ง์› ์ด์ง ๊ด€๋ฆฌ, ๊ธฐ๋Œ€์— ๋ชป ๋ฏธ์น˜๋Š” ๊ธฐ์ˆ  ํŒŒํŠธ๋„ˆ ๋Œ€์‘, ๋ณด์•ˆ ์šฐ์„ ์ˆœ์œ„ ๊ท ํ˜•, ๊ธฐ์ˆ  ๋ถ€์ฑ„ ํ•ด๊ฒฐ ๋“ฑ์˜ ๊ณผ์ œ๊ฐ€ ์‚ฐ์žฌํ•ด ์žˆ๋‹ค.

CIO๋Š” ์ƒ์„ฑํ˜• AI๋กœ ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜๋ฅผ ๋งŒ๋“ค์–ด๋‚ด๋ผ๋Š” ์••๋ฐ•์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ์ตœ๊ณ  ๊ฒฝ์˜์ง„์€ ์‹คํ—˜์„ ๋„˜์–ด AI ํˆฌ์ž์—์„œ ๋‹จ๊ธฐ์ ์ธ ROI์™€ ์žฅ๊ธฐ์ ์ธ ์ „๋žต์  ๊ฐ€์น˜๋ฅผ ๊ธฐ๋Œ€ํ•˜๊ณ  ์žˆ๋‹ค. ํ•„์ž๋Š” ์ตœ๊ทผ ์ƒ์„ฑํ˜• AI ์‹œ๋Œ€์˜ IT ์กฐ์ง ์žฌ๊ตฌ์ƒ๊ณผ ์„ธ๊ณ„ ์ˆ˜์ค€์˜ IT๋Š” ์–ด๋–ค ๋ชจ์Šต์ด์–ด์•ผ ํ•˜๋Š”์ง€ ์ œ์‹œํ•œ ๋ฐ” ์žˆ๋‹ค. ์ด์™€ ํ•จ๊ป˜ CIO๋Š” IT์˜ ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜๋ฅผ ์Šค์Šค๋กœ ์ฃฝ์ด๋Š” ํ”„๋ž™ํ‹ฐ์Šค์™€ ํ–‰์œ„๋„ ๊ฒฝ๊ณ„ํ•ด์•ผ ํ•œ๋‹ค. ์ „๋ฌธ๊ฐ€๋“ค์ด ์ง€์ ํ•˜๋Š” โ€˜ํ•˜์ง€ ๋ง์•„์•ผ ํ•  ์ผโ€™ 7๊ฐ€์ง€๋ฅผ ์ •๋ฆฌํ–ˆ๋‹ค.

1. ๋น…๋ฑ… ๋ฐฉ์‹ ๋ฐฐํฌ๋ฅผ ๋ชฉํ‘œ๋กœ ์„ค์ •ํ•œ๋‹ค

AI์— ๋Œ€ํ•œ ๊ณผ๋Œ€ํฌ์žฅ์€ ์ƒ์„ฑํ˜• AI ์—ญ๋Ÿ‰ ์ œ๊ณต์— ๋Œ€ํ•œ ๊ฒฝ์˜์ง„์˜ ๊ธฐ๋Œ€์น˜๋ฅผ ๋Œ์–ด์˜ฌ๋ ธ๋‹ค. ์ ์ง€ ์•Š์€ ๊ธฐ์—…์˜ ๊ฒฝ์˜์ง„์ด ์ž์œจ ์šด์˜, ๊ณ ๋„ํ™”ํ•œ ์—์ด์ „ํ‹ฑ AI ๊ธฐ๋Šฅ, ๊ฐœ์ธํ™”๋œ AI ๊ธฐ๋ฐ˜ ๊ณ ๊ฐ ์—ฌ์ •๊นŒ์ง€ ๋ชฉํ‘œ๋กœ ์‚ผ๊ณ  ์žˆ๋‹ค.

์„ฑ๊ณผ๊ฐ€ ๋‚ฎ์€ IT ๋ถ€์„œ๋Š” ์š”๊ตฌ๊ฐ€ ํฐ ์ดํ•ด๊ด€๊ณ„์ž์—๊ฒŒ ํœ˜๋‘˜๋ฆฌ๊ธฐ ์‰ฝ๋‹ค. ๋ฐ˜๋ฉด์— ์ œํ’ˆ ๊ธฐ๋ฐ˜ IT ๋ถ€์„œ๋Š” ๋น…๋ฑ… ๋ฐฉ์‹ ๋ฐฐํฌ๋ฅผ ์•ฝ์†ํ•˜์ง€ ์•Š์œผ๋ฉฐ, ์‹คํ—˜๊ณผ ์ตœ์†Œ๊ธฐ๋Šฅ์ œํ’ˆ(MVP)์„ ์šฐ์„ ์‹œํ•˜๊ณ , ์ ์ง„์ ์œผ๋กœ ๊ฐœ์„ ํ•˜๋Š” ๊ธฐ๋Šฅ์„ ์• ์ž์ผ ๋ฐฉ์‹์œผ๋กœ ์ œ๊ณตํ•œ๋‹ค๋Š” ์›์น™์„ ๊ฐ–์ถ”๊ณ  ์žˆ๋‹ค.

๋ฒ ๋ฆฐํŠธ(Verint)์˜ ๊ณ ๊ฐ AI ํ˜์‹  ๋‹ด๋‹น ๊ธ€๋กœ๋ฒŒ ๋ถ€์‚ฌ์žฅ ๋ผ์ง€ ๋ฐœ๋ผ์ˆœ๋‹ค๋žŒ์€ โ€œ๋””์ง€ํ„ธ ์ „ํ™˜ ์ด๋‹ˆ์…”ํ‹ฐ๋ธŒ๋ฅผ ๊ณ„ํšํ•˜๊ณ  ์‹คํ–‰ํ•  ๋•Œ ๊ธฐ์—…์€ ์ž‘์€ ๊ทœ๋ชจ๋กœ ์‹œ์ž‘ํ•ด ์ค‘๋‹จ ์—†์ด ํ™•์žฅํ•ด์•ผ ํ•œ๋‹คโ€๋ผ๊ณ  ๊ฐ•์กฐํ–ˆ๋‹ค. ๋˜, โ€œํ•ต์‹ฌ ๋ชฉํ‘œ๋Š” ๋ช‡ ๋…„์งœ๋ฆฌ ํ”„๋กœ์ ํŠธ๋ฅผ ๊ธฐ๋‹ค๋ฆฌ๊ธฐ๋ณด๋‹ค ์ธก์ • ๊ฐ€๋Šฅํ•œ ์„ฑ๊ณผ๋ฅผ ๋น ๋ฅด๊ฒŒ ์‹คํ˜„ํ•˜๋Š” ๋ฐ ์žˆ์–ด์•ผ ํ•œ๋‹คโ€๋ผ๊ณ  ๋ง๋ถ™์˜€๋‹ค.

๊ถŒ๊ณ  ์‚ฌํ•ญ. ์ดํ•ด๊ด€๊ณ„์ž๋ฅผ ์Šคํ”„๋ฆฐํŠธ ๋ฆฌ๋ทฐ์— ์ดˆ๋Œ€ํ•˜๊ณ  ์ž์ฃผ ๋ธŒ๋ ˆ์ธ์Šคํ† ๋ฐ ์„ธ์…˜์„ ์ž์ฃผ ์ง„ํ–‰ํ•˜๋ฉฐ, ์• ์ž์ผ ๋”œ๋ฆฌ๋ฒ„๋ฆฌ ๋ฐฉ์‹์œผ๋กœ ๋” ์‰ฝ๊ฒŒ ํ˜‘๋ ฅ๊ด€๊ณ„๋ฅผ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ๋‹ค.

2. ๋ฐฐํฌ ๊ณ„ํš ์—†์ด AI PoC๋ฅผ ์ถ”์ง„ํ•œ๋‹ค

์ตœ์ƒ์œ„ SaaS ๋ฐ ๋ณด์•ˆ ์„œ๋น„์Šค ์—…์ฒด๋Š” ์›Œํฌํ”Œ๋กœ์šฐ๋ฅผ ๊ฐ•ํ™”ํ•˜๋Š” AI ์—์ด์ „ํŠธ๋ฅผ ์ถœ์‹œํ•˜๊ณ  ์žˆ๋‹ค. CIO๋Š” ์–ด๋–ค ๊ธฐ๋Šฅ์ด ๊ฐ€์น˜๋ฅผ ์ œ๊ณตํ•˜๋Š”์ง€, ๋ฐ์ดํ„ฐ ํ’ˆ์งˆ ๊ฐœ์„ ์ด ํ•„์š”ํ•œ ์ง€์ ์€ ์–ด๋””์ธ์ง€, ๋กค์•„์›ƒ์„ ์–ด๋–ป๊ฒŒ ํ™•์žฅํ• ์ง€ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด ์‹คํ—˜์ด ํ•„์š”ํ•˜๋‹ค.

ํ•˜์ง€๋งŒ ๋งŽ์€ IT ๋ถ€์„œ๊ฐ€ ์ด๋Ÿฐ ์‹คํ—˜์—์„œ ์ตœ์ข… ์‚ฌ์šฉ์ž์™€ ์ง์ ‘ ํ˜‘์—…ํ•˜์ง€ ์•Š๋Š”๋‹ค. ์ „์ฒด ๋ฐฐํฌ์— ํ•„์š”ํ•œ ์‚ฌํ•ญ์„ ๋‹ด์€ ์• ์ž์ผ ๊ณ„ํš์„ ์ถฉ๋ถ„ํžˆ ๊ณต์œ ํ•˜์ง€ ์•Š๋Š” ๊ฒฝ์šฐ๋„ ๋งŽ๋‹ค. ๊ฒฐ๊ณผ๋Š” ์ดํ•ด๊ด€๊ณ„์ž ๊ธฐ๋Œ€์น˜ ๋ฏธ์ถฉ์กฑ ๋˜๋Š” ํ”„๋กœ๋•์…˜๊นŒ์ง€ ๋„๋‹ฌํ•˜์ง€ ๋ชปํ•œ PoC์˜ ๋‚œ๋ฆฝ์œผ๋กœ ์ด์–ด์ง„๋‹ค.

์—์ด์˜ค๋‹ฅ์Šค(AODocs) ์ฐฝ์—…์ž ๊ฒธ CEO ์Šคํ…ŒํŒ ๋ˆ์ œ๋Š” โ€œ๋งŽ์€ ํŒ€์ด ๋ช‡ ์ฃผ ๋งŒ์— ๋ฒˆ์ฉ์ด๋Š” ํŒŒ์ผ๋Ÿฟ์„ ๊ณต๊ฐœํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ํ”ํ•œ๋ฐ, ์ด๋Š” AI๊ฐ€ ๋‹จ์ˆœํ•˜๊ณ  ์ฆ‰๊ฐ์ ์ด๋ผ๋Š” ์ธ์‹์„ ๋น„์ฆˆ๋‹ˆ์Šค ๋ถ€์„œ์— ์‹ฌ์–ด์ค€๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ๋˜, โ€œ๊ทธ ๋’ค์—๋Š” ๊ฑฐ๋ฒ„๋„Œ์Šค๊ฐ€ ์ ์šฉ๋œ ๋ฐ์ดํ„ฐ ํŒŒ์ดํ”„๋ผ์ธ ๋ถ€์žฌ, ์ง€์‹์„ ์ตœ์‹ ์œผ๋กœ ์œ ์ง€ํ•  ๊ณ„ํš ๋ถ€์žฌ, ๊ธฐ๋ฐ€ ์ •๋ณด ์œ ์ถœ์„ ๋ง‰๋Š” ํ†ต์ œ ๋ถ€์žฌ, ๋ชจ๋ธ ๋น„์šฉ ๊ด€๋ฆฌ ์ „๋žต ๋ถ€์žฌ ๊ฐ™์€ ํ˜„์‹ค์„ ๋งˆ์ฃผํ•˜๋ฉด์„œ ๋ชจ๋“  ์ผ์ด ๋А๋ ค์ง„๋‹คโ€๋ผ๊ณ  ๋ง๋ถ™์˜€๋‹ค.

ํŒŒ์ผ๋Ÿฟ์—๋Š” ๋ช…ํ™•ํ•œ ๋ชฉํ‘œ๊ฐ€ ํ•„์š”ํ•˜๋ฉฐ, ํŒ€์€ ๋ฐฉํ–ฅ ์ „ํ™˜์ด๋‚˜ ๋ถ€์ง„ํ•œ ์‹คํ—˜์˜ ์ข…๋ฃŒ ์‹œ์ ์„ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ์„ฑ๊ณต์ ์œผ๋กœ ๋ชฉํ‘œ์— ๋„๋‹ฌํ•œ๋‹ค๋ฉด, ๋” ๋งŽ์€ ๋ฐ์ดํ„ฐ, ์‚ฌ์šฉ์ž, ์‚ฌ์šฉ๋ก€๋กœ ํŒŒ์ผ๋Ÿฟ์„ ํ™•์žฅํ•˜๋Š” ๋ฐฉ์•ˆ์„ ๋งˆ๋ จํ•ด์•ผ ํ•œ๋‹ค.

๋ฐ์ดํ„ฐ์ด์ฟ (Dataiku) AI ์ „๋žต ์ฑ…์ž„์ž ์ปคํŠธ ๋ฎˆ๋ฉœ์€ IT ๋ถ€์„œ๊ฐ€ ํŒŒ์ผ๋Ÿฟ ํ”„๋กœ์ ํŠธ์˜ ์„ฑ๊ณต์„ AI ์—์ด์ „ํŠธ๊ฐ€ ํ”„๋กœ๋•์…˜์—์„œ๋„ ์ž‘๋™ํ•œ๋‹ค๋Š” ์ฆ๊ฑฐ๋กœ ์ทจ๊ธ‰ํ•˜๋Š” ๊ฒƒ์ด ์‹ค์ˆ˜๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ๋ฎˆ๋ฉœ์€ โ€œํŒŒ์ผ๋Ÿฟ์€ ๋ฐ์ดํ„ฐ์…‹์ด ์ž‘๊ณ , ์‚ฌ์šฉ์ž๊ฐ€ ๊ด€๋Œ€ํ•˜๋ฉฐ, ๋ฌธ์ œ๊ฐ€ ํ„ฐ์งˆ ๋•Œ ์ธ๊ฐ„์ด ๊ฐ๋…ํ•˜๋Š” ๋“ฑ ์‹ค์ œ ์ œ์•ฝ์ด ์—†๋Š” ํ™˜๊ฒฝ์—์„œ ๋Œ์•„๊ฐ€๊ธฐ ๋•Œ๋ฌธ์— ์„ฑ๊ณตํ•œ๋‹คโ€๋ผ๊ณ  ์„ค๋ช…ํ–ˆ๋‹ค.

๊ถŒ๊ณ  ์‚ฌํ•ญ. IT๋Š” PoC์˜ ์„ฑ๊ณต ๊ธฐ์ค€์„ ์ •์˜ํ•˜๋Š” ๋ฌธ์„œ๋ฅผ ์ดํ•ด๊ด€๊ณ„์ž์™€ ํ•จ๊ป˜ ์ž‘์„ฑํ•˜๊ณ , ์• ์ž์ผ ๋ฐฉ๋ฒ•๋ก ์„ ์ ์šฉํ•ด PoC์™€ ์—ฌ๋Ÿฌ ํŒŒ์ผ๋Ÿฟ ๋‹จ๊ณ„๋ฅผ ๊ด€๋ฆฌํ•ด์•ผ ํ•œ๋‹ค. ์ด๋Ÿฐ ์›์น™์€ ์ดํ•ด๊ด€๊ณ„์ž๊ฐ€ ์—ฌ์ •์— ํ•จ๊ป˜ํ•˜๋„๋ก ๋งŒ๋“ค๊ณ , ์‹คํ—˜์ด ๋ฐฐํฌ ๋ชฉํ‘œ ์ค‘ ํ•˜๋‚˜๋ผ๋Š” ์ ์„ ๋ช…ํ™•ํžˆ ํ•œ๋‹ค.

3. ์ฑ„ํƒ์ด ์•„๋‹ˆ๋ผ ๋ฐฐํฌ์—๋งŒ ์ง‘์ค‘ํ•œ๋‹ค

๋ฐ˜๋ณต์  ๋ฐฐํฌ์— ๋Œ€ํ•œ ์กฐ์ง์˜ ๋™์˜๋ฅผ ํ™•๋ณดํ•˜๋Š” ์ผ์€ ์ผ๊ด€๋œ ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜ ์ œ๊ณต์— ํ•„์š”ํ•˜์ง€๋งŒ ์ถฉ๋ถ„์กฐ๊ฑด์€ ์•„๋‹ˆ๋‹ค. ๋„ˆ๋ฌด ๋งŽ์€ ๋ฐ๋ธŒ์˜ต์Šค ๋ฐ ๋ฐ์ดํ„ฐ ์‚ฌ์ด์–ธ์ŠคํŒ€์ด ๋ฐฐํฌ๊ฐ€ ์ผ์ •๋Œ€๋กœ ์ง„ํ–‰๋˜๊ณ  ๋ชฉํ‘œ ๋ฒ”์œ„๋ฅผ ๋‹ฌ์„ฑํ•˜๋ฉด โ€œ์ผ์„ ์ž˜ ๋๋ƒˆ๋‹คโ€๋ผ๊ณ  ์ƒ๊ฐํ•œ๋‹ค. ํ•˜์ง€๋งŒ ์ด๋Ÿฐ ์ธ์‹์€ IT์˜ ๋ณ€ํ™”๊ด€๋ฆฌ ์ฑ…์ž„์„ ๊ฐ„๊ณผํ•˜๋Š” ๊ฒƒ์ด๋ฉฐ, ํŠนํžˆ AI ์—ญ๋Ÿ‰์€ ๋ถ€์„œ ์šด์˜ ๋ฐฉ์‹์„ ํฌ๊ฒŒ ๋ฐ”๊ฟ€ ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์—์„œ ์ฃผ์˜๊ฐ€ ํ•„์š”ํ•˜๋‹ค.

์‚ฌ๋ฆฌํƒ€์‚ฌ(Saritasa) ์ฐฝ์—…์ž ๊ฒธ CEO ๋‹‰ ํ”„๋กœ์—˜๋ฆฌ์น˜๋Š” โ€œIT ๋ถ€์„œ๋Š” ์ˆ™๋ จ๋„๊ฐ€ ๋†’์ง€๋งŒ IT ๊ตฌ์„ฑ์›์€ ๊ตฌ์ถ•ํ•œ ์ œํ’ˆ์˜ ์ตœ์ข… ์‚ฌ์šฉ์ž์ธ ๊ฒฝ์šฐ๊ฐ€ ๋“œ๋ฌผ๊ณ , ์‹ค์ œ ์‚ฌ์šฉ์ž๋กœ๋ถ€ํ„ฐ ์ถฉ๋ถ„ํ•œ ํ”ผ๋“œ๋ฐฑ์„ ๋ฐ›๋Š” ๊ฒฝ์šฐ๋„ ๋“œ๋ฌผ๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ํ”„๋กœ์—˜๋ฆฌ์น˜๋Š” โ€œ๊ทธ ๊ฒฐ๊ณผ, ๊ธฐ๋Šฅ์ ์œผ๋กœ ์™„๋ฒฝํ•˜์ง€๋งŒ ์•„๋ฌด๋„ ์“ฐ์ง€ ์•Š๋Š” ์†”๋ฃจ์…˜์ด ๋  ์ˆ˜ ์žˆ๋‹คโ€๋ผ๋ฉฐ, โ€œํ•ด๊ฒฐ์ฑ…์€ ๋‹จ์ˆœํ•˜๋‹ค. ์ตœ์ข… ์‚ฌ์šฉ์ž๋ฅผ ์ดˆ๊ธฐ๋ถ€ํ„ฐ ์ž์ฃผ ์ฐธ์—ฌ์‹œํ‚ค๊ณ  ๋ชจ๋“  ๋‹จ๊ณ„์—์„œ ํ”ผ๋“œ๋ฐฑ์„ ๋“ฃ๊ณ , ์‹ค์ œ ์‚ฌ์šฉ์ž๊ฐ€ ์ž˜ ์“ธ ์ˆ˜ ์žˆ๋Š” ์†”๋ฃจ์…˜์„ ๊ตฌ์ถ•ํ•ด์•ผ ํ•œ๋‹คโ€๋ผ๊ณ  ์กฐ์–ธํ–ˆ๋‹ค.

๊ถŒ๊ณ  ์‚ฌํ•ญ. CIO๊ฐ€ ์ƒ์„ฑํ˜• AI ์‹œ๋Œ€์— ์• ์ž์ผ ํ”„๋ž™ํ‹ฐ์Šค๋ฅผ ์žฌ์ ๊ฒ€ํ•ด์•ผ ํ•˜๋Š” ์ด์œ  ์ค‘ ํ•˜๋‚˜๋Š” ํ”„๋กœ์ ํŠธ์˜ โ€˜์™„๋ฃŒ(done)โ€™ ์ƒํƒœ๋ฅผ ๋‹ค์‹œ ์ •์˜ํ•ด ์• ์ž์ผํŒ€์ด ์ฑ„ํƒ๊ณผ ๋ณ€ํ™”๊ด€๋ฆฌ๋ฅผ ๊ธฐ๋Šฅ ์ˆ˜์ค€์˜ ์ˆ˜์šฉ ๊ธฐ์ค€์— ํฌํ•จํ•˜๋„๋ก ๋งŒ๋“ค๊ธฐ ์œ„ํ•ด์„œ๋‹ค.

4. ๋น„์ฆˆ๋‹ˆ์Šค ๋ถ€์„œ์˜ ์—…๋ฌด ๋ฐฉ์‹์„ ์ฒ˜๋ฐฉํ•œ๋‹ค

์ด์‚ฌํšŒ๋Š” CIO๊ฐ€ AI ์ „๋žต ๊ฑฐ๋ฒ„๋„Œ์Šค ๋ชจ๋ธ์„ ์ด์•ผ๊ธฐํ•˜๊ธธ ๊ธฐ๋Œ€ํ•œ๋‹ค. ์ด ๋ชจ๋ธ์—๋Š” ์ง์›์ด AI ์—ญ๋Ÿ‰์„ ์–ด๋–ป๊ฒŒ ์‹คํ—˜ํ•ด์•ผ ํ•˜๋Š”์ง€ ์„ค๋ช…ํ•˜๋Š” ๋ฐฉ๋ฒ•์ด ํฌํ•จ๋ผ์•ผ ํ•œ๋‹ค. ๊ฑฐ๋ฒ„๋„Œ์Šค๋Š” ์ง์›์ด ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋Š” AI ๋„๊ตฌ, ์ ‘๊ทผ ๊ฐ€๋Šฅํ•œ ๋ฐ์ดํ„ฐ, ์‹คํ—˜์˜ ์„ฑ๊ณตยทํ•™์Šตยท์‹คํŒจ๋ฅผ ์–ด๋””์— ๋ณด๊ณ ํ•ด์•ผ ํ•˜๋Š”์ง€๋ฅผ ์ •์˜ํ•ด์•ผ ํ•œ๋‹ค.

CIO๋Š” ์•„ํ‚คํ…ํŠธ, ๋น„์ฆˆ๋‹ˆ์Šค ๊ด€๊ณ„ ๊ด€๋ฆฌ์ž, ์• ๋„๋ฆฌ์ŠคํŠธ๋ฅผ ์ง€์ •ํ•ด ์ด๋Ÿฐ ์‹คํ—˜์„ ํ•จ๊ป˜ ์ง„ํ–‰ํ•ด์•ผ ํ•œ๋‹ค. ํ•˜์ง€๋งŒ ์ด๋Ÿฐ ๊ฒฝ๊ณ„ ์˜์—ญ์„ ๋„˜์–ด ๋น„์ฆˆ๋‹ˆ์Šค ๋ถ€์„œ์˜ ์›Œํฌํ”Œ๋กœ์šฐ๋ฅผ ์ฒ˜๋ฐฉํ•˜๋Š” ๊ฒƒ์€ ๊ฐ€์น˜๋ฅผ ์†์ƒํ•  ์ˆ˜ ์žˆ๋Š”๋ฐ, IT ๋ถ€์„œ๋Š” ๋น„์ฆˆ๋‹ˆ์Šค ๋ถ€์„œ์˜ ์šด์˜ ๋ชฉํ‘œ์™€ ์›Œํฌํ”Œ๋กœ์šฐ ์˜ˆ์™ธ๋ฅผ ์ž˜ ์•Œ์ง€ ๋ชปํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค.

์‹œํŠธ๋ฆญ์Šค ๋ถ€์‚ฌ์žฅ ๊ฒธ CTO์ด์ž ๋ฏธ๋ž˜ํ•™์ž์ธ ๋ธŒ๋ผ์ด์–ธ ๋งค๋“ ์€ โ€œ์ง„์งœ ๋ณ€ํ™”๋Š” ์ด์ œ ์‚ฌ๋žŒ์˜ ์‹ค์ œ ์—…๋ฌด ๋ฐฉ์‹์—์„œ ์ถœ๋ฐœํ•˜๋Š” ์ƒํ–ฅ์‹ ๋ณ€ํ™”์ด๋ฉฐ, ์กฐ์ง์ด ์ •ํ•œ ๋ฐฉ์‹์—์„œ ์ถœ๋ฐœํ•˜๋Š” ๋ณ€ํ™”๊ฐ€ ์•„๋‹ˆ๋‹คโ€๋ผ๊ณ  ๋งํ•œ๋‹ค.

๋งค๋“ ์€ โ€œ์ง์› ์Šค์Šค๋กœ AI ๋„๊ตฌ๋ฅผ ๋„์ž…ํ•˜๊ธฐ ์‹œ์ž‘ํ•œ ์ˆœ๊ฐ„๋ถ€ํ„ฐ ํ•˜ํ–ฅ์‹ ์žฅ๊ธฐ ๋กœ๋“œ๋งต ๋ชจ๋ธ์€ ๊นจ์กŒ์ง€๋งŒ, ์˜ค๋Š˜๋‚ ์—๋„ ๋Œ€๋ถ€๋ถ„ ๊ธฐ์—…์€ ์„œ๋“œํŒŒํ‹ฐ AI๋ฅผ ๊ฑฐ๋ฒ„๋„Œ์Šค ํ•˜์— ์•ˆ์ „ํ•˜๊ฒŒ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒฝ๋กœ๋ฅผ ์ œ๊ณตํ•˜์ง€ ์•Š๋Š”๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ๋˜ํ•œ, โ€œ์Šน์ธ๋œ ๊ฒฝ๋กœ๊ฐ€ ์—†์–ด๋„ ์‚ฌ๋žŒ์€ ์–ด์ฐจํ”ผ AI ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜๋ฉฐ, ๊ด€๋ฆฌ๋˜์ง€ ์•Š์€ AI ์ฑ„ํƒ์€ ์ „๋žต์  ๊ฐ€์น˜๋ฅผ ๋งŒ๋“ค์ง€ ๋ชปํ•œ ์ฑ„ ์œ„ํ—˜๋งŒ ํ‚ค์šด๋‹คโ€๋ผ๊ณ  ๊ฒฝ๊ณ ํ–ˆ๋‹ค.

๊ถŒ๊ณ  ์‚ฌํ•ญ. CIO๋Š” ํ•˜ํ–ฅ์‹ ์ „๋žต์„ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ํ•ด์•ผ ํ•˜์ง€๋งŒ, ๋””์ง€ํ„ธ ์ „ํ™˜์ด ์‹คํŒจํ•˜๋Š” 1์ˆœ์œ„ ์ด์œ ๋Š” IT๊ฐ€ ์šด์˜์˜ ๋ฐœ์ „์— ์ƒํ–ฅ์‹ ์ฐธ์—ฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค๋Š” ์ ์„ ์ธ์ •ํ•˜์ง€ ์•Š์„ ๋•Œ๋‹ค. IT ๋ถ€์„œ๋Š” ์‹์Šค์‹œ๊ทธ๋งˆ ๊ต์œก์„ ๋ฐ›์€ ํ”„๋กœ์„ธ์Šค ์ „๋ฌธ๊ฐ€๋ฅผ ์ง€์ •ํ•ด ์‹คํ—˜์˜ ํŒŒํŠธ๋„ˆ๋กœ ์ฐธ์—ฌ์‹œํ‚ค๊ณ , AI ์—์ด์ „ํŠธ์™€ ์‚ฌ๋žŒ์ด ํ˜‘์—…ํ•˜๋Š” ์›Œํฌํ”Œ๋กœ์šฐ ํ˜์‹ ์„ ์•ˆ๋‚ดํ•˜๋Š” ๊ฐ€์ด๋“œ ์—ญํ• ์„ ๋งก๊ฒจ์•ผ ํ•œ๋‹ค.

5. AI ๋ฐฐํฌ ๊ณผ์ •์—์„œ ๊ธฐ์ˆ  ๋ถ€์ฑ„๋ฅผ ๊ฐ€์†ํ™”ํ•œ๋‹ค

SaaS ์„œ๋น„์Šค์˜ ๋‚œ๋ฆฝ์€ ๋งŽ์€ IT ๋ถ€์„œ๊ฐ€ ๊ฒช๋Š” ๋ฌธ์ œ์ด๋ฉฐ, ๋น„์ฆˆ๋‹ˆ์Šค ๋ถ€์„œ ๋ฆฌ๋”๊ฐ€ ๋„๊ตฌ๋ฅผ ์ง์ ‘ ์„ ํƒํ•˜๊ณ  ์„€๋„์šฐ IT ํ”„๋ž™ํ‹ฐ์Šค๋ฅผ ํ‚ค์šธ ๋•Œ ํŠนํžˆ ์‹ฌํ•ด์ง„๋‹ค. ๊ธฐ์—…์€ AI๋ฅผ ์‹คํ—˜ํ•ด์•ผ ํ•˜์ง€๋งŒ, ํ†ต์ œ๋˜์ง€ ์•Š์€ AI ์—์ด์ „ํŠธ๋ฅผ ๋ฐฐํฌํ•˜๋Š” ํ–‰์œ„๋Š” ๋ณด์•ˆ๊ณผ ์ปดํ”Œ๋ผ์ด์–ธ์Šค ์œ„ํ—˜์ด ๋œ๋‹ค.

IT/๋ณด์•ˆ ํ†ตํ•ฉ ํ”Œ๋žซํผ ํšŒ์‚ฌ ์ด๋ฃจ(Iru)์˜ ์ตœ๊ณ  ๊ธฐ์ˆ  ์ „๋ฌธ๊ฐ€ ์›ฐ๋˜ ๋„๋“œ๋Š” โ€œ๊ธฐ์—…์€ ํŠน์ • ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋ ค๊ณ  ์—ฌ๋Ÿฌ AI ๋„๊ตฌ๋ฅผ ๊ตฌ๋งคํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์•ž์œผ๋กœ ๋ช‡ ๋…„ ๋™์•ˆ ์ด๋Ÿฐ ํ™•์‚ฐ์œผ๋กœ ์ธํ•ด IT ๋ถ€์„œ๊ฐ€ ๊ด€๋ฆฌํ•ด์•ผ ํ•  ์†”๋ฃจ์…˜ ์—…์ฒด ์ˆ˜๊ฐ€ ์ง€๋‚˜์น˜๊ฒŒ ๋Š˜์–ด๋‚  ๊ฒƒโ€์ด๋ผ๊ณ  ๋งํ–ˆ๋‹ค.

IT ์•„ํ‚คํ…ํŠธ๋Š” ํ‘œ์ค€์œผ๋กœ ์ด์•ผ๊ธฐํ•˜๊ณ  ํ™•์žฅ ๊ฐ€๋Šฅํ•œ ํ”Œ๋žซํผ ์‚ฌ์šฉ์„ ํ•ต์‹ฌ ์ „๋žต์œผ๋กœ ๋ฐ€์–ด์•ผ ํ•œ๋‹ค. ์ดํ•ด๊ด€๊ณ„์ž๊ฐ€ ๊ธฐ์ˆ ๊ณผ ๋„๊ตฌ๋ฅผ ์ฒ˜๋ฐฉํ•˜๋ ค๋Š” ์••๋ฐ•์€ ์–ธ์ œ๋‚˜ ์กด์žฌํ•˜์ง€๋งŒ, ์•„ํ‚คํ…ํŠธ๋Š” ์ƒ์‡„ ์š”์†Œ, ์‹ ๊ทœ ํ”Œ๋žซํผ ์ง€์› ๋น„์šฉ, ๊ธฐ์ˆ  ๋ถ€์ฑ„ ๋ˆ„์  ์œ„ํ—˜์„ ์•Œ๋ ค์•ผ ํ•œ๋‹ค.

์‚ฌ์ด๋ฒ„ ์œ„ํ—˜ ํ‰๊ฐ€ ํ”Œ๋žซํผ ์ฝ”๋ฒ„(Kovrr)์˜ CEO ์•ผํ‚ค๋ฅด ๊ณจ๋ž€์€ โ€œAI์™€ ๋ฐ์ดํ„ฐ ์ด๋‹ˆ์…”ํ‹ฐ๋ธŒ๊ฐ€ ์ž์‚ฐ ๊ฐ€์‹œ์„ฑ๊ณผ ์‹œ์Šคํ…œ์ด ๊ฐ€์น˜๋ฅผ ๋งŒ๋“ค๋ฉด์„œ ๋™์‹œ์— ๋…ธ์ถœ ์œ„ํ—˜์„ ํ‚ค์šฐ๋Š” ๋ฐฉ์‹์— ๋Œ€ํ•œ ๊ณต์œ ๋œ ๊ด€์ ์—†์ด ์ถ”์ง„๋  ๋•Œ IT ์กฐ์ง์€ ์ž ์žฌ์  ์˜ํ–ฅ๋ ฅ์„ ์Šค์Šค๋กœ ์ œํ•œํ•œ๋‹คโ€๋ผ๊ณ  ์ง€์ ํ–ˆ๋‹ค. ๊ณจ๋ž€์€ โ€œํšจ๊ณผ์ ์ธ ๊ฑฐ๋ฒ„๋„Œ์Šค๋Š” ์–ด๋–ค ๋„๊ตฌ๊ฐ€ ์กด์žฌํ•˜๋Š”์ง€, ์–ด๋–ค ๋ฐ์ดํ„ฐ์™€ ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š”์ง€, ์žฅ์• ๊ฐ€ ๋‚ฌ์„ ๋•Œ ์–ด๋–ค ํ•จ์˜๊ฐ€ ์žˆ๋Š”์ง€๋ฅผ ์ดํ•ดํ•˜๋Š” ๋ฐ ๋‹ฌ๋ ค ์žˆ๋‹คโ€๋ผ๊ณ  ์„ค๋ช…ํ–ˆ๋‹ค.

๊ถŒ๊ณ  ์‚ฌํ•ญ. ๋น„์ฆˆ๋‹ˆ์Šค ์กฐ์ง์ด ํ•ด๋ฒ•์„ ์ฒ˜๋ฐฉํ•˜๋ ค๊ณ  ํ•  ๋•Œ๊ฐ€ ๋งŽ์ง€๋งŒ, ๋ชฉํ‘œํ•œ ๋น„์ฆˆ๋‹ˆ์Šค ์š”๊ตฌ์‚ฌํ•ญ์„ ์งˆ๋ฌธ์œผ๋กœ ํ™•์ธํ•˜๋Š” ์ฑ…์ž„์€ IT์— ์žˆ๋‹ค. CIO๋Š” IT ๋ฆฌ๋”๊ฐ€ ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ๊ฐ, ์šฉ๊ธฐ, ์ธ๋‚ด๋ฅผ ๊ธฐ๋ฅด๋„๋ก ๋„์™€ ์ดํ•ด๊ด€๊ณ„์ž์˜ โ€˜ํ•ด๋ฒ• ์š”๊ตฌโ€™๋ฅผ ํ–‰๊ตฐ ๋ช…๋ น์œผ๋กœ ๋ฐ›์•„๋“ค์ด์ง€ ๋ง๊ณ  ๋ชฉํ‘œ ์ค‘์‹ฌ์œผ๋กœ ํ˜‘์—…ํ•˜๋„๋ก ๋งŒ๋“ค์–ด์•ผ ํ•œ๋‹ค.

6. ์ง€์†์ ์ธ ์ง€์› ์—†์ด ์ผํšŒ์„ฑ ํ”„๋กœ์ ํŠธ๋ฅผ ์ˆ˜์šฉํ•œ๋‹ค

์• ์ž์ผ ํŒ€์ด ์•„์ด๋””์–ด์—์„œ PoC, ํ”„๋กœ๋•์…˜ ๋ฐฐํฌ, ์ตœ์ข… ์‚ฌ์šฉ์ž ์ฑ„ํƒ๊นŒ์ง€ AI๋ฅผ ์„ฑ๊ณต์ ์œผ๋กœ ํ†ต๊ณผ์‹œํ‚ค๋”๋ผ๋„ ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜ ์ œ๊ณต์€ ๊ทธ๋•Œ๋ถ€ํ„ฐ ์‹œ์ž‘์ธ ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹ค. ๋‹ค์Œ ๋‹จ๊ณ„๋Š” ํ”ผ๋“œ๋ฐฑ ์ˆ˜์ง‘, ๊ฒฐ๊ณผ ์ธก์ •, ์„ฑ๊ณต ๊ธฐ์ค€์„ ์ถฉ์กฑํ•˜๊ธฐ ์œ„ํ•œ ๋ฐ˜๋ณต ๊ฐœ์„ ์ด๋‹ค.

์• ์ž์ผ ํŒ€์€ ๋ฐ˜๋ณต์„ ์›ํ•˜๊ณ , ์ดํ•ด๊ด€๊ณ„์ž๋Š” ๊ธฐ์ˆ ยท๋ฐ์ดํ„ฐยทAI ์—ญ๋Ÿ‰์˜ ๊ฐœ์„ ์„ ์›ํ•œ๋‹ค. ๊ทธ๋ ‡๋‹ค๋ฉด IT ๋ถ€์„œ๋Š” ์™œ ๋ ˆ๊ฑฐ์‹œ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์ด ๋„ˆ๋ฌด ๋งŽ๊ณ , ๊ธฐ์ˆ  ๋ถ€์ฑ„๊ฐ€ ์Œ“์ด๋ฉฐ, ์ตœ์ข… ์‚ฌ์šฉ์ž๋Š” ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ํ˜„๋Œ€ํ™”๋ฅผ ์š”๊ตฌํ•˜๋ฉฐ ์ขŒ์ ˆํ•˜๋Š” ๊ฒƒ์ผ๊นŒ?

AI ๊ธฐ๋ฐ˜ ์šด์˜ ์ตœ์ ํ™” ํ”Œ๋žซํผ ํšŒ์‚ฌ ์˜ตํ‚ค(Opkey) CEO ํŒ์นด์ง€ ๊ณ ์—˜์€ โ€œ๋งŽ์€ IT ํŒ€์€ ๊ตฌํ˜„ ์ดํ›„๋ฅผ ๊ณ„ํšํ•˜์ง€ ์•Š๊ณ , ์ง€์†์ ์ธ ์ตœ์ ํ™”์— ํ•„์š”ํ•œ ์˜ˆ์‚ฐ์„ ์ฑ…์ •ํ•˜์ง€ ์•Š๋Š”๋‹ค. ์ง€์†์ ์ธ ์ตœ์ ํ™”์—๋Š” ํ…Œ์ŠคํŠธ, ์‚ฌ์šฉ์ž ์ฑ„ํƒ, ๋ฐ์ดํ„ฐ ๊ฑฐ๋ฒ„๋„Œ์Šค, ๋ฐ˜๋ณต ๊ฐœ์„ ์ด ํฌํ•จ๋˜๋Š”๋ฐ, ์ด๋Ÿฐ ์š”์†Œ๊ฐ€ ์žˆ์–ด์•ผ ์“ธ๋งŒํ•œ ์‹œ์Šคํ…œ์ด โ€˜์„œ๋ž ์† ์†Œํ”„ํŠธ์›จ์–ดโ€™๊ฐ€ ๋˜๋Š” ๊ฒƒ์„ ๋ง‰์„ ์ˆ˜ ์žˆ๋‹คโ€๋ผ๊ณ  ๋งํ–ˆ๋‹ค. ๋˜, โ€œ๊ฐ€์žฅ ๊ฐ•๋ ฅํ•œ ํ˜์‹ ์€ IT๊ฐ€ โ€˜๊ธฐ์ˆ  ๋ฐฐํฌโ€™์—์„œ โ€˜๋น„์ฆˆ๋‹ˆ์Šค์™€ ํ•จ๊ป˜ ์ง„ํ™”ํ•˜๋Š” ๋™์  ์ตœ์ ํ™” ์ „ํ™˜ ๊ตฌ์ถ•โ€™์œผ๋กœ ์ „ํ™˜ํ•  ๋•Œ ์„ฑ๊ณตํ•œ๋‹คโ€๋ผ๊ณ  ๊ฐ•์กฐํ–ˆ๋‹ค.

๊ถŒ๊ณ  ์‚ฌํ•ญ. ์• ์ž์ผ PMO์˜ ํ•ต์‹ฌ ์ฑ…์ž„์€ ๋ถ€์„œ ๋ฆฌ๋”์™€ CFO๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์žฌ๋ฌด ๊ฑฐ๋ฒ„๋„Œ์Šค๋ฅผ ๊ฐ•์ œํ•˜๋Š” ์ผ์ด๋‹ค. ์„ฑ๊ณต์ ์ธ ๋ฐฐํฌ์™€ ๊ฐ€์น˜ ์ œ๊ณต์œผ๋กœ ์ด์–ด์ง€๋Š” ์ด๋‹ˆ์…”ํ‹ฐ๋ธŒ์—๋Š” ์—…๊ทธ๋ ˆ์ด๋“œ์™€ ๊ธฐํƒ€ ๋ผ์ดํ”„์‚ฌ์ดํด ๊ด€๋ฆฌ์— ํ•„์š”ํ•œ ์ง€์†์ ์ธ ์˜ˆ์‚ฐ์ด ํ•„์š”ํ•˜๋‹ค.

7. ํ•™์Šต ์‹œ๊ฐ„์„ ์œ„ํ•œ ํˆฌ์ž๊ฐ€ ๋ถ€์กฑํ•˜๋‹ค

๋งŽ์€ CIO๋Š” ๊ต์œก ๊ณผ์ • ๋ฐฐ์ •, ์ปจํผ๋Ÿฐ์Šค ์ฐธ์„, ๋ฆฌ๋” ์ฝ”์นญ์— ๋ฐฐ์ •ํ•˜๋Š” ์˜ˆ์‚ฐ์„ ๊ฐ–๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ํ•™์Šต ํ”„๋กœ๊ทธ๋žจ ๊ตฌ๋…๋งŒ์œผ๋กœ๋Š” ์ถฉ๋ถ„ํ•˜์ง€ ์•Š์œผ๋ฉฐ, ๋งŽ์€ IT ์ง์›์€ ๊ต์œก์— ์‹œ๊ฐ„์„ ์“ฐ๊ธฐ ์–ด๋ ค์šธ ๋งŒํผ ์••๋ฐ•๊ณผ ์‹œ๊ฐ„ ์ œ์•ฝ์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ ์ง์›์€ ์ƒˆ๋กœ์šด ๊ธฐ์ˆ ์„ ์‹คํ—˜ํ•˜๊ณ  ๊ฒฝํ—˜ํ•˜๊ณ  ๊ฐ€๋ฅด์น˜๋ฉด์„œ ํ‰์ƒํ•™์Šต ์Šต๊ด€์„ ๊ธฐ๋ฅผ ์‹œ๊ฐ„์ด ํ•„์š”ํ•˜๋‹ค.

๋””์ง€ํ„ธ ์ „ํ™˜ ์„œ๋น„์Šค ํšŒ์‚ฌ ๋ฐ”์Šค(VASS)์˜ ์ˆ˜์„ ๊ธฐ์ˆ  ์ „๋ฌธ๊ฐ€ ๋งˆ์ดํด ํŒŒ์ดํ…”์€ โ€œ์„ฑ๊ณผ๊ฐ€ ๋†’์€ ํŒ€์€ ์žฅ๊ธฐ ๊ณ„ํš์— ํ•™์Šต์„ ํฌํ•จํ•ด ์—ญ๋Ÿ‰ ์„ฑ์žฅ๊ณผ ํ˜์‹ ์ด ํ•จ๊ป˜ ์ผ์–ด๋‚˜๋„๋ก ๋งŒ๋“ ๋‹คโ€๋ผ๋ฉฐ, โ€œ๊ธฐ์ˆ  ํŒ€์— ์ฃผ 1์‹œ๊ฐ„ ํ•™์Šต์„ ์š”๊ตฌํ•˜๊ณ  ์ž๊ฒฉ์ฆ์— ํ•„์š”ํ•œ ์‹œํ—˜ ์‘์‹œ๋ฃŒ๋ฅผ ํ™˜๊ธ‰ํ•˜๊ณ , ํŒ€์›์ด ๋ฐฐ์šด ๋‚ด์šฉ์„ ์ฃผ๋ณ€์— ๊ณต์œ ํ•˜๋Š” ์ ์‹ฌ ํ•™์Šต ์„ธ์…˜์— ์ธ์„ผํ‹ฐ๋ธŒ๋ฅผ ์ œ๊ณตํ•˜๋ผโ€๋ผ๊ณ  ์กฐ์–ธํ–ˆ๋‹ค.

๊ถŒ๊ณ  ์‚ฌํ•ญ. CIO๋Š” IT๊ฐ€ ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜๋ฅผ ์ฃฝ์ด๋Š” ๋ฐฉ์‹๋ฟ ์•„๋‹ˆ๋ผ ๋ฆฌ๋”์‹ญ์ด IT ๋ฌธํ™”๋ฅผ ์ฃฝ์ด๋Š” ๋ฐฉ์‹๋„ ๋Œ์•„๋ด์•ผ ํ•œ๋‹ค. ๋ฆฌ๋”๋Š” IT์— 130% ๊ฐ€๋™๋ฅ ์„ ๋ฌด๊ธฐํ•œ ๊ฐ•์š”ํ•  ์ˆ˜ ์—†์œผ๋ฉฐ, ํ”„๋กœ์„ธ์Šค ์ง„ํ™”๋ฅผ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ํ•™์Šต ๊ธฐํšŒ์™€ ํ•™์Šต ๊ธฐ๊ฐ„์„ ๋งŒ๋“ค์–ด์•ผ ํ•œ๋‹ค.

IT์˜ ๊ฐ€์น˜๋ฅผ ์Šค์Šค๋กœ ์†์ƒํ•˜์ง€ ์•Š์œผ๋ ค๋ฉด, ๊ฒฐ๋ก ์€ CIO๊ฐ€ ๊ฐ•๋ ฅํ•œ ๊ฑฐ๋ฒ„๋„Œ์Šค์™€ ์œ ์—ฐํ•œ ์šด์˜ ๋ชจ๋ธ์„ ๋„์ž…ํ•˜๊ณ  ์ฑ„ํƒํ•˜๋Š” ๋ฌธ์ œ๋กœ ๊ท€๊ฒฐ๋œ๋‹ค. ๋˜ํ•œ CIO๋Š” ์ดํ•ด๊ด€๊ณ„์ž์™€ ํŒŒํŠธ๋„ˆ์‹ญ์„ ๋งบ์–ด ๋น„์ฆˆ๋‹ˆ์Šค ๊ฐ€์น˜๋ฅผ ์ œ๊ณตํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ฝ”์นญํ•˜๋Š” ๋™์‹œ์— ๊ฑฐ๋ฒ„๋„Œ์Šค, ์šด์˜ ์›์น™, ํ˜‘์—… ์ฑ…์ž„์—์„œ ์–‘๋ณดํ•  ์ˆ˜ ์—†๋Š” ๊ธฐ์ค€์„ ์„ธ์šฐ๊ณ  ์‹คํ–‰ํ•ด์•ผ ํ•œ๋‹ค.
dl-ciokorea@fondryco.com

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