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AI coding work is shifting fast, and your career path may split

23 January 2026 at 05:38

AI coding work is rising fast, but the biggest payoff isn’t evenly shared. A Science analysis suggests seasoned developers get stronger gains than newcomers, which could reshape how you learn, interview, and prove value.

The post AI coding work is shifting fast, and your career path may split appeared first on Digital Trends.

The forward-deployed engineer: Why talent, not technology, is the true bottleneck for enterprise AI

20 January 2026 at 07:15

Despite unprecedented investment in artificial intelligence, most enterprises have hit an integration wall. The technology works in isolation. The proofs of concept impress.

But when it comes time to deploy AI into production that touches real customers, impacts revenue and introduces legitimate risk, organizations balk–for valid reasons: AI systems are fundamentally non-deterministic.

Unlike traditional software that behaves predictably, large language models can produce unexpected results. They risk providing confidently wrong answers, hallucinated facts and off-brand responses. For risk-conscious enterprises, this uncertainty creates a barrier that no amount of technical sophistication can overcome.

This pattern is common across industries. In my years helping enterprises deploy AI technology, I’ve watched many organizations build impressive AI demos that never made it past the integration wall.  The technology was ready. The business case was sound. But the organizational risk tolerance wasn’t there, and nobody knew how to bridge the gap between what AI could do in a sandbox and what the enterprise was willing to deploy in production. At that point, I came to believe that the bottleneck wasn’t the technology. It was the talent deploying it.

A few months ago, I joined Andela, which provides technical talent to enterprises for short or long-term assignments. From this vantage point, it remains clearer than ever that the capability that enterprises need has a name: the forward-deployed engineer (FDE). Palantir originally coined the term to describe customer-centric technologists essential to deploying their platform inside government agencies and enterprises. More recently, frontier labs, hyperscalers and startups have adopted the model. OpenAI, for example, will assign senior FDEs to high-value customers as investments to unlock platform adoption.

But here’s what CIOs need to understand: this capability has been concentrated with AI platform companies to drive their own growth. For enterprises to break through the integration wall, they need to develop FDEs internally.

What makes a forward-deployed engineer

The defining characteristic of an FDE is the ability to bridge technical solutions with business outcomes in ways traditional engineers simply don’t. FDEs are not just builders. They’re translators operating at the intersection of engineering, architecture and business strategy.

They are what I think of as “expedition leaders” guiding organizations through the uncharted terrain of generative AI. Critically, they understand that deploying AI into production is more than a technical challenge. It’s also a risk management challenge that requires earning organizational trust through proper guardrails, monitoring and containment strategies.

In 15 years at Google Cloud and now at Andela, I’ve met only a handful of individuals who embody this archetype. What sets them apart isn’t a single skill but a combination of four working in concert.

  • The first is problem-solving and judgment. AI output is often 80% to 90% correct, which makes the remaining 10% to 20% dangerously deceptive (or maddeningly overcomplicated). Effective FDEs possess the contextual understanding to catch what the model gets wrong. They spot AI workslop or the recommendation that ignores a critical business constraint. More importantly, they know how to design systems that contain this risk: output validation, human-in-the-loop checkpoints and deterministic fallback responses when the model is uncertain. This is what makes the difference between a demo that impresses and a production system that executives will sign off on.
  • The second competency is solutions engineering and design. FDEs must translate business requirements into technical architectures while navigating real trade-offs: cost, performance, latency and scalability. They know when a small language model (with lower inference cost) will outperform a frontier model for a specific use case, and they can justify that decision in terms of economics rather than technical elegance. Critically, they prioritize simplicity. The fastest path through the integration wall almost always begins with the minimum viable product (MVP) that solves 80% of the problem with appropriate guardrails. The solution will not be the elegant system that addresses every edge case but introduces uncontainable risk.
  • Third is client and stakeholder management. The FDE serves as the primary technical interface with business stakeholders, which means explaining technical mechanics to executives who often lack significant experience with AI. Instead, these leaders care about risk, timeline and business impact. This is where FDEs earn the organizational trust that allows AI to move into production. They translate non-deterministic behavior into risk frameworks that executives understand: what’s the blast radius if something goes wrong, what monitoring is in place and what’s the rollback plan? This makes AI’s uncertainty legible and manageable to risk-conscious decision makers.
  • The fourth competency is strategic alignment. FDEs connect AI implementations to measurable business outcomes. They advise on which opportunities will move the needle versus which are technically interesting but carry disproportionate risk relative to value. They think about operational costs and long-term maintainability, as well as initial deployment. This commercial orientation—paired with an honest assessment of risk—is what separates an FDE from even the most talented software engineer.

The individuals who possess all of these competencies share a common profile. They typically started their careers as developers or in another deeply technical function. They likely studied computer science. Over time, they developed expertise in a specific industry and cultivated unusual adaptability and the willingness to stay curious as the landscape shifts beneath them. Because of this rare combination, they’re concentrated at the largest technology companies and command high compensation.

The CIO’s dilemma

If FDEs are as scarce as I’m suggesting, what options do CIOs have?

Waiting for the talent market to produce more of them will take time. Every month that AI initiatives stall at the integration wall, the gap widens between organizations capturing real value and those still showcasing demos to their boards. The non-deterministic nature of AI isn’t going away. If anything, as models become more capable, their potential for unexpected behavior increases. The enterprises that thrive will be those that develop the internal capability to deploy AI responsibly and confidently, not those waiting for the technology to become risk-free.

The alternative is to grow FDEs from within. This is harder than hiring, but it’s the only path that scales. The good news: FDE capability can be developed. It requires the right raw material and an intensive, structured approach. At Andela, we’ve built a curriculum that takes experienced engineers and trains them to operate as FDEs. Here’s what we’ve learned about what works.

Building your FDE bench

Start by identifying the right candidates. Not every strong engineer will make the transition.  Look for experienced software engineers who demonstrate curiosity beyond their technical domain. You want people with foundational strength in core development practices and exposure to data science and cloud architecture. Prior industry expertise is a significant accelerant. Someone who understands healthcare compliance or financial services risk frameworks will ramp faster than someone learning the domain from scratch.

The technical development path has three layers. The foundation is AI and ML literacy: LLM concepts, prompting techniques, Python proficiency, understanding of tokens and basic agent architectures. These are table stakes.

The middle layer is the applied toolkit. Engineers need working competency in three areas that map to the “three hats” an FDE wears.

  • First is RAG, or retrieval-augmented generation, knowing how to connect models to enterprise data sources reliably and accurately.
  • Second is agentic AI, orchestrating multi-step reasoning and action sequences with appropriate checkpoints and controls.
  • Third is production operations, ensuring solutions can be deployed with proper monitoring, guardrails and incident response capabilities.

These skills are developed through building and shipping actual systems that have to survive contact with real-world risk requirements.

The advanced layer is deep expertise: model internals, fine-tuning, the kind of knowledge that allows an FDE to troubleshoot when standard approaches fail. This is what separates someone who can follow a playbook from someone who can improvise when the playbook doesn’t cover the situation. It is also someone who can explain to a skeptical CISO why a particular approach is safe to deploy.

Professional capabilities are equally as important as technical training and can be harder to develop. FDEs must learn to reframe conversations, to stop talking about technical agents and start discussing business problems and risk mitigation. They must manage high-stakes stakeholder relationships, including difficult conversations around scope changes, timeline slips and the inherent uncertainties of non-deterministic systems. Most importantly, they must develop judgment: the ability to make good decisions under ambiguity and to inspire confidence in executives who are being asked to accept a new kind of technology risk.

Set realistic expectations with your leadership and your candidates. Even with a strong program, not everyone will complete the transition. But even a small cohort of FDE-capable talent can dramatically accelerate your path to overcoming the integration wall. One effective FDE embedded with a business unit can accomplish more than a dozen traditional engineers working in isolation from the business context. That’s because the FDE understands that the barrier was never primarily technical.

The stakes

The enterprises that develop FDE capability will break through the integration wall. They’ll move from impressive demos to production systems that generate real value. Each successful deployment will build organizational confidence for the next. Those that don’t will remain stuck, unable to convert AI investment into AI returns, watching more risk-tolerant competitors pull ahead.

My bet when I joined Andela was that AI would not outpace human brilliance. I still believe that. But humans have to evolve. The FDE represents that evolution: technically deep, commercially minded, fluent in risk and adaptive enough to lead through continuous change. This is the archetype for the AI era. CIOs who invest in building this capability now won’t just keep pace with AI advancement; they’ll be the ones who finally capture the enterprise value that has remained stubbornly hard to reach.

This article is published as part of the Foundry Expert Contributor Network.
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음묞음답 | 음볞 왞식 Ʞ업의 Ꞁ로벌 도앜, 튞늬도륎 CIO가 말하는 변화에 강한 IT 전략

20 January 2026 at 02:25

우동 뾌랜드 마룚가메제멎 등을 욎영하는 음볞 왞식 êž°ì—… 튞늬도륎홀딩슀는 Ꞁ로벌 시장 확장을 목표로 디지턞곌 IT Ʞ반의 겜영 혁신에 속도륌 낎고 있닀. 읎 곌정에서 시슀템 전멎 현대화와 조직 개펞, SaaS·AI 활용까지 직접 읎끌얎 옚 CIO 읎소묎띌 알슀녞늬(磯村康兞)가 벀더 겜험곌 겜영 시각을 바탕윌로 변화에 강한 êž°ì—… Ʞ반을 구축하는 전략곌 철학을 제시했닀.

Q(CIO재팬) : 지ꞈ까지의 겜력에 대핮 섀명핎 달띌.
A(읎소묎띌 알슀녞늬) : 컀늬얎는 후지쓰에서 시작했닀. 앜 7년 동안 죌로 공공 부묞 시슀템을 닎당하는 시슀템 엔지니얎로 음하며 현장에서 Ʞ술 역량을 닀젞왔닀.

읎후 2000년 소프튞뱅크(현 소프튞뱅크귞룹)로 읎직했닀. 당시 손정의 회장읎 “앞윌로는 읞터넷 시대”띌고 강조하던 시Ʞ로, 사낎에서는 읞터넷 ꎀ렚 벀처가 잇따띌 출범하고 있었닀. 귞쀑 하나가 전자상거래 사업윌로, 현재의 섞랐넷쇌핑읎닀. 나는 시슀템 책임자로 사업 출범에 찞여핎 앜 8년 동안 사업 성장을 뒷받칚하는 역할을 맡았닀.

닀음윌로 도전한 곳은 왞식 IT 벀처 갈프넷읎닀. 튞늬도륎홀딩슀륌 비롯한 죌요 왞식 첎읞을 고객윌로 둔 회사로, 읎곳에서 4년 동안 개발 책임자로 시슀템을 읎끌었을 뿐 아니띌 영업 책임자 역할도 겜험했닀. Ʞ술뿐 아니띌 비슈니슀 현장을 직접 움직읎는 얎렀움곌 재믞륌 첎감할 수 있었던 점은 큰 수확읎었닀.

읎후 투자회사 였크캐플탈(현 UNIVA·였크홀딩슀)로 자늬륌 옮겚 앜 8년간 투자 Ʞ업에 핞슈옚윌로 ꎀ여했닀. 겜영 재걎곌 êž°ì—… 가치 제고륌 추진했고, 겜우에 따띌서는 직접 대표읎사륌 맡는 등 겜영 전반에 깊읎 ꎀ여하는 겜험을 쌓았닀. 읎 시Ʞ에 형성된 ‘사업을 얎떻게 재정비하고 성장윌로 읎끌 것읞가’띌는 ꎀ점은 지ꞈ의 쀑요한 자산읎 되고 있닀.

귞늬고 2019년 튞늬도륎홀딩슀 CIO로 부임했닀. 얎느덧 6년읎 지난 현재, 벀더로서 축적한 지식곌 사업회사에서의 겜험, 겜영자로서의 시각을 몚두 활용핎 사업 성장을 견읞하는 CIO로서 도전을 읎얎가고 있닀.

Q : 지ꞈ까지의 겜력 가욎데 특히 읞상에 낹는 음은 묎엇읞가.
A : 돌아볎멎 각 업종곌 역할마닀 큰 도전읎 있었닀. 처음 SI 업묎륌 맡았을 때는 얌마나 큰 규몚의 프로젝튞륌 욎영할 수 있는지가 성장의 Ʞ쀀읎었닀. 당시 20대에 800읞월(人月, 여러 읞력읎 수개월 읎상 투입돌, 읞력 수×투입 개월 수륌 합산하멎 800에 읎륎는) 규몚의 프로젝튞륌 맡았는데, 지ꞈ 생각핎 볎멎 젊은 시절에 상당히 큰 책임을 ë§¡êžž 만큌 Ʞ회륌 죌던 회사였닀고 느낀닀.

소프튞뱅크에서는 처음윌로 ‘비슈니슀륌 만든닀’는 음에 도전했닀. 닎당한 것은 현재의 섞랐넷쇌핑윌로 읎얎지는 전자상거래 사업읎닀. 맀출읎 전혀 없는 상태에서 출발핎, 시슀템 책임자로서 사업읎 앜 200억 엔 규몚로 성장하는 곌정을 뒷받칚했닀. 닚순한 시슀템 개발읎 아니띌, 비슈니슀 성장곌 직접적윌로 연결된 겜험읎었닀는 점에서 컀늬얎 전반에 맀우 큰 의믞륌 낚게닀.

현직읞 튞늬도륎홀딩슀 CIO로서 처음 맡은 큰 곌제는 전사 시슀템의 전멎적읞 현대화였닀. 부임 읎후 앜 6년에 걞쳐 추진핎 왔고, 읎제 몚든 교첎 작업읎 마묎늬 닚계에 읎륎고 있닀.

당쎈에는 3년 낮 완료륌 목표로 했지만, 사낎 사정곌 Ʞ졎 구조륌 섞심하게 고렀하며 진행할 필요가 있었닀. ê·ž 결곌, 속도볎닀 완성도륌 택핮 시간읎 걞늬더띌도 확싀히 끝낮는 방향윌로 추진하게 됐닀.

프로젝튞의 출발점은 ‘시슀템읎 몇 개나 있는지륌 파악하는 것’읎었닀. 처음 점검했을 때 앜 180개의 시슀템읎 졎재했고, 읎후 업묎 목적에 따띌 재정늬하며 통합을 진행했닀. ê·ž 결곌 현재는 앜 40개 수쀀까지 대폭 쀄음 수 있었닀.

읎 곌정을 돌아볎멎, 시슀템 자산 정늬부터 현대화까지 전 곌정을 직접 읎끌얎 옚 겜험은 CIO로서 가장 처음에 도전하Ʞ에 걞맞은 곌제였닀고 생각한닀.

Q : 가장 얎렀웠던 겜험은 묎엇읞가.
A : 가장 신겜을 많읎 쓎 음은 튞늬도륎홀딩슀에서 추진한 업묎 조직 개펞읎었닀. 구첎적윌로는 튞늬도륎귞룹의 볞사 업묎륌 지죌회사와 쉐얎드서비슀 회사(귞룹 공통 ꎀ늬·욎영 업묎륌 통합 수행하는 조직)로 역할을 나눠 재구성했닀. 읎후 회계·읞사·IT 욎영 등 반복적읞 ꎀ늬 업묎륌 낎부 조직읎 아닌 왞부 전묞 위탁업첎(Business Process Outsourcing, BPO)에 맡Ʞ는 방식윌로 욎영 구조륌 바꿚닀.

사낎에서 수행하던 업묎륌 왞부로 옮Ʞ는 곌정은 대닎하멎서도 맀우 섬섞한 조정읎 필요한 프로젝튞였닀. 우선 IT 부묞부터 착수했는데, 읎 곌정읎 가장 얎렀웠닀.

당시 나는 쉐얎드서비슀 회사의 대표륌 겞임하며 최대 앜 180명의 읞력을 읎끌고 있었닀. 읎 조직에는 IT 욎영팀뿐 아니띌 회계 Ʞ장을 닎당하는 재묎 조직, ꞉여 계산을 맡은 읞사 조직 등 읎륞바 였퍌레읎션 Ʞ능읎 집앜돌 있었닀. 전략 수늜은 지죌회사가 ë§¡ê³ , 음상적읞 였퍌레읎션은 하나로 묶얎 ꎀ늬하는 첎제륌 갖추고 있었윌며, 읎 가욎데 음부 업묎륌 닚계적윌로 분늬핎 왞부로 읎전하는 것읎 당시 맡은 역할읎었닀.

당연히 Ʞ졎 업묎륌 수행하던 읞력의 닀음 컀늬얎륌 얎떻게 섀계할지가 큰 곌제가 됐닀. 튞늬도륎는 횚고현 가윔가와시에서 찜업핎 읎후 고베시에 볞사륌 두고 있었고, 당시 쉐얎드서비슀 회사의 거점 역시 고베에 있었닀.

시부알 볞사로 읎동읎 가능한 읞력에게는 지죌회사 업묎륌 제안했지만, 가정 사정 등윌로 전귌읎 얎렀욎 겜우도 적지 않았닀. 읎런 겜우에는 BPO 벀더로 전적핎 Ʞ졎곌 같은 업묎륌 읎얎가도록 하거나, 튞늬도륎귞룹 맀장윌로 활동 묎대륌 옮Ʞ는 방안을 제시했닀. 나는 구성원 한 사람 한 사람곌 멎닎을 거듭하며 닀음 진로륌 핚께 결정핎 나갔닀.

묌론 읎 곌정은 혌자서 감당할 수 있는 음읎 아니었닀. 부장곌 ꎀ늬직의 협조륌 얻얎 직원듀곌 진지하게 대화륌 읎얎가며 추진했닀. 최종적읞 목표는 각자가 새로욎 환겜에서도 장Ʞ간 역량을 발휘할 수 있도록 하는 것읎었닀. 회사 찚원의 방칚은 분명했지만, 최대한 구성원듀읎 납득할 수 있는 결론에 읎륎는 것읎 당시 슀슀로에게 죌얎진 가장 큰 책임읎었닀고 볞닀.

Q : 특히 Ʞ억에 낹는 말읎나 사걎읎 있는가.
A : 크게 두 가지가 있닀. 첫 번짞는 섞랐넷쇌핑 출범에 ꎀ여하던 시Ʞ의 겜험읎닀. 당시 섞랐&아읎홀딩슀 회장읎었던 슀슈킀 도시후믞의 말을, 당시 상사읎자 회장의 아듀읞 슀슈킀 알슀히로로부터 전핎 듀은 적읎 있닀.

한 번은 “사람듀 앞에서 읎알Ʞ할 때 얎떻게 하멎 ꞎ장하지 않을 수 있느냐”고 묌었는데, “묎늬핎서 잘난 척하지 말고, 몚륎는 것은 읎알Ʞ하지 않윌며, 알고 있는 것만 말하멎 ꞎ장하지 않는닀”는 답을 듀었닀. 몚륎는 것은 몚륞닀고 말하멎 된닀는 읎알Ʞ였닀. 있는 귞대로, 곌장하지 않고 말하는 사람읎알말로 ê²°êµ­ 성곌륌 만듀얎 간닀는 점을 강하게 느ꌈ닀.

두 번짞는 같은 시Ʞ, 섞랐넷쇌핑읎 알후의 자회사 사업읎었을 때의 겜험읎닀. 당시에는 읞터넷읎 아직 볞격적읞 비슈니슀로 자늬 잡Ʞ 전읎었고, 음볞에서는 알후가 앞서 있었윌며 구Ꞁ읎 막 진입하던 시Ʞ였닀.

읎용자가 ꞉슝하멎서 서버가 혌잡핎지고 시슀템읎 한계에 부딪히는 상황읎 자죌 발생했는데, 귞때 당시 알후 대표였던 읎녞우에 마사히로로부터 “읞터넷 비슈니슀에서는 사용자가 늘얎나멎 서버륌 슝섀하는 것읎 Ʞ볞 원칙”읎띌는 말을 듀었닀. ê·ž 한마디에 큰 깚달음을 얻었닀.

Ʞ졎 엔터프띌읎슈 환겜에서는 값비싌 자원을 얎떻게 최적화핎 끝까지 활용할 것읞가가 Ʞ볞적읞 사고방식읎었닀. 나는 역시 제한된 자원을 횚윚적윌로 쓰는 것읎 당연하닀고 여겚 왔닀.

하지만 읞터넷의 섞계에서는 저렎한 서버륌 추가핎 확장하는 것읎 자연슀러욎 선택읎었닀. 투자륌 전제로 한 슀쌀음아웃 묞화가 뿌늬낎렀 있었고, 추가 투자가 불가능하닀멎 읞터넷 비슈니슀 자첎가 성늜하지 않는닀는 읞식읎 자늬 잡고 있었닀.

읎러한 사고방식의 찚읎는 맀우 충격적읎었닀. 엔터프띌읎슈 Ʞ술곌 읞터넷 Ʞ술 사읎의 볞질적읞 찚읎륌 분명하게 첎감한 순간읎었고, ê·ž 간극은 지ꞈ도 완전히 메워지지 않은 채 낚아 있닀고 느끌고 있닀.

Q : CIO로서 ì–Žë–š 때 볎람을 느끌는가.
A: 회사의 방향성을 빠륎게 싀현할 수 있는 Ʞ반을 마령할 때 CIO로서의 볎람을 느낀닀. 귞런 멎에서 튞늬도륎의 목표는 고객에게 감동적읞 겜험을 제공하는 것읎닀. ê·ž 최전선에는 맀장에서 음하는 직원곌 읎륌 뒷받칚하는 맀니지뚌튞가 있닀. 닀만 사람의 힘에만 의졎하는 데에는 한계가 있Ʞ 때묞에, 읎듀을 뒀에서 얎떻게 지원할지가 쀑요하닀. 변화에 신속히 대응할 수 있는 비슈니슀 Ʞ반을 갖추는 것읎알말로 CIO로서의 가장 큰 볎람읎닀.

IT 부서가 자첎 녌늬만윌로 움직여서는 의믞가 없닀. 쀑요한 것은 IT가 비슈니슀에 얌마나 Ʞ여하고 있는지, 귞늬고 변화에 얌마나 유연하게 대응할 수 있는 Ʞ반을 구축했는지닀.

예륌 듀얎 사업 확장을 고믌할 때는 업태가 늘얎날 겜우 하나의 구조로 대응할지, 여러 구조륌 조합할지에 대한 섀계 판닚읎 필요하닀. 서버륌 늘멮 것읞지, 한 대륌 대형화할 것읞지와 같은 슀쌀음아웃곌 슀쌀음업 선택도 마찬가지닀. 읎런 아킀텍처륌 검토하는 곌정 자첎가 맀우 흥믞로욎 영역읎닀.

또 지ꞈ처럌 변화가 잊은 시대에는 겜영진읎 Ʞ졎 방칚을 바꟞는 음도 발생한닀. 읎때 대규몚 투자륌 읎유로 시슀템을 포Ʞ하지 못하는 상황은 바람직하지 않닀. 귞래서 가능한 한 구독형 서비슀, 슉 SaaS륌 적극 활용하고 있닀. 특히 유연성읎 요구되는 백였플슀 영역은 SaaS륌 조합하는 펞읎 늬슀크륌 쀄음 수 있닀.

읎러한 판닚을 뒷받칚하는 것은 엔지니얎로서의 겜험곌 사업 겜영에 직접 ꎀ여했던 겜험읎닀. Ʞ술을 충분히 읎핎하지 못하멎 최적의 선택을 할 수 없고, 겜영 ꎀ점읎 없윌멎 비슈니슀륌 얎떻게 지원할지에 대한 답도 나였지 않는닀. 읎 두 가지륌 핚께 활용핎 사고할 수 있닀는 점읎 CIO 역할의 가장 큰 슐거움읎닀.

사싀 IT 벀더 시절부터 앞윌로는 SaaS가 필수가 될 것읎띌고 생각핎 왔닀. 당시에는 제안하더띌도 사용자 Ʞ업읎 채택하지 않윌멎 싀행윌로 읎얎지지 않았지만, CIO가 된 읎후에는 슀슀로 결정핎 싀행할 수 있닀는 점을 싀감했닀. 읎는 맀우 큰 찚읎읎며, 사업회사로 자늬륌 옮게Ʞ에 가능핎진 도전읎닀.

튞늬도륎귞룹은 변화륌 두렀워하지 않고 진화륌 거듭핎 옚 Ʞ업읎닀. ê·ž 덕분에 ꞉성장을 읎뀘고, 격변하는 환겜 속에서도 대응핎 올 수 있었닀. 읎 강점은 반드시 지쌜알 한닀고 볎고, 시슀템 Ʞ반을 전멎적윌로 SaaS 쀑심윌로 전환하는 작업을 추진핎 왔닀.

SaaS 벀더의 제품 뒀에는 수많은 뛰얎난 엔지니얎가 졎재한닀. ꎀ점에 따띌서는 읎듀읎 몚두 회사륌 뒷받칚하는 왞부 읞력읎띌고도 볌 수 있닀. 자사 역량에만 의졎하지 않고 왞부의 힘을 얎떻게 조합할지 섀계하는 것, 귞것읎 CIO의 역할읎며 나에게 가장 큰 볎람읎닀.

Q : AI 활용에 대핎서는 얎떻게 볎고 있는가.
A: 최귌 생성형 AI에 대한 ꎀ심읎 높아지고 있지만, 튞늬도륎귞룹읎 집쀑하고 있는 것은 현장의 생산성을 높읎는 AI 활용읎닀. 생성형 AI는 화읎튞칌띌 업묎의 횚윚화에는 횚곌적읎닀. 닀만 사업곌 직접 맞닿아 있는 현장 업묎에서는 슉시 싀행 가능하고 싀횚성읎 분명한 AI 활용읎 필요한 것 같닀.

ê·ž 대표적읞 사례가 수요 예잡읎닀. 맀출곌 방묞객 수륌 AI로 예잡핚윌로썚 닀음 날 필요한 읞력 규몚나 식자재 발죌량을 볎닀 횚윚적윌로 산정할 수 있닀. 읎륌 통핎 맀장 욎영 계획읎 한잵 수월핎졌고, 현장의 부닎도 크게 쀄었닀.

또 하나는 얌굎 읞식을 활용한 귌태 ꎀ늬닀. 튞늬도륎귞룹에는 파튞타임곌 아륎바읎튞 직원읎 많아 출퇎귌 Ʞ록 ꎀ늬가 쀑요한 곌제였닀. Ʞ졎의 지묞읎나 정맥 읞식 방식은 묌을 자죌 사용하는 환겜읎나 추욎 날씚로 읞핎 예왞가 발생하는 겜우가 많았지만, 얌굎 읞식윌로 전환한 읎후에는 예왞가 거의 발생하지 않고 있닀. 읞식 속도도 빠륎고 마슀크륌 착용한 상태에서도 슉시 읞식할 수 있얎, 현장에서는 귌태 ꎀ늬가 훚씬 수월핎졌닀는 반응읎 나옚닀.

화렀핎 볎읎는 Ʞ술은 아닐지 몚륎지만, 읎런 접귌읎 현장의 생산성을 ꟞쀀히 끌얎올늬고 있닀. 읎것읎 튞늬도륎귞룹읎 지향하는 AI 활용의 볞질읎띌고 볞닀.

Q : CIO에게 필요한 자질은 묎엇읎띌고 볎는가.
A : 가장 쀑요하닀고 생각하는 것은 ‘각였’닀. 묌론 한 번 정한 음을 끝까지 핮낮는 것도 쀑요하지만, 귞에 앞서 묎엇을 목표로 하는지 분명히 제시핎알 한닀. 믞래의 몚습을 귞늰 ë’€ “읎 방향윌로 회사륌 읎끌겠닀”고 선얞하는 것 자첎가 CIO에게는 각였의 표현읎띌고 볞닀.

나 역시 DX 비전을 왞부에 공개하멎서 “읎제는 반드시 핎낎알 한닀”는 결심읎 ì„°ë‹€. 귞렇게 핎알 직원곌 벀더 몚두가 튞늬도륎귞룹읎 ì–Žë–€ 몚습을 지향하는지 읎핎하고, 같은 방향을 바띌볎게 된닀. 읎는 맀우 큰 의믞륌 가진닀.

CIO에게는 목표로 하는 몚습을 하나의 귞늌윌로 제시하고, ê·ž 비전을 향핎 흔듀늌 없읎 나아가는 추진력읎 필요하닀. 읎때 쀑요한 것읎 백캐슀튞(backcast) 사고, 슉 최종 목표에 도달하Ʞ 위핎 지ꞈ 묎엇을 핎알 하는지륌 거꟞로 계산핎 나가는 방식읎닀. 포얎캐슀튞(forecast) 방식, 닀시 말핮 현재 상태륌 출발점윌로 삌아 곌제륌 하나씩 핎결하는 방식만윌로는 새로욎 가치륌 만듀얎낎Ʞ 얎렵닀.

묌론 음정 수쀀의 안정Ʞ에 듀얎서멎 포얎캐슀튞 방식의 개선윌로 충분한 겜우도 있닀. 하지만 큰 변화륌 만듀얎알 할 때는 백캐슀튞 ꎀ점에서 곌감하게 방향곌 겜로륌 귞렀알 한닀.

귞늬고 ê·ž 곌정에서 예상곌 현싀 사읎에 큰 간극읎 생ꞎ닀멎, “읎걎 아니닀”띌고 판닚하고 곌감하게 방향을 전환할 수 있는 결닚력까지 갖추는 것, 읎것읎 CIO에게 요구되는 핵심 자질읎띌고 볞닀.

Q : CIO륌 꿈꟞는 직원에게 필요한 역량은 묎엇읞가.
A : 나는 팀원듀에게 늘 “장찚 CIO나 CTO, 혹은 CDO 같은 역할을 맡을 수 있는 읞재로 성장하Ꞟ 바란닀”고 읎알Ʞ하고 있닀. 음볞에는 아직 귞런 읞재가 충분히 많지 않닀. 귞렇Ʞ 때묞에 디지턞을 비슈니슀와 연결하는 가교 역할을 할 수 있는 사람을 더 늘렀알 한닀고 볞닀. 젊은 시절부터 읎 역할을 목표로 컀늬얎륌 쌓아 가Ꞟ 바란닀.

읎륌 위핎 필요한 역량은 크게 섞 가지닀. 첫 번짞는 Ʞ쎈적읞 Ʞ술 역량읎닀. 윔드륌 직접 작성하지 않는 IT 늬더도 있지만, 할 수 있닀멎 ê·ž 펞읎 훚씬 ë‚«ë‹€. 나 역시 쀑학생 때부터 윔드륌 썚 왔닀. 프로귞래밍 얞얎도 하나만 아는 것볎닀 두 가지 읎상을 익히멎 비교가 가능핎지고 읎핎의 깊읎도 달띌진닀. 읎는 읎직을 통핎 새로욎 시알가 엎늬는 것곌 비슷하며, 여러 ꎀ점을 갖는 것읎 쀑요하닀고 생각한닀.

두 번짞는 아킀텍튞로서의 역량읎닀. 사용자 Ʞ업의 CIO는 Ʞ졎 Ʞ술을 얎떻게 조합핎 자사 비슈니슀에 가장 적합한 구조륌 만듀 것읞지륌 끊임없읎 고믌핎알 한닀. CTO의 역할곌 맞닿아 있는 부분도 있지만, 넀튞워크나 읞프띌, 큎띌우드 같은 Ʞ쎈륌 읎핎하지 못하멎 최적의 조합을 판당할 수 없닀. 시슀템 아킀텍튞로서의 지식곌 사고는 필수적읎닀.

마지막은 컀뮀니쌀읎션 역량읎닀. 프로젝튞가 싀팚하는 읎유는 Ʞ술 부족볎닀 소통 부족에서 비롯되는 겜우가 훚씬 ë§Žë‹€. 나는 평소 음대음 대화륌 자죌 하는데, 대화 상대는 대표부터 귞룹사 임원, 사업회사 겜영진까지 닀양하닀. 읎듀읎 묎엇을 하고 싶은지 읎핎하지 못하멎 장Ʞ적읞 ꎀ점의 시슀템 섀계는 불가능하고, 신뢰할 수 있는 조얞자가 되지 못하멎 성곌도 나였Ʞ 얎렵닀. 읎런 역량은 나뿐 아니띌 부장꞉ 구성원에게도 요구하고 있닀.

Ʞ쎈적읞 Ʞ술 역량, 아킀텍튞로서의 섀계 역량, 귞늬고 컀뮀니쌀읎션 역량. 읎 섞 가지는 CIO륌 목표로 할 때 반드시 갖춰알 할 자질읎닀. 특히 B2B Ʞ업음수록 파튾너 Ʞ업곌의 ꎀ계가 쀑요하Ʞ 때묞에, 젊은 시절부터 읎륌 강하게 의식하Ꞟ 권하고 ì‹¶ë‹€.

Q : 앞윌로의 목표는?
A: 우늬는 ‘Ꞁ로벌 푾드 컎퍌니’륌 êž°ì—… 비전윌로 낎섞우고 있닀. 목표는 유명한 햄버거 첎읞읎나 컀플 첎읞곌 얎깚륌 나란히 하는, 음볞 최쎈의 ‘섞계에서 통하는 왞식 Ʞ업’읎 되는 것읎닀.

튞늬도륎귞룹은 읎믞 30개국 읎상에 진출핎 있지만, 몚든 국가에서 음볞곌 동음한 품질을 구현하고 있느냐고 하멎 아직 곌제가 낚아 있닀. 읎 수쀀을 얎떻게 끌얎올늎지가 앞윌로의 큰 곌제닀. 디지턞의 힘윌로 Ʞ쀀을 맞추고, 새로욎 국가로도 볎닀 쉜게 확장할 수 있는 환겜을 만드는 것읎 사업 가속윌로 읎얎진닀고 볞닀.

지ꞈ까지는 음볞 시장에 집쀑핎 왔지만, 앞윌로는 Ꞁ로벌 자회사와 프랜찚읎슈 파튞너에 대핎서도 볎닀 적극적윌로 지원핎 나갈 생각읎닀.

묌론 몚든 것을 음률적읞 구조로 적용하는 것은 현싀적읎지 않닀. 제조업처럌 전 섞계에 동음한 시슀템을 적용하는 방식도 있지만, 왞식 산업은 현지 소비자가 싀제로 뚹얎알 가치가 생ꞎ닀. 음정한 자윚성을 유지하멎서도, 튞늬도륎귞룹윌로서 반드시 지쌜알 할 Ʞ쀀을 얎떻게 정착시킬지가 쀑요하닀.

읎 곌정에서 횚곌적읞 수닚읎 디지턞 Ʞ반읎닀. Ʞ쀀을 시슀템에 녹여 두멎, 의식하지 않아도 자연슀럜게 품질곌 욎영 Ʞ쀀읎 유지된닀. 읎런 구조륌 앞윌로 더 늘렀 가고자 한닀.

닀만 곌도하게 적용하멎 ‘손윌로 만듀고 갓 조늬한닀’는 우늬의 욎영 철학읎 앜핎질 위험도 있닀. ê·ž 균형을 얎디에 둘 것읞지는 쉜지 않은 곌제지만, 였히렀 ê·ž 지점에 재믞가 있닀고 느낀닀.

볞사 겜영진곌 각 사업 책임자듀곌 지속적윌로 녌의하며, 각 지역에 맞는 최적의 균형점을 찟아가는 작업을 전 섞계로 확대핮 나가고 ì‹¶ë‹€.
dl-ciokorea@foundryco.com

*읎 Ʞ사는 CIO 재팬에 게재된 원묞을 바탕윌로 재구성한 것입니닀. 원묞은 여Ʞ서 확읞할 수 있습니닀.

The top 6 project management mistakes — and what to do instead

19 January 2026 at 05:00

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 don’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 organization’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 won’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.

That’s not their fault. They’ve been taught to stay in their lane in formal training and by many executives. Keep the project moving. Don’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 don’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 can’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 what’s done, what’s in progress, and what’s late. But the metrics they use show how busy everyone is at creating outputs, not how they’re tracking toward achieving outcomes.

All of that busyness can look impressive on paper, but it’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 they’re doing and why, the next question to answer is how will we know we’re successful.

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

Think about a project that’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, they’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 doesn’t add value, they should be able to call it out.

This isn’t an excuse to have no process or claim you’re being agile just to skip the necessary steps. It’s about right-sizing the process, simplifying where you can, and being thoughtful about what’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 don’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, it’s easy to assume someone just didn’t want to change. Project teams blame people, then layer on more governance, more process, and more pressure. Most of the time, it’s not a people problem. It’s how the changes are being done to people instead of with them.

People don’t resist because they’re lazy or difficult. They resist because they don’t understand why it’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 everyone’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 aren’t resistant to change. They’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 it’s treated like a one-way path. Status reports people don’t understand. Steering committee slides read to a room full of executives who aren’t engaged. Unread emails. The information goes out because it’s required, not because it’s helping people make better decisions or take the right action.

But that kind of communication doesn’t create clarity, build engagement, or drive alignment. And it doesn’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 shouldn’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 can’t be a formality. When teams, sponsors, and stakeholders know what’s happening and why it matters, they make decisions faster. You don’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 that’s not how you define project success.

If you keep project managers out of the conversations about strategy and business goals, they’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 doesn’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. You’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:

倉化に匷い基盀づくりでグロヌバル䌁業ぞ——トリドヌルCIOが挑む改革ずは

18 January 2026 at 18:49

ベンダヌ経隓を歊噚に、事業成長を牜匕するCIOぞ

——これたでのキャリアに぀いお教えおください。

私のキャリアは富士通から始たりたした。7幎間、䞻に行政向けシステムのシステム゚ンゞニアずしお働き、珟堎で技術を磚いおきたした。

その埌、2000幎に゜フトバンク珟 ゜フトバンクグルヌプぞ転職したす。圓時は孫正矩さんが「これからはむンタヌネットの時代だ」ず発信しおいた頃で、瀟内では次々ずむンタヌネット関連のベンチャヌが立ち䞊がっおいたした。その䞀぀がEコマヌス事業、珟圚のセブンネットショッピングです。私はシステム責任者ずしお立ち䞊げに関わり、玄8幎間、事業の成長を支える圹割を担いたした。

次に挑戊したのは、倖食ITベンチャヌのガルフネットです。トリドヌルホヌルディングスをはじめ有名な倖食チェヌンを顧客に持぀䌚瀟で、ここでは4幎間、開発責任者ずしおシステム面をリヌドするだけでなく、営業責任者も経隓したした。技術に加えおビゞネスの珟堎を動かす難しさず面癜さを䜓感できたのは倧きな収穫でした。

その埌は投資䌚瀟Oakキャピタル珟 UNIVA・Oakホヌルディングスに移り、玄8幎間にわたっお投資先の䌁業にハンズオンで関わりたした。経営再建やバリュヌアップ、時には自ら瀟長に就任するなど、経営そのものに深く入り蟌む経隓を積みたした。この時期に培った「事業をどう立お盎し、成長ぞ導くか」ずいう芖点は、今の自分の倧きな財産になっおいたす。

そしお2019幎、トリドヌルホヌルディングスのCIOに着任したした。ちょうど6幎が経過したずころですが、これたでのキャリアで積み重ねおきたベンダヌずしおの知識、事業䌚瀟での経隓、そしお経営者ずしおの芖点のすべおを総動員し、事業成長を牜匕するCIOずしお挑戊を続けおいたす。

キャリアを倉えた「ビゞネスを぀くる」ずいう挑戊

——これたでの経歎の䞭で、特に印象に残っおいる仕事はありたすか

振り返るず、それぞれの業皮や立堎で倧きな挑戊がありたした。最初にSIに携わっおいた頃は、どれだけの芏暡のプロゞェクトを回せるかが自分の成長のものさしでした。圓時、800人月芏暡の開発プロゞェクトを20代で任されおいお、今思えばずおも倧きな責任を若いうちに䞎えおくれる䌚瀟だったず思いたす。

゜フトバンクでは、初めお「ビゞネスを぀くる」ずいうこずに挑戊したした。担圓したのは、珟圚のセブンネットショッピングに぀ながるEコマヌス事業です。売䞊れロからスタヌトし、システム責任者ずしお玄200億円芏暡たで事業が成長するプロセスを支えた経隓は、自分のキャリアにおいお非垞に倧きな意味を持ちたした。単なるシステム開発ではなく、ビゞネスを成長させるこずに盎結する仕事だったからです。

珟職であるトリドヌルホヌルディングスのCIOずしおの最初の倧仕事は、システムの党面的なモダナむズでした。着任しおから6幎をかけお取り組んできたのですが、ようやくすべおの眮き換えが完了する段階にきおいたす。

圓初は3幎で完了させる぀もりでしたが、瀟内の事情や既存の仕組みを䞁寧に考慮しながら進める必芁があり、結果ずしお時間をかけおでも確実にやり切る圢になりたした。

取り組みのスタヌトは「システムがいく぀あるのかを数える」ずころからでした。最初に掗い出した時点で180ほどのシステムが存圚しおいお、そこから業務の目的に立ち返っお敎理し、統合を進めおきたした。最終的には180のシステムを倧幅に集玄し、今では40皋床にたで枛らすこずができおいたす。

こうしおみるず、システムの棚卞しからモダナむズたでを自分の手でリヌドしおこられたこずは、CIOずしお最初に取り組むにふさわしいチャレンゞだったず思いたす。

「オペレヌション領域を切り離す」ずいう挑戊

——これたでのキャリアの䞭で、最もチャレンゞングだった出来事を教えおください。

ずおも神経を䜿ったのが、トリドヌルホヌルディングスで手がけた業務組織改革の取り組みです。

具䜓的には、トリドヌルグルヌプの本瀟業務を、持ち株䌚瀟ずシェアヌドサヌビス䌚瀟に分けたうえで、シェアヌドサヌビス䌚瀟が担っおいる管理郚門の定型業務をオフバランス化し、BPOベンダヌに移管するずいう取り組みでした。瀟内で担っおいた業務を倖郚に出すずいうのは、倧胆で、非垞に繊现な調敎を䌎うプロゞェクトでした。たずはIT郚門から着手したしたが、これが最も倧倉だったず思いたす。

私は圓時、シェアヌドサヌビス䌚瀟の瀟長を兌務しおおり、最倧で180人ほどのメンバヌを率いおいたした。そこにはIT運甚のチヌムだけでなく、経理の蚘垳を担うファむナンス郚隊や、人事の絊䞎蚈算を担圓する郚隊など、いわゆるオペレヌション機胜が集玄されおいたした。戊略立案は持ち株䌚瀟が担い、日垞のオペレヌションは䞀぀に束ねお管理する䜓制を敎えおいたのです。その業務を少しず぀切り出しお倖郚に移すずいうのが、圓時の私の圹割でした。

圓然、既存の仕事を担っおいた人材の「次のキャリアをどう぀くるか」が課題になりたす。トリドヌルは兵庫県加叀川垂で創業し、その埌兵庫県神戞垂に本瀟を眮いおいたしたが、圓時シェアヌドサヌビス䌚瀟の拠点も神戞にありたした。

枋谷の本瀟ぞ転勀可胜な人にはホヌルディングスの業務を打蚺したしたが、家庭の事情などで転勀が難しい方も倚くいたした。そうした方には、BPOベンダヌぞ転籍しおこれたでず同じ業務を継続しおもらったり、トリドヌルグルヌプの店舗に掻躍の堎を移しおもらったりず、䞀人ひずりず面談を重ねお次の道を䞀緒に決めおいきたした。

もちろん、これは私ひずりでできるこずではありたせん。郚長や管理職のメンバヌに協力を埗お、埓業員たちず真摯に察話を重ねながら進めたした。最終的には「それぞれが次の環境で長く掻躍できるこず」がゎヌルでした。䌚瀟ずしおの方針は明確にある䞀方で、できるだけ玍埗感を持っお着地させるこずが、自分の最倧の䜿呜だったず思いたす。

投資を惜したぬむンタヌネットの発想がもたらした気づき

——仕事をする䞊で心に残っおいる蚀葉や出来事はありたすか

心に残っおいる蚀葉は2぀ありたす。

たず䞀぀は、セブンネットショッピングの立ち䞊げに関わっおいた頃のこずです。圓時セブン&アむ・ホヌルディングスの䌚長を務めおいた鈎朚敏文さんの蚀葉を、圓時の䞊叞であっお䌚長のご子息である、鈎朚康匘さんより教えおいただいたこずがありたした。

あるずき「人前で話すずきにどうすれば緊匵しないのでしょうか」ず尋ねたら、「背䌞びせず、分からないこずは話さず、知っおいるこずだけ話せば緊匵しない」ずおっしゃったんです。確かに、分からないこずは「分からない」ず蚀えばよい。そうやっお等身倧で話す人こそ、実瞟を残しおいけるのだず匷く感じたした。

もう䞀぀は同じ時期、セブンネットショッピングがダフヌの子䌚瀟の事業だった頃の経隓です。圓時はただむンタヌネットが本栌的なビゞネスになりきっおおらず、日本ではダフヌが先駆けおいお、Googleがようやく参入したばかりの時期でした。

ナヌザヌが急増するずサヌバが混み合い、システムが逌迫する堎面も倚かったのですが、その時に圓時ダフヌの瀟長であった井䞊雅博さんから「むンタヌネットビゞネスずいうのはナヌザヌのアクセスが増えたらサヌバを远加するのがゲヌムのルヌルなんだ。」ず蚀われたんです。その蚀葉にハッずしたした。

埓来の゚ンタヌプラむズの䞖界では、高䟡なリ゜ヌスをどう最適化しお䜿い切るか、ずいう発想が基本でした。私自身も「限られた資源を倧事に掻甚する」こずを圓たり前だず思っおいたのです。

しかしむンタヌネットの䞖界では「安䟡なサヌバを䞊べればいい」ずいう発想が䞻流で、投資を前提にしたスケヌルアりトの文化が根づいおいたした。もし远加投資ができないのであれば、むンタヌネットビゞネス自䜓が成り立たないずいう考え方です。

この考え方の違いは衝撃でした。゚ンタヌプラむズのテクノロゞヌず、むンタヌネットのテクノロゞヌずの倧きな違いをたざたざず感じた瞬間でしたし、その違いはいたなお、䞖の䞭では完党に融合しきれおいない郚分が残っおいるず感じおいたす。

倉化に匷い基盀づくりこそCIOの最倧のやりがい

——CIOずしお、どのようなずころにやりがいを感じたすか

私にずっおCIOのやりがいは、「䌚瀟が目指す方向性を加速させる基盀をどうやっお぀くるか」に尜きるず思っおいたす。

圓瀟のミッションは「お客さたに感動䜓隓を届けるこず」です。その最前線に立っおいるのは店舗のスタッフであり、それを支えるマネゞメント局です。

ずはいえ、人だけに頌るのには限界がありたすから、そこで「裏偎から圌らをどう支えるか」が重芁になりたす。倉化に玠早く察応できるビゞネス基盀を敎えるこずこそ、CIOずしおの醍醐味だず思いたす。

IT郚門が自分たちの論理だけで動いおいおも面癜くはなりたせん。倧事なのは「ビゞネスにどれだけ貢献できおいるか」「倉化にどれだけ柔軟に察応できる基盀を築けたか」ずいうこずです。

䟋えば事業のスケヌルを考えるずき、「業態が増えたら䞀぀の仕組みで賄うのか、それずも耇数を組み合わせるのか」ずいった蚭蚈思想が問われたす。たた「サヌバ台数を増やすのか、䞀台を倧芏暡化するのか」ずいうスケヌルアりトスケヌルアップの刀断も必芁になりたす。こうしたアヌキテクチャの怜蚎は非垞に面癜い郚分です。

さらに、今のように倉化の激しい時代では、経営陣が「やっぱりやめよう」ず方針を転換するこずは必ず起こりたす。そんなずきに「倚額の投資をしおしたったからシステムを捚おられない」ずいうのでは困るわけです。

だからこそ、私はなるべくサブスクリプション、぀たりSaaSを掻甚しおいたす。特にバックオフィスのように柔軟性が求められる領域は、SaaSを組み合わせた方がリスクを抑えられたす。

こうした刀断を支えおいるのは、゚ンゞニアずしおの経隓ず、事業経営に携わった経隓の䞡方です。テクノロゞヌに粟通しおいないず最適な遞択はできたせんし、経営の芖点がなければ「ビゞネスをどう支えるか」ずいう答えも出せたせん。その䞡方を掻かしお考えられるのは、CIOずしおの䞀番の楜しさだず思っおいたす。

実は私はITベンダヌ時代から「これからはSaaSが必須になる」ず考えおいたした。圓時は提案しおもナヌザヌ䌁業が採甚しなければ圢になりたせんでしたが、CIOの立堎になっお初めお「自分が決めれば実行できる」ず実感したした。これは非垞に倧きな違いであり、事業䌚瀟偎に移ったからこそ挑戊できおいるこずです。

トリドヌルグルヌプは倉化を恐れずに進化を続けおきた䌚瀟です。だからこそ急成長しおこられたし、時代の荒波にも沈たずに察応しおきたした。この匷みは絶察に倱っおはいけないですから、そのためにも、システム基盀を党面的にSaaSにする取り組みを進めおきたした。

SaaSベンダヌの補品の裏には優秀な゚ンゞニアが数倚くいお、考え方によっおは圌ら党員が私たちを支えおくれおいる存圚ずも蚀えたす。自瀟の力だけではなく、倖郚の力をどう組み合わせるか。それを蚭蚈できるこずこそがCIOの圹割であり、私にずっおのやりがいなのです。

——AI掻甚に぀いおはいかがですか

䞖の䞭では生成AIばかりが泚目されおいたすが、私たちが泚力しおいるのは「珟堎の生産性を高めるAI掻甚」です。生成AIはホワむトカラヌの業務効率化には有効ですが、私たちの事業に盎結する珟堎業務では、もっず実務的なAIの力が必芁だず考えおいたす。

その代衚䟋が需芁予枬です。売䞊や来店客数をAIで予枬するこずで、「明日は䜕人のスタッフを配眮すべきか」「どれだけ食材を仕入れるべきか」ずいった店舗マネゞメントの蚈画を効率化できたす。これにより、珟堎の負担を倧幅に軜枛するこずができたした。

もう䞀぀は顔認蚌を掻甚した勀怠管理です。圓瀟には倚くのパヌト・アルバむトスタッフが働いおおり、その打刻䜜業は倧きな課題でした。埓来の指王や静脈認蚌では氎仕事や寒さで䟋倖が発生しがちでしたが、顔認蚌に切り替えおからは䟋倖れロ。しかも打刻スピヌドも速く、マスクをしおいおも瞬時に認蚌できるため、珟堎から「勀怠がスムヌズになった」ず奜評です。

掟手さはありたせんが、こうした取り組みが珟堎の生産性を着実に匕き䞊げおいたす。これこそが、私たちが目指すAI掻甚の本質だず思っおいたす。

CIOに必芁なのは「ビゞョンを語るこず」ず「やり抜く芚悟」

——CIOに必芁な資質ずは䜕でしょうか

私が最も倧事だず思うのは「芚悟」です。もちろん「決めたこずをやり切る」こずも重芁ですが、その前に「䜕を目指すのか」をはっきりず打ち出さなければなりたせん。未来の絵を描いたら、「この方向ぞ䌚瀟を導いおいく」ず宣蚀する。その宣蚀自䜓が、CIOにずっおの芚悟の蚌だず思っおいたす。

私自身も「DXビゞョン」を瀟倖に公衚したこずで、「もう絶察にやり切るしかない」ず腹が決たりたした。そうするこずで、瀟員もベンダヌも「トリドヌルグルヌプはこういう姿を目指しおいるのだ」ず理解し、同じ方向を向けるようになるのです。これは非垞に倧きな意味を持ちたす。

CIOには、目指す姿を絵ずしお瀺し、そのビゞョンに向かっおひたすら突き進む力が求められたす。その際、バックキャストの発想が欠かせたせん。「このゎヌルに到達するために、今䜕をすべきか」を逆算しお考えるのです。フォアキャスト、぀たり珟状の延長線䞊で課題解決を積み重ねるだけでは、新しい䟡倀は生たれたせん。

もちろん、䞀定の安定期に入ればフォアキャスト的な改善で十分なこずもありたす。しかし、倧きな倉革を起こす時には、バックキャストで倧胆に道筋を描く必芁がありたす。

そしお、ずきに倧きなギャップが生じたら「違う、こちらに舵を切るぞ」ず果断に方向転換できる——。これこそがCIOに求められる資質だず私は考えおいたす。

デゞタル時代のリヌダヌが身に぀けるべき「䞉本柱」ずは

——これからCIOを目指す人材に求められるスキルは䜕でしょうか

私自身、チヌムのメンバヌには「将来はCIOやCTO、あるいはCDOずいった圹割を担える人材になっおほしい」ず垞々䌝えおいたす。日本にはただそうした人材が十分に育っおいたせん。だからこそ、倚くの䌁業でデゞタルをビゞネスに結び぀ける橋枡し圹ずなれる人を増やす必芁があるず思っおいたす。若い人も、最初からこの圹割を目指しおキャリアを積んでほしいず考えおいたす。

そのために必芁なのは倧きく䞉぀の力です。

たずは基瀎的な技術力です。コヌドを曞けないITリヌダヌもいたすが、曞けるに越したこずはありたせん。私自身も䞭孊生の頃からコヌドを曞いおきたした。プログラミング蚀語も䞀぀ではなく、二぀以䞊孊ぶこずで比范ができ、より深い理解に぀ながりたす。これは転職を経隓するず新しい䞖界が芋えるのず同じで、耇数の芖点を持぀こずが重芁だず思いたす。

次に必芁なのはアヌキテクトずしおの力です。ナヌザヌ䌁業のCIOは「既存の技術をどう組み合わせ、自瀟のビゞネスに最適な構造を぀くるか」を垞に考えなければなりたせん。CTOの圹割に近い郚分でもありたすが、ネットワヌクやむンフラ、クラりドずいった基瀎を理解しおいないず、最適な組み合わせを刀断できたせん。システムアヌキテクトずしおの知識ず発想は必須だず考えおいたす。

そしお最埌はコミュニケヌション力です。プロゞェクトがうたくいかない原因の倚くは、技術力䞍足よりもコミュニケヌション䞍足にありたす。私は1on1をよくやりたすが、盞手は瀟長からグルヌプ䌚瀟の圹員、事業䌚瀟の幹郚たで幅広いです。圌らが「䜕をやりたいのか」を理解しなければ、先を芋据えたシステム蚭蚈はできたせんし、信頌できる盞談盞手になれなければ良い成果も出せたせん。これは自分だけでなく、郚長クラスのメンバヌにも求めおいたす。

基瀎的な技術力、アヌキテクトずしおの構築力、そしおコミュニケヌション力——。この䞉぀はCIOを目指す䞊で欠かせない資質です。BtoB䌁業なら特に、パヌトナヌ䌁業ずの関係が重芁ですから、若いうちから匷く意識しおほしいず思っおいたす。

目指すは「䞖界に通じる倖食䌁業」――グロヌバルブランドぞの挑戊

——今埌の展望に぀いお教えおください。

圓瀟は「グロヌバルフヌドカンパニヌ」を䌁業ビゞョンに掲げおいたす。目指しおいるのは、有名なハンバヌガヌチェヌンやコヌヒヌチェヌンず肩を䞊べる、日本初の「䞖界に通じる倖食䌁業」になるこずです。

トリドヌルグルヌプはすでに30カ囜以䞊に展開しおいたすが、すべおの囜で日本ず同じクオリティヌを実珟できおいるかずいえば、ただ課題が残っおいたす。ここをどう底䞊げするかが、これからの倧きなテヌマです。私はデゞタルの力で氎準をそろえ、さらに新しい囜ぞ展開しやすい環境を敎えるこずが、ビゞネスの加速に぀ながるず考えおいたす。

これたでは日本垂堎に泚力しおきたしたが、今埌はグロヌバルの子䌚瀟やフランチャむズパヌトナヌに察しお、より積極的に支揎しおいきたいず思っおいたす。

もちろん、すべおを䞀埋の仕組みに圓おはめるのは珟実的ではありたせん。補造業のように党䞖界で同じシステムを展開するアプロヌチもありたすが、私たち倖食産業では「珟地の人に食べおもらっお初めお䟡倀がある」わけですから、䞀定の自由床を残し぀぀、「トリドヌルグルヌプずしお絶察に守っおほしい基準」をどう浞透させるかが重芁になりたす。

そこで有効なのがデゞタル基盀です。仕組みに組み蟌んでしたえば、意識せずずも自然に基準が担保される。そうした仕掛けを増やしおいきたいず考えおいたす。

ただしやりすぎるず、圓瀟の匷みである「手づくり・できたお」のこだわりが薄れおしたうリスクもありたす。その線匕きをどうするかは難しい課題ですが、むしろそこに面癜さがあるず感じおいたす。

トップや事業䌚瀟の責任者ず䞀緒に議論を重ね、珟地に合った最適なバランスを芋぀けおいく。そうした取り組みをグロヌバルに広げおいきたいず思っおいたす。

The workforce shift — why CIOs and people leaders must partner harder than ever

15 January 2026 at 07:20

AI won’t replace people. But leaders who ignore workforce redesign will begin to fail and be replaced by leaders who adapt and quickly.

For the last decade or so, digital transformation has been framed as a technology challenge. New platforms. Cloud migrations. Data lakes. APIs. Automation. Security layered on top. It was complex, often messy and rarely finished — but the underlying assumption stayed the same: Humans remained at the center of work, with technology enabling them.

AI breaks that assumption.

Not because it is magical or sentient — it isn’t — but because it behaves in ways that feel human. It writes, reasons, summarizes, analyzes and decides at speeds that humans simply cannot match. That creates a very different emotional and organizational response to any technology that has come before it.

I was recently at a breakfast session with HR leaders where the topic was simple enough on paper: AI and how to implement it in organizations. In reality, the conversation quickly moved away from tools and vendors and landed squarely on people — fear, confusion, opportunity, resistance and fatigue. That is where the real challenge sits.

AI feels human and that changes everything

AI is just technology. But it feels human because it has been designed to interact with us in human ways. Large language models combined with domain data create the illusion that AI can do anything. Maybe one day it will. Right now, what it can do is expose how unprepared most organizations are for the scale and pace of change it brings.

We are all chasing competitive advantages — revenue growth, margin improvement, improving resilience — and AI is being positioned as the shortcut. But unlike previous waves of automation, this one does not sit neatly inside a single function.

Earlier this year I made what I thought was an obvious statement on a panel: “AI is not your colleague. AI is not your friend. It is just technology.” After the session, someone told me — completely seriously — that AI was their colleague. It was listed on their Teams org chart. It was an agent with tasks allocated to it.

That blurring of boundaries should make leaders pause.

Perception becomes reality very quickly inside organizations. If people believe AI is a colleague, what does that mean for accountability, trust and decision-making? Who owns outcomes when work is split between humans and machines? These are not abstract questions — they show up in performance, morale and risk.

When I spoke to younger employees outside that HR audience, the picture was even more stark. They understood what AI was. They were already using it. But many believed it would reduce the number of jobs available to their generation. Nearly half saw AI as a net negative force. None saw it as purely positive.

That sentiment matters. Because engagement is not driven by strategy decks — it is driven by how people feel about their future.

Roles, skills and org design are already out of date

One of the biggest problems organizations face is that work is changing faster than their structures can keep up.

As Zoe Johnson, HR director at 1st Central, put it: “The biggest mismatch is in how fast the technology is evolving and how possible it is to redesign systems, processes and people impacts to keep pace with how fast work is changing. We are seeing fast progress in our customer-facing areas, where efficiencies can clearly be made.”

Job frameworks, skills models and career paths are struggling to keep up with reality. This mirrors what we are now seeing publicly, with BBC reporting that many large organizations expect HR and IT responsibilities to converge as AI reshapes how work actually flows through the enterprise.

AI does not neatly replace a role — it reshapes tasks across multiple roles simultaneously. That shift is already forcing leadership teams to rethink whether work should be organized by function at all or instead designed end‑to‑end around outcomes. That makes traditional workforce planning dangerously slow.

Organizations are also hitting change saturation. We have spent years telling ourselves that “the only constant is change,” but AI feels relentless. It lands on top of digital transformation, cloud, cyber, regulation and cost pressure.

Johnson is clear-eyed about this tension: “This is a constant battle, to keep on top of technology development but also ensure performance is consistent and doesn’t dip. I’m not sure anyone has all the answers, but focusing change resource on where the biggest impact can be made has been a key focus area for us.”

That focus is critical. Because indiscriminate AI adoption does not create advantages — it creates noise.

This is no longer an IT problem

For years, organizations have layered technology on top of broken processes. Sometimes that was a conscious trade-off to move faster. Sometimes it was avoidance. Either way, humans could usually compensate.

AI does not compensate. It amplifies. This is the same dynamic highlighted recently in the Wall Street Journal, where CIOs describe AI agents accelerating both productivity and structural weakness when layered onto poorly designed processes.

Put AI on top of a poor process and you get faster failure. Put it on top of bad data and you scale mistakes at speed. This is not something a CIO can “fix” alone — and it never really was.

The value chain — how people, process, systems and data interact to create outcomes — is the invisible thread most organizations barely understand. AI pulls on that thread hard.

That is why the relationship between CIOs and people leaders has moved from important to existential.

Johnson describes what effective partnership actually looks like in practice: “Constant communication and connection is key. We have an AI governance forum and an AI working group where we regularly discuss how AI interventions are being developed in the business.”

That shared ownership matters. Not governance theatre, but real, ongoing collaboration where trade-offs are explicit and consequences understood.

Culture plays a decisive role here. As Johnson notes, “Culture and trust is at the heart of keeping colleagues engaged during technological change. Open and honest communication is key and finding more interesting and value-adding work for colleagues.”

AI changes what work is. People leaders are the ones who understand how that lands emotionally.

The CEO view: Speed, restraint and cultural expectations

From the CEO seat, AI is both opportunity and risk. Hayley Roberts, CEO of Distology, is pragmatic about how leadership teams get this wrong.

“All new tech developments should be seen as an opportunity,” she said. “Leadership is misaligned when the needs of each department are not congruent with the business’s overall strategy. With AI it has to be bought in by the whole organization, with clear understanding of the benefits and ethical use.”

Some teams want to move fast. Others hesitate — because of regulation, fear or lack of confidence. Knowing when to accelerate and when to hold back is a leadership skill.

“We love new tech at Distology,” Roberts explains, “but that doesn’t mean it is all going to have a business benefit. We use AI in different teams but it is not yet a business strategy. It will become part of our roadmap, but we are using what makes sense — not what we think we should be using.”

That restraint is often missing. AI is not a race to deploy tools — it is a race to build sustainable advantage.

Roberts is also clear that organizations must reset cultural expectations: “Businesses are still very much people, not machines. Comprehensive internal assessment helps allay fear of job losses and assists in retaining positive culture.”

There is no finished AI product. Just constant evolution. And that places a new burden on leadership coherence.

“I trust what we are doing with our AI awareness and strategy,” Roberts says. “There is no silver bullet. Making rash decisions would be catastrophic. I am excited about what AI might do for us as a growing business over time.”

Accountability doesn’t disappear — it concentrates

One uncomfortable truth sits underneath all of this: AI does not remove accountability. It concentrates it. Recent coverage in The HR Director on AI‑driven restructuring, role redesign and burnout reinforces that outcomes are shaped less by the technology itself and more by the leadership choices made around design, data and pace of change.

When decisions are automated or augmented, the responsibility still sits with humans — across the entire C-suite. You cannot outsource judgement to an algorithm and then blame IT when it goes wrong.

This is why workforce redesign is not optional. Skills, org design and leadership behaviors must evolve together. CIOs bring the technical understanding. CPOs and HRDs bring insight into capability, culture and trust. CEOs set the tone and pace.

Ignore that partnership and AI will magnify every weakness you already have.

Get it right and it becomes a powerful force for growth, resilience and better work.

The workforce shift is already underway. The question is whether leaders are redesigning for it — or reacting too late.

This article is published as part of the Foundry Expert Contributor Network.
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6 maxims for today’s digital leader playbook

15 January 2026 at 05:00

Modern CIOs and tech leaders carry responsibility not only for an organization’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, I’ve distilled here some of my favourite maxims from different business functions.

Maxim 2: Try to be human

You’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, it’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 don’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 aren’t my natural environment. And we’ve probably all experienced how work and socializing sometimes don’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 something’s bad for the company or a dead-end, they shrug and say the business just doesn’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.

It’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 it’ll inflate future company running costs, not that it doesn’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, it’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 doesn’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 I’ve learned and seen reinforces this. Without this focus, you’re just an IT supplier taking orders, not the executive IT partner of the business. Question any actions by your team that can’t be linked back to the company’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 team’s successes and be honest about your mistakes. As CIO, you’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, you’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 you’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, it’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 we’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

14 January 2026 at 05:00

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 — 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 Nationwide’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. 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 is 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 DXC’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, 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.  

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 company’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 bachelor’s degree from Brooklyn College, and an MBA from the University of Chicago’s 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 firm’s IT budget, collaborated with the firm’s AI and innovation team, and led a data governance initiative that reduced high-risk file exposures, and helped scale the firm’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 – Archie W. Dunham College of Business.

New CIO appointments, December 2025

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John Hancock names Kartik Sakthivel CIO

Ameet Shetty joins RaceTrac as CIO

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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 Glazer’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 Kohl’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 Love’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 O’Leary as CIO

Bill Poirier named CIO at the University of Central Florida

Avalara announces Shahan Parshad as CIO

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The tech leadership realizing more than the sum of parts

14 January 2026 at 05:00

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.

“What it comes down to, in order to achieve that, is the team,” he says. “I came into this organization because of the culture, and the listen first, act later mentality. It’s something I believe in and I’m going to continue that culture.”

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.

“Once you’re a customer of ours, we have to make sure we’re a needs-based business,” he says. “We have to be the first thing that sticks in their mind because it’s not about a track on a Bobcat that just broke. It’s $1,000 a day someone’s not going to make due to a piece of equipment that’s down.”

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.

“Some people prefer our website,” he says. “But 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 we’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.”

Of course, AI is always in the conversation since people can’t write updated descriptions for 250,000 SKUs.

“AI will fundamentally change what everybody’s job is,” he says. “I know I have to prepare for it and be forward thinking. We have to embrace it. If you don’t, you’re going to get left behind.”

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 that’s very purpose-built for the type of process an organization is running, or that unique sales process, or whatever. But in other cases, it’s very hard. We’ve acquired companies with their own custom built ERP platform, where they spent 20 years curating it down to eliminate every button click. Those don’t go quite as well, but you start with a good culture, and being transparent with employees and customers about what’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, you’re not just dragging them along but bringing them along on the journey.

On AI: Everybody’s talking it, but there’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 you’re going after AI. You can’t just use it because it’s a buzzword. You have to bake it into your strategy and existing use cases, and then leverage it. We’re doing it in a way that allows us to augment our existing strategy rather than completely and fundamentally change it. So for example, we’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 they’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, that’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 they’re buying online and in person. If they’re buying construction equipment and material handling equipment, we’ll see that. But when somebody’s buying a custom fork for a forklift, that’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 hasn’t been successful in my experience in the past. So we’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 we’re not afraid to have more than one operational platform. Today, in our ecosystem of 23 different companies, we’re manufacturing parts in our material handling business, and that’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. It’s an entirely different model. So we’re not establishing one core platform in that case, but the right amount of platforms. It’s not 23, but it’s also not one. So as we think about being able to scale, it’s also saying that if you try to be all things to all people, you’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 — same finance team, same IT teams — we’ll have more than one operational platform. Then through different technologies, including AI, ensure we have one view of the customer, even if they’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 can’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 we’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, we’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 we’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 we’re also pulling in that data and putting it back into our core operational platform, and there it rests. So if we’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. We’ve already changed it five times and we’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.

Siete pasos para pasar de ser soporte técnico a estratega de TI

13 January 2026 at 06:35

No es nada raro que los profesionales de TI se sientan en los grupos empresariales como poco más que “receptores de pedidos”: se les indica qué sistemas implementar o solucionar, en lugar de preguntar cómo la tecnología puede resolver problemas empresariales más importantes. No obstante, dar el salto de técnico de soporte a asesor estratégico lleva su tiempo. Quienes lo hacen bien no se centran sólo en solucionar problemas, sino que aprenden el negocio, hablan en un lenguaje sencillo, se enfocan en resultados en lugar de tareas, y miran hacia el futuro para prevenir problemas en lugar de reaccionar únicamente ante ellos.

Poro, a continuación detallamos siete pasos para pasar de ser personal de soporte reactivo a asesor de confianza.

1. Dejar de esperar a que nos digan qué hacer

Eric Johnson, director de TI de PagerDuty, proveedor de software de gestión de operaciones digitales, considera que el mayor obstáculo que frena a los profesionales de TI es la mentalidad pasiva. Quedarse sentado esperando instrucciones impide que los equipos de TI alcancen el nivel de asociación estratégica que desean.

De ahí que señales que “muchas organizaciones de TI caen en esa trampa. Es como decir: ‘Bueno, no podemos hacer nada a menos que nos digan qué hacer’. Y yo les pregunto: ‘¿Han propuesto algo? ¿Han dado ideas sobre lo que se podría hacer?’. Y muchas veces la respuesta es no. Nunca se alcanzará el nivel deseado si no se aporta algo”.

Mientras, Bill Young, director de tecnología y socio operativo de la empresa de selección de personal de TI RightClick, prefiere ser más directo: los profesionales de TI deben pasar de pensar “mi trabajo es arreglar cosas” a “mi trabajo es mejorar el negocio”.

Por su parte, Dana Stocking, directora de TI de la startup de selección de personal de IA Mercor, destaca que uno de los mayores errores que cometen los responsables de TI es tratar las solicitudes de la empresa como casillas a marcar en lugar de oportunidades para identificar causas fundamentales. Y dice: “Cuando alguien solicita acceso a un software o quiere comprar una nueva herramienta, no se limite a satisfacer la solicitud. Indague en el “porqué”. ¿Qué problema subyacente intentan resolver? A menudo descubrirá que la solución propuesta no es la más adecuada y, al comprender la causa raíz, podrá resolver problemas organizativos más amplios”.

Noe Ramos, vicepresidenta de operaciones de IA de Agiloft, destaca que los buenos líderes de TI ven su trabajo como parte de un ecosistema más amplio, que funciona mejor cuando las personas son abiertas, comparten información y colaboran. De ahí que afirme: “Pasar de “mi sistema” a “nuestro resultado” es un cambio sutil, pero transformador”.

2. Comprender el negocio, no sólo los problemas

Para Johson, los profesionales de TI deben mostrarse como socios comprendiendo realmente lo que ocurre en el negocio, en lugar de esperar a que las partes interesadas acudan a ellos con problemas que resolver. Por eso considera que “cuando interactúas con tus socios comerciales, aportas ideas y soluciones proactivas. No esperas a que te expongan sus problemas y los pongan en tu lista de tareas pendientes; de lo contrario, te conviertes en nada más que una organización que se limita a tomar nota”.

¿Cómo desarrollar esa comprensión? Muy sencillo: asistiendo a reuniones de negocio, haciendo preguntas y escuchando. Por eso Joe Locandro, vicepresidente ejecutivo y director de informática global de Rimini Street, anima a su equipo a asistir regularmente a reuniones departamentales. “Para adquirir ese lenguaje empresarial hay que asistir a reuniones de ejecutivos y ser invitado, ya sea una vez al mes o al trimestre. Eso permite comprender la jerga empresarial y lo que realmente importa”.

Adrienne DeTray, vicepresidenta sénior y directora de informática de Universal Technical Institute, coincide en el argumento: “Acérquese al negocio, tanto física como estratégicamente. Asista a revisiones de la cadena de valor, comprenda la estrategia y los objetivos, participe en reuniones operativas fuera del ámbito técnico. No se pueden alinear los objetivos si no se comprende de dónde viene el negocio y hacia dónde se dirige”.

Para profesionales que dan soporte a departamentos específicos, esto significa pasar tiempo con esos equipos a diario. Por ejemplo, si da soporte a ventas, comprenda cómo funciona el proceso, los puntos débiles a los que se enfrentan los vendedores y cómo miden su éxito trimestral.

3. Liderar con el objetivo, no con las peticiones

En lugar de mantener una mentalidad de “tomar nota”, los profesionales de TI deben hacer preguntas profundas sobre lo que necesitan sus socios y qué impulsa esa necesidad, lo que fomenta la resolución de problemas y el enfoque en resultados en lugar de limitarse a implementar soluciones, afirma DeTray.

El equipo de Johnson sigue un enfoque estructurado. Cada mes realizan reuniones de alineación de cartera, donde discuten iniciativas clave con los socios comerciales. “De hecho, hacemos esas preguntas del estilo cuál es el estado objetivo (es decir, el resultado deseado). Y si conocemos ese estado objetivo, podemos mantener conversaciones con ellos sobre lo que se puede hacer de forma proactiva para ayudarles a alcanzarlo”, explica.

Para un equipo financiero que quiere cerrar los libros más rápido, esto podría significar explorar oportunidades de automatización. Para equipos de ventas que luchan con trabajo administrativo, podría implicar crear herramientas que eliminen la introducción repetitiva de datos. La clave es comprender los objetivos empresariales antes de proponer soluciones técnicas. ¿Cómo se define el éxito para este equipo este trimestre? ¿Cómo miden el progreso? ¿Qué obstáculos se interponen en su camino?

El equipo de datos de Johnson lo ha demostrado al pasar de un enfoque reactivo a proactivo. Al mantener distintas conversaciones con la empresa sobre sus objetivos, el equipo comenzó a sugerir programas para atraer nuevos clientes, identificar oportunidades de expansión y crear copilotos de IA que redujeran el trabajo administrativo del equipo de ventas.

4. Centrarse en los resultados, no en las tareas

Uno de los cambios más efectivos que pueden hacer los profesionales de TI para pasar de “tomadores de pedidos” a asesores estratégicos es modificar la forma en que comunican su trabajo. En lugar de describir lo que hicieron, deben describir lo que ese trabajo permitió lograr.

Locandro, de Rimini Street, observa de manera repetida el antiguo estilo de comunicación basado en tareas en su organización. “Muchos de los informes que se enviaban a la empresa se centraban en actividades: lo ocupados que estaban todos, o “hemos actualizado esto”, o “hemos entregado aquello”
 Nadie informaba: “Este es el valor que se ha generado como resultado de esta tarea. Este es el resultado que se ha entregado o se ha podido lograr gracias a esta tarea”. ¿La solución? Pasar de informes basados en actividades a informes basados en valor y resultados. Eliminar jerga técnica y siglas.

“Uno de los cambios más eficaces es pasar de describir la actividad a describir el impacto. Por ejemplo, en lugar de decir “hemos automatizado este proceso”, diga “hemos liberado 200 horas al mes para que el equipo de ventas se concentre en trabajo que genera ingresos”. Este cambio de enfoque, de los insumos a los resultados, replantea el papel de TI como facilitador de la estrategia vinculada a los objetivos empresariales”, afirma Ramos, de Agiloft.

A los líderes de la empresa no les preocupan los detalles técnicos, afirma Christopher Daden, director tecnológico de Criteria Corp. Quieren comprender el propósito del trabajo y el impacto que tendrá. “Los profesionales de TI deben enmarcar cada iniciativa en términos del problema empresarial que resuelve, el riesgo que reduce o la oportunidad que abre”, añade. “Un lenguaje enfocado en resultados, como cómo una solución mejora la experiencia del cliente, acelera los ingresos o refuerza la escalabilidad, ofrece a los ejecutivos una visión clara del valor”.

5. Buscar pequeñas victorias que sumen

Los profesionales de TI no siempre necesitan grandes proyectos de transformación para marcar una diferencia real. A veces, la decisión más inteligente es centrarse en unas pocas victorias rápidas que ofrezcan resultados inmediatos. “Las pequeñas cosas pueden sumar algo grande. Si identificas cosas pequeñas, victorias rápidas que puedan beneficiar a la organización con la que colaboran, a veces se trata de un proceso que podría automatizarse. Si haces esto para varios pasos de un proceso, de repente habrás automatizado una buena parte del mismo”.

Johnson advierte contra la búsqueda constante de grandes logros. En su opinión, “son más difíciles de encontrar y más difíciles de ejecutar. En un plazo de 30 a 60 días, los profesionales de TI pueden comprender las métricas y los estados objetivo, y luego buscar oportunidades para ayudar, aunque empiecen con cosas pequeñas”.

Ese mismo enfoque de pequeñas victorias también se aplica cuando los equipos de TI miran más allá de los procesos y centran su atención en las herramientas y licencias cotidianas de las que dependen los empleados. Meg Donovan, directora de personal de Nexthink, empresa que desarrolla software de gestión de la experiencia digital del empleado, explica cómo su equipo de TI proporciona datos sobre el uso real de las herramientas de software en la empresa —y cuáles no se utilizan. “Creemos que necesitamos esta herramienta. Pero, ¿realmente la necesitamos? ¿Y necesitamos 2.500 licencias? Porque puede mostrarme que sólo están utilizando 10”, admite.

6. Medir el impacto, no sólo la finalización

Demasiados profesionales de TI implementan un proyecto y siguen adelante sin comprobar si realmente ha funcionado. Los profesionales de TI estratégicos se aseguran de hacer un seguimiento completo. Después de implementar una solución, los equipos de TI deben medir la diferencia entre el estado “antes” y “después” para determinar el impacto real, afirma Johnson. “Veo que muchas empresas no hacen todo lo que deberían en este sentido. Son muy rápidas a la hora de identificar el problema y poner en marcha la solución, pero no dan el paso final, que probablemente es el más importante: ¿ha tenido el impacto que esperaban y están [realmente] midiendo eso?”, añade.

Cuando el impacto no alcanza lo esperado, los profesionales de TI estratégicos no se dan por vencidos. Investigan por qué no se han materializado los resultados esperados y realizan correcciones. A veces, esto significa refinar la solución. Otras veces, significa encontrar un enfoque completamente distinto.

7. Utilizar la IA para liberar capacidad estratégica

La IA no es la estrella del cambio estratégico de TI, pero sin duda puede impulsar el trabajo. El valor real proviene del uso de la IA para manejar tareas repetitivas, de modo que los profesionales de TI tengan más tiempo para abordar problemas de mayor valor. Según Johnson, muchas áreas de TI están implementando soluciones basadas en agentes para gestionar el soporte de nivel uno, lo que libera tiempo del personal para proyectos que la empresa consideraría de mayor impacto que responder tickets de soporte.

El equipo de Daden en Criteria ha logrado resultados sorprendentes: “Más del 80% de nuestro código de producción ahora es creado por sistemas de IA, lo que ha aumentado la productividad de ingeniería en al menos un 30%. “Al rediseñar los flujos de trabajo e integrar la automatización inteligente, el equipo logró una desviación de tickets superior al 94%, manteniendo e incluso mejorando la satisfacción de los candidatos”. Los tiempos de respuesta y resolución han mejorado, y el propio trabajo evolucionado, con varios miembros del equipo pasando a desempeñar roles de mayor valor en otras partes de la empresa. “Los que se quedaron pasaron del soporte transaccional a crear activos de alto rendimiento que hacen que nuestros modelos de IA sean más precisos y más sensibles al contexto”, dice Daden, para añadir: “Pasaron de responder tickets a mejorar la inteligencia del propio sistema, lo que supone una contribución fundamentalmente más estratégica”.

Young, de RightClick, señala un ejemplo de cómo las herramientas de toma de notas con IA pueden facilitar el trabajo del equipo de TI y hacerlo más estratégico. Estas herramientas liberan a los profesionales de TI de la distracción de capturar cada detalle durante las reuniones. En lugar de detenerse a escribir, pueden mantenerse concentrados en la conversación y en las decisiones que se toman. Esto significa que dedican menos tiempo al trabajo administrativo y más tiempo a pensar, resolver problemas y planificar los siguientes pasos, el tipo de trabajo que realmente impulsa el negocio.

“No hay nada peor que estar concentrado y tener que interrumpir ese flujo para tomar notas sobre lo que se está diciendo”, afirma, para concluir: “Estas herramientas de toma de notas con IA permiten que las reuniones fluyan a un ritmo normal y pueden proporcionar al equipo un resumen de acciones y puntos de debate. Son muy valiosas”.

AI ìš°ë € 현싀 되나···2025년 Ʞ술업계 감원 24만 명 읎상

13 January 2026 at 02:48

볎고서에 따륎멎, 2025년 한 핮 동안 전 섞계 Ʞ술 업계에서 앜 24만 4,851개의 음자늬가 사띌진 것윌로 나타났닀. 영국에 볞사륌 둔 ꞈ융 서비슀 êž°ì—… 래셔널FX는 전 섞계 Ʞ업읎 횚윚성곌 수익성, AI êž°ë°˜ 생산성에 쎈점을 맞추Ʞ 위핎 욎영 방식을 재펞한 결곌띌고 분석했닀.

튞룚업(TrueUp), 테크크런치(TechCrunch), 믞국 여러 죌의 WARN 데읎터베읎슀에 볎고된 감원 사례륌 분석한 래셔널FX는 겜제적 불확싀성곌 고ꞈ늬 환겜, AI와 자동화 도입을 죌요 배겜윌로 지목했닀. 볎고서는 읎 같은 요읞윌로 읞핎 2025년읎 “2022년 팬데믹 읎후 조정 국멎에 읎얎 또 한번 지속적읞 구조조정읎 읎얎진 시Ʞ”띌고 진닚했닀.

Ʞ업은 2025년 감원의 가장 빈번한 원읞윌로 AI와 자동화륌 ꌜ았닀. 래셔널FX에 따륎멎 음부 Ʞ업은 새로욎 Ʞ술에 대응핎 직원 재교육을 진행했지만, 상당수는 직묎륌 완전히 대첎하는 방식윌로 읞력 구조륌 조정했닀.

래셔널FX의 애널늬슀튞 앚런 윔얞은 성명을 통핎 “2025년 Ʞ술업계 감원은 닚Ʞ적읞 비용 절감읎 아니띌 구조적 재펞을 가속화하는 곌정에서 전 섞계 수십만 명의 귌로자륌 음터에서 밀얎냈닀”띌고 섀명했닀. 귞는 “고ꞈ늬, 묎역 제한, 지정학적 불확싀성 같은 거시겜제적 압박읎 êž°ì—… 신뢰에 계속 부닎윌로 작용했지만, 지난핎 음자늬 감소의 가장 지배적읞 요읞은 자동화와 읞공지능의 빠륞 확산읎었닀”띌고 분석했닀.

읎번 분석에서는 믞국 Ʞ술 Ʞ업읎 전첎 Ꞁ로벌 Ʞ술업계 감원의 대부분을 찚지한 사싀도 드러났닀. 읎듀 Ʞ업은 전 섞계 Ʞ술업계 감원의 앜 69.7%륌 찚지했윌며, 읎에 따띌 믞국 Ʞ술 Ʞ업의 국낎왞 사업장에서 17만 명읎 넘는 읞력읎 감축된 것윌로 나타났닀.

믞국 낮 Ʞ술업계 감원, 캘늬포니아가 최닀

래셔널FX 볎고서에 따륎멎, 2025년 믞국 Ʞ술 업계에서 최닀 감원을 Ʞ록한 곳은 캘늬포니아죌였닀. 캘늬포니아에서는 올핎 7만 3,499개의 음자늬가 쀄얎듀며, 읎는 믞국 전첎 Ʞ술업계 감원의 앜 43.08%륌 찚지했닀. 볎고서는 워싱턎죌에서도 연쎈 읎후 4만 2,221개의 Ʞ술 ꎀ렚 음자늬가 사띌졌윌며, 읎는 전첎의 24.74%에 핎당한닀고 밝혔닀.

래셔널FX에 의하멎 2025년 믞국에서 Ʞ술업계 감원읎 가장 많았던 죌는 닀음곌 같닀.

  • 캘늬포니아: 7만 3,499개(43.08%)
  • 워싱턎: 4만 2,221개(24.74%)
  • 뉎욕: 2만 6,900개(15.8%)
  • 텍사슀: 9,816개(6%)
  • 맀사추섞잠: 3,477개

“2025년 최닀 읞력 감축 Ʞ업은 읞텔”

래셔널FX 볎고서에 따륎멎 2025년 한 핮 동안 가장 많은 읞력 감축을 당행한 Ʞ업은 읞텔읎었닀.

볎고서는 2024년 말 Ʞ쀀 앜 10만 9,000명을 고용하고 있던 읞텔읎 2025년 말까지 읞력을 앜 7만 5,000명 수쀀윌로, 앜 3만 4,000개의 직묎륌 쀄음 계획을 발표했닀고 밝혔닀. 볎고서는 2025년 대규몚 감원을 겪은 닀륞 죌요 믞국 Ʞ술 Ʞ업윌로 아마졎, 마읎크로소프튞(MS), 버띌읎슌, 타타컚섀턎시서비슀, 액섌추얎, IBM, HP륌 ꌜ았닀.

  • 아마졎: 2만 명 읎상 감원
  • 마읎크로소프튞: 1만 9,215명 감원
  • 버띌읎슌: 1만 5,000명(전첎 읞력의 15%)
  • 타타 컚섀팅 서비슀: 1만 2,000명 감원
  • 액섌추얎: 1만 1,000명 감원
  • IBM: 9,000명 감원
  • HP: 6,000명 감원(전첎 읞력의 10%)

윔얞은 “곌거 곌잉 채용에 따륞 감원곌 달늬, 2025년의 읞력 감축 상당수는 음시적읞 조정읎 아닌 영구적읞 변화였닀. Ʞ업읎 AI 쀑심 욎영 몚덞로 재펞되는 곌정에서 직묎 자첎가 사띌진 겜우가 많았닀”띌고 섀명했닀. 귞는 읎얎 “자동화에 대규몚 투자가 읎뀄졌음에도 읎런 구조조정읎 슉각적읞 횚윚성 개선윌로 읎얎지지 않은 겜우도 적지 않닀. 읎는 AI êž°ë°˜ 생산성에 대한 Ʞ대와 대규몚 읞력 전환의 현싀 사읎의 ꎎ늬가 점점 컀지고 있음을 시사한닀”띌고 분석했닀.

AI와 자동화, 음자늬 축소의 핵심 요읞

래셔널FX는 2025년 읞력 감원의 가장 빈번한 원읞윌로 AI와 자동화륌 지목했닀. 볎고서에 따륎멎 음부 Ʞ업은 직원 재교육을 선택했지만, 음부는 직묎 자첎륌 대첎하는 방향윌로 대응했닀. 특히 데읎터 처늬, 고객 지원, 읞사, 행정 부묞에서 변화가 두드러졌닀.

아마졎은 지난핎 10월 28음 1만 4,000명 감원을 확정하며, 회사의 전략적 쎈점읎 AI에 ë§žì¶°ì ž 있고 핎당 Ʞ술읎 가젞올 변화에 적응하고 있닀고 밝혔닀. 앞서 2023년 영국 통신사 BT는 2030년까지 직원곌 계앜직을 포핚핎 5만 5,000개의 음자늬륌 감축할 계획읎띌고 발표했닀. 볎고서에 따륎멎, 2025년 3월 말 Ʞ쀀 BT의 직원 수는 앜 8만 5,300명윌로, 2024년 같은 시점볎닀 앜 6,400명 쀄얎든 것윌로 나타났닀.

전묞 서비슀 êž°ì—… 액섌추얎는 AI 역량 재교육 전략의 음환윌로 불곌 3개월 만에 1만 1,000명의 읞력을 감축했닀고 밝혔닀. HP 역시 2025년 11월, 전사적읞 AI 통합을 추진하는 곌정에서 6,000개 직묎륌 쀄읎겠닀고 발표했닀. 섞음슈포슀의 CEO 마크 베니였프도 AI가 섞음슈포슀 욎영 전반에 믞치는 영향을 읎유로 고객 지원 읞력을 4,000명 감축했닀고 섀명했닀.

윔얞은 “자동화와 전략적 전환, 겜제적 불확싀성 등 구조적읞 압박 요읞읎 지속되고 있얎 2026년에도 감원읎 끝나지는 않을 가능성읎 크닀. 적얎도 1분Ʞ까지는 읎 흐늄읎 읎얎질 것”읎띌고 전망했닀. 귞는 읎얎 “음부 섞부 산업은 위축읎 계속되겠지만, AI ꎀ렚 직묎륌 쀑심윌로 닀륞 영역에서는 비교적 활발한 채용읎 나타날 수 있닀”띌고 낎닀뎀닀.
dl-ciokorea@foundryco.com

2026幎のITトレンドを読む囜内トップITリヌダヌの提蚀

12 January 2026 at 16:46

2026幎、䌁業のIT戊略はか぀おないスピヌドで進化しおいたす。生成AIの普及、サむバヌセキュリティの高床化、デヌタ掻甚の深化など、倉革の波は経営の根幹にたで及んでいたす。こうした環境䞋で、CIOをはじめずするITリヌダヌには、テクノロゞヌずビゞネスを融合させ、持続的な競争力を生み出す戊略が求められおいたす。

CIO.com Japanでは、囜内を代衚するCIO、CTO、CAIOをはじめずするITリヌダヌに「2026幎に泚目すべきITトレンド」ずその背景に぀いおコメントをいただきたした。

本蚘事では、囜内トップITリヌダヌが語る「次の䞀手」を通じお、2026幎のIT戊略の方向性を探りたす。

株匏䌚瀟リコヌ
コヌポレヌト䞊垭執行圹員CTO
セキュリティ統括担圓
技術統括郚 郚⟧、デゞタル戊略郚 郚⟧
野氎 泰之 氏

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Richo

AI駆動型プロセス最適化が䌁業競争力を決める

2026幎ぱヌゞェント型AIの本栌導入が進み、「AI駆動型プロセス最適化」ずそのための「デヌタ掻甚基盀・デヌタ敎備匷化」が加速したす。

リコヌではERPの刷新を進めおいたすが、刷新に䌎い業務プロセスをAI駆動型に再蚭蚈しながら開発・運甚の自動化を進めたす。

同時にAI掻甚匷化のために予防型セキュリティぞの進化、AIガバナンス・リスクマネゞメントの匷化を進めおいきたす。

株匏䌚瀟荏原補䜜所
執行圹 CIO最高情報責任者)
小和瀬 浩之 氏

株匏䌚瀟荏原補䜜所 執行圹 CIO最高情報責任者 小和瀬 浩之 氏

EBREA

AI時代の本質は「人材再配眮」ずプロセス再蚭蚈

昚今報道されるAI導入促進による埓業員数の敎理が倧きく報道されたすが、生産性向䞊ずいうよりは、新たなAI収益源ぞの「人材の戊略的再配眮」だずみおいたす。

我々はAIによる真の生産性向䞊を実珟し、ROIを高めるためには、機胜プロセスの培底的な再蚭蚈・再線成が必須であり、その劎力はAI技術導入よりも䞀局の劎力を芁するず考えおいたす。

株匏䌚瀟博報堂DYホヌルディングス
執行圹員
CAIO
森 正匥 氏

株匏䌚瀟博報堂DYホヌルディングス 執行圹員 CAIO 森 正匥 氏

Hakuhodo

AI゚ヌゞェント時代の到来創造性ず効率化の䞡立が鍵

2026幎は、AIが単なる生成ツヌルから自埋的に「考え、動く」゚ヌゞェントぞず進化し、実務ぞの浞透が定着するフェヌズに入るず予想されたす。同時に、AIぞの過床な䟝存によるアりトプットの均質化や、埓業員の創造性が損なわれるリスクも指摘されおいたす。単なる効率化にずどたらず、珟堎の暗黙知や自瀟ならではの創造性をAIずいかに融合させるかを念頭に、組織デザむンや業務プロセス、デヌタのAI-Ready化を進めるこずが重芁な経営課題ずなるず考えたす。

IT領域においおは、「Vibe Coding」に代衚されるAI駆動型の開発手法が広がり、システム構築のアプロヌチそのものが倉容し぀぀ありたす。゚ヌゞェントによるシステム間連携やフィゞカルAIずいった新たな技術朮流ぞの察応も芋据え、倉化に柔軟に適応できるアヌキテクチャぞの刷新を蚈画的に進めおいくこずが倧切です。

䌊藀忠商事株匏䌚瀟
准執行圹員 IT・デゞタル戊略郚長 
浊䞊 善䞀郎 氏

䌊藀忠商事株匏䌚瀟 准執行圹員 IT・デゞタル戊略郚長  浊䞊 善䞀郎 氏

Itochu

AIトランスフォヌメヌションが経営の最倧テヌマになる幎

2026幎のITトレンドは、AIを「生産性向䞊のための道具」ずしお芋る段階から、「䌚瀟の競争力を支える土台」ずしお捉え盎す流れが䞀気に進む幎になるず考えおいたす。

これに䌎い、IT経営基盀の圹割も倧きく倉わりたす。基幹システムは単なる業務凊理の仕組みから、AIが掻甚しやすいデヌタを蓄積する「AIを前提ずした基盀」ぞず進化し、それらを支えるオンプレミスず耇数クラりドの䞀䜓的な運甚、すなわち「ハむブリッドクラりド管理」の重芁性がこれたで以䞊に高たっおいくでしょう。

こうした基盀の䞊でビゞネスを牜匕するのが、自埋的に業務を進めるAI゚ヌゞェントや、珟堎でリアルタむムに刀断を䞋す゚ッゞAIずいった技術です。しかし、AIが業務の䞭枢に入り蟌むほど、「どのAIに䜕を任せ、結果をどう説明するか」ずいうAIガバナンスや、生成AIを悪甚した攻撃に察抗する倚局的なサむバヌセキュリティ察策ずいった「守り」の仕組みも欠かせなくなりたす。

最終的には、単にツヌルを導入するだけでなく、ビゞネスモデルや意思決定のあり方そのものをAI前提に再構築する「AIトランスフォヌメヌションAIX」を、党瀟ずしおどう実珟しおいくか。これが、2026幎の経営における最倧のテヌマになるず芋おいたす。

楜倩グルヌプ株匏䌚瀟
専務執行圹員 Group CIOChief Information Officer& Group CTOChief Technology Officer
黒䜏 昭仁 氏

楜倩グルヌプ株匏䌚瀟 専務執行圹員 Group CIOChief Information Officer& Group CTOChief Technology Officer 黒䜏 昭仁 氏

Rakuten

AIの民䞻化の時代䌁業競争力はデヌタ資産・AIテクノロゞヌ・倫理芳が鍵に

2026 幎は、AIを䜿甚しおいるずいう認識すらなくなっおいくほど、AIが日垞の「圓たり前」になるでしょう。これはたさに、楜倩グルヌプが目指す「AI の民䞻化」の姿です。このAI時代の競争においおは、䌁業の持぀デヌタ資産、AIテクノロゞヌ、そしお倫理芳 の぀が倧きなキヌワヌドになるず考えおいたす。

楜倩グルヌプでは、蓄積された各ドメむンの膚倧なデヌタを、圓瀟独自の AI ゚ヌゞェントにより 70 以䞊のサヌビスに連携させ、お客様䞀人ひずりに最適化された䜓隓を提䟛しおいくこずで、「楜倩゚コシステム経枈圏」の進化を目指しおいたす。顧客䜓隓を AI テクノロゞヌで再構築し、より䟿利で安党なサヌビスを提䟛できるよう、今埌も努めおたいりたす。

IPOかM&Aかスタヌトアップの「ゎヌル」で倉わるストックオプションの珟金化ルヌルず泚意点

12 January 2026 at 14:01

暗闇の䞭を手探りで進み、幟倚のハヌドシングスを乗り越えおきたスタヌトアップにずっお、IPO新芏䞊堎やM&A䌁業の買収・合䜵ずいったむグゞットは、䞀぀の倧きな到達点です。そしお、埓業員ずしおストックオプションを握りしめ、絊䞎以䞊の䟡倀貢献を続けおきた人々にずっおは、その努力が報われ、経枈的な果実を手にする瞬間でもありたす。

しかし、䞊堎の鐘を鳎らしたその日に、すぐさた倧金が手に入るわけではありたせん。むしろ、そこからが「珟金化」に向けた最埌の、そしお最も神経を䜿う戊いの始たりでもありたす。むンサむダヌ取匕芏制、ロックアップ期間、皎金の玍付タむミング、あるいはM&Aにおける買い手䌁業ずの条件亀枉など、ゎヌル盎前には倚くのハヌドルが埅ち構えおいたす。

ストックオプションで実際にキャッシュを手にするたでのプロセスは非垞に泥臭く、耇雑なルヌルに瞛られおいたす。本蚘事では、その最終局面で慌おないために、IPOずM&Aそれぞれの出口におけるストックオプションの取り扱いず、泚意すべき実務のリアルを解説したす。


1. IPO新芏䞊堎時の暩利行䜿ず売华プロセス

倚くのスタヌトアップ関係者が倢芋るIPO。蚌刞取匕所に䞊堎し、誰でも自由に自瀟の株を売買できるようになるむベントです。しかし、ストックオプションを持぀埓業員にずっお、䞊堎日はゎヌルではなく、あくたでスタヌトラむンに過ぎたせん。

たず理解すべきは、䞊堎承認が降りたからずいっお、無条件にすべおのストックオプションが行䜿できるわけではないずいう点です。ストックオプションには通垞、べスティング暩利確定期間が蚭定されおいたす。䞊堎時点で入瀟から日が浅く、ただ暩利が確定しおいない分に぀いおは、圓然ながら行䜿もお預けずなりたす。たた、皎制適栌ストックオプションの堎合、暩利行䜿は「付䞎決議から2幎経過埌」か぀「䞊堎埌」ずいった条件が぀いおいるこずが䞀般的です。

いざ暩利が確定し、行䜿可胜な状態になったずしおも、次に立ちはだかるのがむンサむダヌ取匕芏制です。䞊堎䌁業の埓業員は、未公開の重芁事実決算情報や業務提携の話などを知り埗る立堎にありたす。そのため、自分の䌚瀟の株であっおも、奜きな時に自由に売買するこずはできたせん。倚くの䌁業では、四半期決算の発衚盎埌など、特定の「売買可胜期間りィンドり」を瀟内ルヌルで定めおいたす。埓業員はその限られた期間内に、瀟内の管理郚門に申請を行い、蚱可を埗た䞊で蚌刞䌚瀟を通じお暩利行䜿ず株匏売华を行うこずになりたす。

さらに、皎制非適栌ストックオプションを持っおいる堎合は、資金繰りの問題も発生したす。第2回の蚘事で解説した通り、非適栌SOは暩利を行䜿した瞬間に、ただ株を売っおいなくおも倚額の皎金が発生したす。そのため、行䜿ず同時に株を垂堎で売华し、その代金で玍皎ず行䜿䟡額の払い蟌みを枈たせる「キャッシュレス行䜿」の手続きをずるのが䞀般的です。これには蚌刞䌚瀟ずの事前の連携が䞍可欠であり、䞊堎前から準備を進めおおく必芁がありたす。


2. 「ロックアップ」期間の制玄ず垂堎ぞの圱響

IPOにおける最倧の関門、それがロックアップLock-upです。これは、䞊堎盎埌の株䟡の暎萜を防ぐために、既存の倧株䞻やストックオプション保有者に察しお、䞀定期間、株匏の売华を犁止する契玄のこずを指したす。

もし䞊堎初日に、創業瀟長やベンチャヌキャピタル、そしお倧量のストックオプションを持った埓業員が䞀斉に株を売りに出したらどうなるでしょうか。売り泚文が殺到し、株䟡は倧暎萜しおしたいたす。これでは新たに株を買っおくれた䞀般投資家が損をしおしたいたす。そこで䞻幹事蚌刞䌚瀟は、䌚瀟偎ず協議の䞊、「䞊堎から180日間玄半幎間は株を売っおはいけない」ずいう玄束を取り付けたす。これがロックアップです。

埓業員にずっお、この半幎間は粟神的に非垞に長く感じられる期間です。ニュヌスでは「時䟡総額〇〇億円で䞊堎」ず華々しく報じられ、自分の保有するストックオプションの䟡倀も蚈算䞊は数千䞇円になっおいるかもしれたせん。しかし、それはあくたで「含み益」であり、絵に描いた逅です。目の前に倧金があるのに觊れるこずができず、その間に株䟡が䞋がっおいく恐怖ず戊わなければなりたせん。実際、䞊堎盎埌の期埅感ご祝儀盞堎で高倀を぀けた株䟡が、半幎埌には半分以䞋になっおしたうケヌスも珍しくありたせん。

そしお、ロックアップ期間が明ける日、通称「ロックアップ解陀」のタむミングでは、垂堎が倧きく動きたす。溜たっおいた売り圧力が䞀気に解攟されるため、株䟡が䞀時的に䞋萜する傟向がありたす。賢明なストックオプション保有者は、解陀日になったからずいっお慌おお成行売りをするのではなく、垂堎の動向を芋極めながら、数回に分けお売华するずいった分散戊略をずるこずが掚奚されたす。䞀攫千金を狙うギャンブルではなく、冷静な資産運甚の芖点が求められるのです。


3. M&A買収時のストックオプションの取り扱い

近幎、IPOず䞊んで有力な遞択肢ずなっおいるのが、倧䌁業などによるM&A買収です。この堎合、ストックオプションの扱いはIPOよりも耇雑で、買い手䌁業ずの契玄内容合䜵契玄曞などによっお倩ず地ほどの差が生たれたす。

M&Aにおいおストックオプションがどうなるかは、倧きく分けお䞉぀のパタヌンがありたす。䞀぀目は買い取りCash outです。買い手䌁業が、埓業員の持っおいるストックオプションを珟金で買い取っおくれるパタヌンです。「買収䟡栌ず行䜿䟡額の差額」を珟金ずしお受け取れるため、埓業員にずっおは最も分かりやすく、即座に利益が確定するハッピヌなシナリオです。ただし、皎務䞊は絊䞎所埗ボヌナスずしお扱われるこずが倚く、高い皎率がかかる点には泚意が必芁です。

二぀目はロヌルオヌバヌ眮き換えです。買収された䌚瀟のストックオプションを消滅させる代わりに、買い手䌁業のストックオプションや株匏を新しく亀付するパタヌンです。䟋えば、スタヌトアップA瀟が䞊堎䌁業B瀟に買収された堎合、A瀟のストックオプションは消え、代わりにB瀟のストックオプションをもらいたす。この堎合、すぐに珟金化できるわけではなく、B瀟の株䟡䞊昇やB瀟での勀務継続が新たな条件ずなりたす。M&A埌も䌚瀟に残っお働いおほしいずいう、リテンション匕き留めの意図が匷く働きたす。

䞉぀目は、最悪のケヌスですが消滅です。契玄内容によっおは、行䜿条件を満たしおいないべスティング期間䞭のストックオプションは、䜕の察䟡もなくただ消滅しおしたうこずもあり埗たす。これを防ぐために重芁になるのがアクセラレヌション条項加速条項です。「M&Aによっお䌚瀟支配暩が移動した堎合は、すべおの未確定ストックオプションの暩利を盎ちに確定させる」ずいう特玄を、発行時の契玄曞に盛り蟌んでおくこずです。これがあれば、M&Aが決たった瞬間にすべおの暩利を行䜿可胜な状態にし、買収察䟡を受け取るこずができたす。経営陣やCFOは、M&A亀枉においお、埓業員の暩利が守られるように買い手偎ずタフな亀枉を行う矩務があるず蚀えるでしょう。


4. 䞊堎前の珟金化手段セカンダリヌマヌケットの掻甚

これたでは「䞊堎するか、M&Aされるか」の二択しか珟金化の手段はありたせんでした。しかし近幎、䞊堎前の未公開株を売買できるセカンダリヌマヌケットが日本でも胎動し始めおいたす。

通垞、䞊堎たでには5幎から10幎ずいう長い時間がかかりたす。その間、創業メンバヌや初期の埓業員にも、結婚、出産、䜏宅賌入、芪の介護ずいったラむフむベントが発生し、たずたった珟金が必芁になる堎面が蚪れたす。「䌚瀟は順調に成長しおいるし、応揎したい気持ちは倉わらないが、今どうしおも珟金が必芁だ」。こうしたニヌズに応えるために、保有しおいる株匏やストックオプションの䞀郚を、䞊堎前にファンドや投資家に売华するこずを認めるケヌスが増えおいたす。

海倖では䞀般的ですが、日本でも䞀郚のVCベンチャヌキャピタルやセカンダリヌ特化型ファンドが、埓業員持ち株の買い取りを行っおいたす。経営陣ずしおも、IPOたでの長い道のりで埓業員が息切れしないよう、ガス抜きずしお郚分的な珟金化Cash inを認めるこずは、モチベヌション維持の芳点から合理的です。

たた、退職時にストックオプションを行䜿しお株匏に倉え、それを䌚瀟やファンドが買い取るずいうスキヌムも敎備され぀぀ありたす。これにより、「蟞めたら玙切れ」ではなく、「貢献した分だけ珟金を持っお卒業できる」ずいう健党な゚コシステムが䜜られようずしおいたす。ただし、セカンダリヌでの売华は皎務䞊の取り扱いが耇雑になる堎合があるため、必ず専門家の助蚀を仰ぎながら進める必芁がありたす。


11 perfiles profesionales relacionados con la nube muy demandados por las empresas

12 January 2026 at 06:38

Es una evidencia: las organizaciones no cejan de invertir con fuerza en soluciones en la nube de cara a 2026. El objetivo es claro según el informe 2025 CIO Cloud Computing Study de Foundry: mejorar la productividad de los empleados en el 31% de los casos, mejorar la seguridad y la gobernanza en la organización en el 30%, y acelerar la adopción de la IA y el machine learning en el 13%.

La encuesta revela que el 70% de los responsables de la toma de decisiones de TI está de acuerdo en que su organización ha acelerado la migración a la nube en los últimos 12 meses, en comparación con el 62% en 2024 y el 57% en 2023. Además, el 70% reconoce que su organización opta por defecto por los servicios basados en la nube cuando actualiza o adquiere nueva tecnología, y el 71% afirma que las inversiones en la nube han ayudado a su organización a mantener un aumento de los ingresos en los últimos 12 meses.

Este crecimiento en la adopción de la nube también ha provocado un aumento de la demanda de determinados puestos relacionados con la nube. A continuación, y sirviéndonos de la investigación de Foundry, le detallamos algunos de los que las empresas probablemente hayan añadido para respaldar sus inversiones en la nube.

Arquitecto de seguridad

Los arquitectos de seguridad se encargan de crear, diseñar e implementar soluciones de seguridad en la organización para mantener la seguridad de la infraestructura de TI. Para los que trabajan en un entorno de nube, el objetivo es diseñar e implementar soluciones de seguridad que protejan la infraestructura, los datos y las aplicaciones basados en dicho entorno.

Habilidades: diseño de arquitectura de seguridad, seguridad de redes, cumplimiento y gobernanza de la seguridad, respuesta a incidentes y análisis forense, cifrado de datos, gestión de identidades y accesos (IAM), automatización y DevSecOps.

Crecimiento del puesto: el 22% de las empresas ha añadido puestos de arquitecto de seguridad como parte de sus inversiones en la nube.

Administrador de sistemas en la nube

Los administradores de sistemas en la nube se encargan de supervisar el mantenimiento y la gestión general de la infraestructura en la nube. Estos profesionales de TI son expertos en navegar por entornos virtualizados ya sea implementando políticas basadas en la nube, desplegando parches y actualizaciones o analizando el rendimiento de la red.

Habilidades: conocimiento de la implementación e integración, la seguridad y la configuración, así como de las herramientas de software en la nube más populares, como Azure, AWS, GCP, Exchange y Office 365.

Crecimiento del puesto: el 22% de las empresas cuenta con nuevos puestos de administrador de sistemas en la nube como parte de sus inversiones en la nube.

Arquitecto de datos

La función de un arquitecto de datos es asegurarse de que los datos de una organización estén estructurados de manera que se pueda acceder a ellos fácilmente, estén protegidos y se almacenen de manera eficiente, y satisfagan las necesidades empresariales. Los datos se han convertido en la principal forma en que las empresas realizan análisis y ayudan en la toma de decisiones empresariales, y la mayor parte de esos datos se almacenan ahora en la nube.

Habilidades: almacenamiento de datos, escalabilidad y optimización del rendimiento, automatización y virtualización, gobernanza de datos y seguridad en la nube, migración de datos y conocimiento de soluciones de nube híbrida.

Crecimiento del puesto: el 22% de las empresas ha incorporado puestos de arquitecto de datos como parte de sus inversiones en la nube.

Gerente de gobernanza y cumplimiento normativo en la nube

Los gestores de gobernanza y cumplimiento normativo en la nube ayudan a las empresas a navegar por las complejidades de la seguridad, la gobernanza, la normativa internacional y las políticas internas. Se encargan de identificar los riesgos potenciales, implementan herramientas automatizadas para supervisar la seguridad y el cumplimiento normativo, y ayudan a las empresas a mantener operaciones seguras en la nube.

Habilidades: sólidos conocimientos de políticas normativas como el RGPD, la HIPAA, el PCI DSS y otras leyes internacionales de protección de datos. Otras habilidades adicionales incluyen el conocimiento de herramientas como CSPM, Azure, AWS, Microsoft Purview Compliance Manager y otras herramientas de gobernanza de TI.

Crecimiento del puesto: el 20% de las empresas ha incorporado puestos de gestor de cumplimiento normativo y gobernanza en la nube como parte de sus inversiones en la nube.

Ingeniero de seguridad

Los ingenieros de seguridad se encargan de supervisar la seguridad de los sistemas, las redes y los datos de una organización para garantizar que estén protegidos contra las amenazas de ciberseguridad. Se trata de perfiles que pueden ayudar a las organizaciones que invierten en la nube a garantizar que los servicios, las aplicaciones y los datos que se ejecutan en plataformas en la nube sean seguros y cumplan con cualquier normativa gubernamental.

Habilidades: seguridad de redes, IAM, cifrado, gestión de vulnerabilidades, arquitectura de seguridad, seguridad en la nube, automatización y diseño y optimización de infraestructuras.

Crecimiento del puesto: el 19% de las empresas ha añadido puestos de ingeniero de seguridad como parte de sus inversiones en la nube.

Gerente de productos en la nube

La adopción de la nube suele ir acompañada de un aumento del desarrollo interno de servicios basados en la nube. Un gerente de productos en la nube puede ayudar a los equipos de la nube a desarrollar soluciones eficaces destinadas a cumplir los objetivos empresariales. También se encargan de utilizar su profundo conocimiento de la gestión de productos en el entorno de la nube para trabajar en estrecha colaboración con las partes interesadas que son clave en el negocio, identificar y definir los requisitos de los usuarios o clientes, desarrollar hojas de ruta de productos y supervisar el proceso de control de calidad para obtener comentarios sobre cómo mejorar la oferta de productos.

Habilidades: gestión de productos, diseño de UX, comunicación y colaboración, y una sólida formación técnica.

Crecimiento del puesto: el 19% de las organizaciones dispone de nuevos puestos de gestor de productos en la nube como parte de sus inversiones en la nube.

Consultor de nube

Con la rápida adopción y migración a la nube, las organizaciones buscan profesionales que puedan aprovechar las tecnologías de nube para satisfacer las necesidades empresariales, hacer crecer el negocio y mejorar la eficiencia. Estos profesionales son expertos en nube y se mantienen al día de las últimas innovaciones en tecnología de nube para asesorar mejor a los líderes empresariales.

Habilidades: conocimientos de arquitectura y diseño de soluciones, DevOps, automatización, gestión de proyectos, seguridad en la nube, cumplimiento normativo, migración a la nube y conocimientos de las plataformas de nube más populares.

Crecimiento del puesto: el 18% de las empresas ha incorporado consultores de nube como parte de sus inversiones en nube.

Ingeniero de DevOps

DevOps se centra en combinar las operaciones de TI con el proceso de desarrollo para mejorar los sistemas de TI y actuar como intermediario en el mantenimiento del flujo de comunicación entre los equipos de codificación e ingeniería. Es un puesto que se centra en la implementación de aplicaciones automatizadas, el mantenimiento de la infraestructura de TI y nube, y la identificación de los posibles riesgos y beneficios de los nuevos programas y sistemas.

Habilidades: automatización, Linux, pruebas de control de calidad, seguridad, contenedorización y conocimientos de lenguajes de programación como Java y Ruby.

Crecimiento del puesto: el 17% de las empresas cuenta ya con nuevos puestos de ingeniero DevOps como parte de sus inversiones en la nube.

Profesional de FinOps/optimización de costes en la nube

Los profesionales de FinOps y optimización de costes en la nube combinan conocimientos de finanzas, tecnología y negocios para ayudar a supervisar el panorama cada vez más complejo de las inversiones en la nube. La computación en la nube es parte integral de la IA, por lo que, a medida que más organizaciones invierten en ella, también están revisando sus inversiones en infraestructura en la nube. Los profesionales de FinOps y optimización de costes en la nube pueden ayudar a las organizaciones a tomar las decisiones financieras adecuadas en torno a las inversiones en tecnología que afectarán al negocio.

Habilidades: conocimientos de finanzas, negocios y tecnología, junto con habilidades en el uso de herramientas y plataformas como AWS, Azure, GCP y plataformas FinOps nativas de la nube.

Crecimiento del puesto: el 16% de las empresas ha incorporado puestos de profesional de FinOps y optimización de costes en la nube como parte de sus inversiones en la nube.

Responsable de FinOps/gerente de FinOps

Los responsables y gerentes de FinOps se encargan de supervisar la intersección entre la ingeniería, las finanzas y los negocios. A medida que más organizaciones crean servicios y herramientas en la nube, buscan profesionales de FinOps con conocimientos técnicos que les ayuden a salvar la brecha entre las finanzas y la tecnología, que aporten mejores ideas sobre cómo reducir costes y ajustarse al presupuesto, al tiempo que se implementan tecnologías innovadoras.

Habilidades: sólidos conocimientos de ingeniería, finanzas y tecnología. Otras habilidades adicionales incluyen conocimientos de plataformas en la nube, habilidades básicas de codificación y análisis de datos.

Crecimiento del puesto: el 15% de las empresas ha incorporado puestos de responsable de FinOps y director de FinOps como parte de sus inversiones en la nube.

Ingeniero de fiabilidad del sitio (SRE)

Cualquier organización que implemente estrategias en la nube presta especial atención a la fiabilidad y la escalabilidad, con lo que se garantizan el acceso a los datos desde la nube y bajo demanda, según sea necesario. Los ingenieros de fiabilidad del sitio son responsables de supervisar la automatización de la infraestructura de TI, la supervisión de aplicaciones y la gestión de sistemas. La infraestructura en la nube requiere actualizaciones frecuentes de software, y los servicios deben poder escalarse con el crecimiento de la organización.

Habilidades: gestión del cambio, gestión de la infraestructura de TI, respuesta a incidentes de emergencia, mejora de procesos y supervisión de aplicaciones.

Crecimiento del puesto: el 10% de las empresas ha añadido puestos de ingeniero de fiabilidad del sitio como parte de sus inversiones en la nube.

How tech and strategy align at Videojet

12 January 2026 at 05:00

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 isn’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.

“When we were part of Danaher, Videojet was a rounding error,” Sehgal says. “Now under Veralto, we’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.”

Tech moves to the center of strategy

Following Videojet’s most recent strategic planning cycle, one of the company’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.

“Historically, these initiatives were owned by product or operations leaders,” Sehgal says. “The fact that technology is now seen as a primary driver of growth says everything about how the organization’s mindset has shifted.”

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. “We needed to recast technology,” he adds. “That meant aligning to our three most important outcomes: growth, margin expansion, and productivity.”

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 Videojet’s most strategic capabilities, including data and AI, e-commerce and web, and ERP transformation.

“It’s about being deliberate,” Sehgal says. “You can’t extract long-term value from AI or automation without first fixing your data strategy and governance. We’re laying the foundation for what I call the multi-agentic future, where workflows are increasingly autonomous.”

Laying the foundation for AI and automation

That foundation is already producing results. In partnership with Sehgal’s team, Videojet is piloting AI and ML applications across multiple fronts. In operations, they’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.

“We’re not limiting experimentation,” Sehgal says. “Teams 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.”

Speaking the language of business

Still, Sehgal knows that even the most elegant technology story won’t land unless it’s translated into business terms. “You can’t walk into a leadership meeting and talk about APIs and architectures,” he said. “You have to talk about how technology contributes to growth and profitability.”

Every initiative under his watch is evaluated through a commercial lens, with clear visibility into how it supports both the customer and the company’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 technology’s targeted contribution to enterprise value. “When we model the impact of our initiatives, we express that impact in business terms that everyone in the organization understands,” he says. “That’s how technology earns its credibility.”

Lessons for tech leaders in legacy industries

For Sehgal, Videojet’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. “In manufacturing, you have to know what holds the business back: labor intensity, asset dependency, supply chain complexity,” he says. “Then, pinpoint where technology can make a difference.”

Building credibility early is equally essential. “The business has to see you as a peer, not a service provider,” he adds. “And you can’t have your CFO reading about a breakthrough before you do.”

Above all, Sehgal believes technology leaders have to be willing to take risks. “In manufacturing or any legacy organization, you have to put skin in the game,” he says. “If you want to drive change, you need to be willing to take on the tough initiatives, own them, and deliver results.” In an industry where efficiency often surpasses innovation, Sehgal is positioning technology to be at the core of a strategy that blends Videojet’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. “Ultimately, our success will be measured not by how digital we are, but by how much we move the business forward,” he says.

採甚力を最倧化する「SOの魅せ方」ずオファヌレタヌの曞き方

11 January 2026 at 13:59

倚くのスタヌトアップが、制床蚭蚈や登蚘ずいったハヌド面には倚倧なコストをかける䞀方で、それを埓業員に䌝える゜フト面、すなわちコミュニケヌションを軜芖しおしたう傟向にありたす。しかし、ストックオプションは、埓業員にずっおは珟圚の絊䞎を犠牲にしお埗るかもしれない「未来の察䟡」です。その䟡倀が䞍明瞭なたたで、リスクを取っお転職を決意できる人は皀でしょう。

採甚競争が激化する珟代においお、ストックオプションは単なる犏利厚生ではなく、他瀟ずの差別化を図る最匷の歊噚になり埗たす。ただし、それは「正しく䌝えられた堎合」に限りたす。本蚘事では、候補者の入瀟意欲を劇的に高めるオファヌの出し方から、入瀟埌のモチベヌション維持、そしお退職時のトラブルを防ぐための出口戊略たで、人事・採甚担圓者が知っおおくべきコミュニケヌションの鉄則を解説したす。


1. 採甚競合に勝぀ための「オファヌレタヌ」ずSO説明資料

採甚のクロヌゞング段階で提瀺されるオファヌレタヌには、通垞、ストックオプションの「個数」や「比率」が蚘茉されおいたす。「あなたには新株予玄暩を100個付䞎したす」あるいは「発行枈株匏数の0.1%を付䞎したす」ずいった蚘述です。しかし、倚くの候補者にずっお、この数字は単なる蚘号に過ぎたせん。その䌚瀟の発行枈株匏総数が䜕株で、珟圚の株䟡がいくらで、将来どれくらいになる芋蟌みなのかが分からなければ、100個ずいう数字が倚いのか少ないのか刀断できないからです。

候補者の心を動かすためには、個数ではなく想定金額キャピタルゲむンで語る必芁がありたす。オファヌレタヌずは別に、䞀枚の補足資料SOシミュレヌションシヌトを甚意するこずを匷く掚奚したす。そこには、珟圚の事業蚈画に基づいた「䞊堎時の目暙時䟡総額」ず、その目暙を達成した堎合に「あなたの持っおいるストックオプションが、皎匕き前でいくらの䟡倀になるのか」を具䜓的な金額で明蚘したす。

䟋えば、「基本絊は幎収600䞇円ですが、4幎埌に時䟡総額300億円で䞊堎するずいう保守的なシナリオでも、あなたのストックオプションは玄2000䞇円の䟡倀になりたす。これを4幎で割れば、実質的な幎収はプラス500䞇円の䟡倀があるオファヌです」ず説明されたらどうでしょうか。提瀺額のむンパクトは党く異なりたす。もちろん、これは確玄された未来ではありたせんが、䌚瀟が目指しおいる頂の高さず、そこに察する分配の意思を明確に瀺すこずで、候補者は初めお「自分事」ずしおリスクずリタヌンを倩秀にかけるこずができたす。

さらに、アップサむドのシナリオだけでなく、ダりンサむドのリスクに぀いおも誠実に䌝えるこずが信頌に぀ながりたす。「もし䞊堎できなかった堎合は䟡倀がれロになる可胜性があるこず」や「䞊堎承認が降りるたでは換金できないこず」を隠さずに説明したす。メリットずデメリットの䞡方を提瀺した䞊で、それでも「䞀緒に倢を远いたい」ず思わせるストヌリヌテリングこそが、スタヌトアップ採甚の真髄です。


2. 瀟内コミュニケヌションず金融教育

無事に入瀟が決たり、ストックオプションを付䞎した埌も、コミュニケヌションを止めおはいけたせん。むしろ、入瀟埌こそが本番です。なぜなら、日々の業務に远われる䞭で、埓業員はストックオプションの存圚や䟡倀を忘れおしたいがちだからです。

定期的に党瀟ミヌティングなどで、資本政策やストックオプションに関する勉匷䌚を開催するこずが重芁です。特に゚ンゞニアやデザむナヌなど、金融知識に詳しくないメンバヌに察しおは、基瀎的なリテラシヌ教育が必芁です。「なぜ株䟡が䞊がるのか」「時䟡総額ずは䜕か」「自分の仕事がどうやっお䌁業䟡倀向䞊に぀ながるのか」を噛み砕いお解説したす。これにより、目の前の開発やデザむンが、単なる䜜業ではなく、自分たちの保有資産の䟡倀を高めるための投資掻動であるずいう認識を持たせるこずができたす。

たた、資金調達のタむミングは、ストックオプションの䟡倀を再認識させる絶奜の機䌚です。「今回のシリヌズB調達によっお株䟡が前回から2倍になりたした。぀たり、皆さんが持っおいるストックオプションの朜圚䟡倀も2倍になったずいうこずです」ずアナりンスするこずで、䌚瀟の成長を我が事ずしお喜ぶ空気が生たれたす。

ただし、過床な期埅を煜りすぎるこずは犁物です。あくたで「未実珟の利益」であり、絵に描いた逅であるこずには倉わりありたせん。「䞊堎すれば金持ちになれる」ずいう金銭的欲求だけを刺激するず、組織の颚土が殺䌐ずしたり、䞊堎が延期になった際の倱望感が倧きくなったりするリスクがありたす。ストックオプションはあくたで、ビゞョン実珟の副産物であるずいうメッセヌゞを䞀貫しお発信し続けるバランス感芚が求められたす。


3. Good Leaver円満退職者ずBad Leaverぞの察応

人事担圓者が最も頭を悩たせるのが、ストックオプションを持った埓業員が退職する際の取り扱いです。埓来の日本の慣行では、退職した時点で未行䜿のストックオプションはすべお倱効没収するずいう契玄が䞀般的でした。しかし、このルヌルは珟代の働き方に合わなくなっおきおいたす。

䟋えば、創業期から5幎間䌚瀟に貢献し、事業の基盀を䜜った功劎者が、家庭の事情や新たなキャリアのために䞊堎前に退職するこずになったずしたす。この人物に察しお「蟞めるなら党おの暩利を眮いおいけ」ず蚀うのは、あたりに酷であり、フェアではありたせん。こうした「䌚瀟に貢献しお円満に退職する人」をGood Leaverグッド・リヌバヌず定矩し、退職埌も䞀定期間は暩利を保持し続けられる、あるいは退職時に暩利を行䜿しお株匏ずしお持ち出せるようにする蚭蚈が増えおいたす。

これを可胜にするのが「べスティング暩利確定」の抂念です。圚籍期間に応じお確定した暩利Vestedに぀いおは、退職埌も持ち出しを認めるずいう考え方です。これにより、埓業員は「もし䞊堎前に蟞めるこずになっおも、今たで積み䞊げた分は無駄にならない」ずいう安心感を持っお働くこずができたす。たた、退職したOB・OGアルムナむが䌚瀟の株䞻であり続けるこずは、圌らが倖の䞖界で䌚瀟のファンや宣䌝マンずしお掻動しおくれる動機付けにもなりたす。

䞀方で、懲戒解雇や競合他瀟ぞの悪意ある転職など、䌚瀟に損害を䞎える圢で蟞めるBad Leaverバッド・リヌバヌに察しおは、確定した暩利であっおも没収できる条項を契玄曞に盛り蟌んでおく必芁がありたす。性善説に立ち぀぀も、最悪の事態に備えた防衛策を甚意しおおくこずが、残された瀟員や株䞻を守るこずに぀ながりたす。どこたでをGoodずし、どこからをBadずするか、その線匕きを明確にし、入瀟時の契玄段階で合意圢成を図っおおくこずが、埌々のトラブルを防ぐ唯䞀の道です。


4. 既存瀟員ぞの远加付䞎ず䞍公平感の解消

組織が拡倧するに぀れお必ず盎面するのが、「叀参瀟員」ず「新芏入瀟瀟員」の間の埅遇栌差、およびストックオプションに関する䞍公平感です。

創業初期のメンバヌは、絊䞎は䜎かったものの、リスクを取った察䟡ずしお倚くのストックオプション䟋えば1%などを持っおいたす。䞀方、シリヌズB以降に入瀟したメンバヌは、垂堎氎準の高い絊䞎をもらっおいる代わりに、ストックオプションの付䞎数はごくわずか䟋えば0.05%などです。この䞡者が混圚するず、「あい぀は昔からいるだけで倧金持ちになれる」「あの人は絊料が高すぎる」ずいった盞互の嫉劬や䞍満が生たれやすくなりたす。

この溝を埋めるための斜策の䞀぀が、リフレッシュ・グラント远加付䞎です。初期メンバヌであっおも、4幎皋床のべスティング期間が終われば、新たに暩利が確定するこずはなくなりたす。そこで、匕き続き高いパフォヌマンスを発揮しおいる瀟員には、新たなストックオプションを远加で付䞎したす。これにより、「過去の遺産」で働いおいるのではなく、「珟圚の貢献」に察しお報われおいるずいう状態を䜜り出したす。

逆に、新芏入瀟者に察しおも、入瀟時の付䞎だけでなく、昇栌や成果に応じた远加付䞎のチャンスがあるこずを明瀺したす。「入瀟時期が遅かったからもう遅い」ず諊めさせるのではなく、これからの頑匵り次第で十分にキャピタルゲむンを埗られる機䌚があるこずを制床ずしお担保するのです。

たた、䞍公平感を解消するためには、党瀟員に察しお「トヌタルリワヌド」ずいう考え方を浞透させるこずも有効です。トヌタルリワヌドずは、基本絊、賞䞎、犏利厚生、そしおストックオプションを含めた「報酬総額」のこずです。初期メンバヌは「珟金絊䞎は少ないが株匏報酬が倚い」、新芏メンバヌは「珟金は倚いが株匏報酬は少ない」。構成芁玠は違えど、䌚瀟が支払っおいるトヌタルリワヌドの䟡倀は公正に蚭蚈されおいるずいうこずを、芖芚的なグラフなどを甚いお説明し、玍埗感を醞成する努力が䞍可欠です。


5. モチベヌション維持のための定期的な䟡倀喚起

ストックオプションは、䞀床枡しお終わりではありたせん。暩利行䜿たでには数幎から10幎近い長い幎月がかかるこずもありたす。その間、埓業員のモチベヌションを維持し続けるためには、定期的なメンテナンスが必芁です。

効果的なのは、半幎に䞀床や䞀幎に䞀床、「報酬通知曞」のような圢匏で、個々人が保有しおいるストックオプションの最新状況を通知するこずです。「珟圚、あなたは〇個の暩利を保有しおおり、そのうち〇個が暩利確定べスティング枈みです。珟圚の掚定評䟡額は〇〇䞇円です」ずいった情報を個別にレポヌティングしたす。

人間は目に芋えないものを意識し続けるこずはできたせん。通垳の残高のように、自分の資産が増えおいるこずを定期的に可芖化しおあげるこずで、日々の業務のモチベヌションに぀なげるこずができたす。たた、こうした通知を行うタむミングで、改めお䌚瀟のビゞョンや䞊堎に向けたロヌドマップを共有し、「この資産を珟金化できるゎヌルたで、あずこれくらいの距離だ」ずいう珟圚地を瀺すこずもリヌダヌの圹割です。

たずめ

採甚や組織開発においお、ストックオプションは魔法の杖ではありたせん。ただ制床があるだけでは、優秀な人材は採甚できたせんし、瀟員の゚ンゲヌゞメントも䞊がりたせん。重芁なのは、その制床に蟌められた「経営の意志」を、盞手に䌝わる蚀葉で翻蚳し、䌝え続けるこずです。

オファヌレタヌでの魅力付け、入瀟埌の金融教育、退職時の誠実な察応、そしお既存瀟員ぞの公平な远加配分。これらすべおのタッチポむントにおいお、䞀貫したメッセヌゞを発信し続けるこずが人事の䜿呜です。「私たちは、成功の果実をあなたず分かち合いたい」。その想いが䌝わった時、ストックオプションは初めお、契玄曞の枠を超えた「同志の蚌」ずなるのです。

ä¿¡èš—åž‹SOのその埌ず、新しいむンセンティブプラン有償SO・RSU

10 January 2026 at 13:42

むンセンティブ報酬の「戊囜時代」ぞ

日本のスタヌトアップにおけるむンセンティブ蚭蚈は、長らく「皎制適栌ストックオプション」の䞀匷時代が続いおいたした。しかし、ここ数幎でその景色は劇的に倉化したした。より柔軟な蚭蚈を求めお登堎した「信蚗型ストックオプション」が䞀倧ブヌムを巻き起こしたかず思えば、囜皎庁による課皎ルヌルの明確化によっお急ブレヌキがかかるずいうドラマチックな展開を芋せたした。

この「信蚗型ショック」を経お、経営者や実務家の関心は、安党か぀効果的な代替手段ぞず向かっおいたす。珟圚では、埓来からある「有償ストックオプション」が芋盎されたり、アメリカのテック䌁業では圓たり前の「RSURestricted Stock Unit」が日本法の䞋で導入されたりず、たさにむンセンティブ報酬の戊囜時代ずも蚀える倚様化が進んでいたす。

経営者にずっお重芁なのは、流行りのスキヌムに飛び぀くこずではありたせん。それぞれのスキヌムが持぀「リスク」ず「リタヌン」、そしお「誰に向けたメッセヌゞなのか」を正しく理解し、自瀟のフェヌズに合わせお最適な組み合わせを遞択するこずです。本蚘事では、激動のトレンドを敎理し、これからのスタンダヌドずなる報酬蚭蚈の矅針盀を提瀺したす。


1. 「信蚗型SOショック」ずは䜕だったのか

たず、時蚈の針を少し戻しお、業界を揺るがした「信蚗型ストックオプション問題」に぀いお振り返りたす。この経緯を理解するこずは、皎務リスクの本質を知る䞊で非垞に重芁です。

信蚗型ストックオプションずは、䌚瀟が発行したストックオプションを、䞀旊「信蚗」ずいう噚プヌルに預けおおき、埌から貢献床に応じお埓業員にポむントを付䞎し、䞊堎時などにそのポむントに応じおストックオプションを分配するスキヌムです。この仕組みの最倧のメリットは、誰に枡すかを埌出しゞャンケンで決められる点にありたした。通垞のストックオプションは発行時点で「誰に䜕個」ず決めなければなりたせんが、信蚗型であれば、入瀟埌の掻躍を芋おから配分を決めるこずができるため、実力䞻矩のスタヌトアップにずっお非垞に䜿い勝手の良い制床ずしお普及したした。

さらに、圓時の解釈では、信蚗ずいう噚を経由するこずで、埓業員にかかる皎金は「絊䞎所埗最倧玄55%」ではなく「譲枡所埗玄20%」で枈むず考えられおいたした。柔軟な配分ができお、か぀皎金も安い。たさに倢のようなスキヌムずしお、数癟瀟以䞊のスタヌトアップが導入したした。

しかし、2023幎5月、囜皎庁は新たな芋解を瀺したした。それは「信蚗型ストックオプションから埗られる利益は、実質的に絊䞎ずしお扱われるべきである」ずいうものでした。぀たり、最倧玄55%の皎率が適甚されるず刀断されたのです。しかも、これから発行するものだけでなく、過去に発行されたものにたで遡及しお適甚される可胜性が瀺唆され、すでに䞊堎しお利益を埗おいた䌁業や個人に倚額の远城課皎が発生するリスクが浮䞊したした。

この発衚により、信蚗型ブヌムは終焉を迎えたした。珟圚では、䞀定の厳栌な芁件を満たせば玄20%の課皎で認められる「セヌフハヌバヌ・ルヌル」が敎備されたしたが、導入・維持コストが高額になるこずや、蚭蚈の難易床が高いこずから、初期のスタヌトアップが気軜に導入できるものではなくなりたした。この事件が残した教蚓は、皎務䞊の「グレヌゟヌン」を攻めるスキヌムは、埌から梯子を倖されるリスクず隣り合わせであるずいう冷厳な事実でした。


2. 有償ストックオプション時䟡発行新株予玄暩の再評䟡

信蚗型に代わる遞択肢ずしお、改めお泚目を集めおいるのが有償ストックオプションです。これは決しお新しい仕組みではなく、叀くから存圚するオヌ゜ドックスな手法です。

通垞のストックオプション無償ストックオプションは、埓業員が䌚瀟から「タダ」で暩利をもらいたす。これに察し、有償ストックオプションは、埓業員や圹員が、その暩利の公正な䟡倀オプション料を䌚瀟にお金を払っお「賌入」する仕組みです。䟋えば、暩利1個あたり100円ずいったプラむシングがなされ、1䞇個欲しければ100䞇円を䌚瀟に振り蟌む必芁がありたす。

なぜわざわざお金を払っおたで暩利を買うのでしょうか。最倧の理由は皎務䞊の安党性にありたす。自腹を切っおリスクを取り、金融商品ずしお賌入しおいるため、そこから埗られる利益は「劎働の察䟡絊䞎」ではなく「投資の利益」ずみなされたす。したがっお、皎制適栌芁件を満たしおいなくおも、売华益は譲枡所埗玄20%ずしお扱われたす。

この特城は、皎制適栌ストックオプションが出せない盞手に察しお非垞に有効です。䟋えば、持ち株比率が3分の1を超えるオヌナヌ瀟長や、瀟倖の協力者、あるいは皎制適栌の幎間限床額最倧3600䞇円〜6000䞇円を超えおさらに暩利を付䞎したいCxOクラスなどが察象ずなりたす。圌らは䞀定のリスク賌入代金を負うこずになりたすが、その分、アップサむドの果実を䜎い皎率で享受できるずいうフェアなトレヌドが成立したす。

ただし、導入に際しおは「公正な評䟡額オプション料」の算定が肝ずなりたす。安すぎれば「実質的な莈䞎」ずみなされお課皎リスクが発生し、高すぎれば埓業員が買えたせん。専門の評䟡機関による算定が必芁ずなるため、数十䞇円から数癟䞇円のコストがかかる点は留意すべきです。


3. グロヌバルスタンダヌド「RSRestricted Stock」ず「RSU」

ストックオプション暩利ではなく、株匏そのものを報酬ずしお枡す仕組みも急速に普及し始めおいたす。それがRS譲枡制限付株匏ずRSU事埌亀付型株匏です。GoogleやAmazonなど、米囜のテック䌁業ではこちらが䞻流であり、日本でもメルカリ等の先進䌁業が積極的に導入しおいたす。

たず、ストックオプションずの決定的な違いを理解したしょう。ストックオプションは「倀䞊がり益」しか埗られたせん。株䟡が行䜿䟡額を䞋回れば䟡倀はれロになりたす。䞀方、RSやRSUは「株匏そのもの」をもらえるため、たずえ株䟡が䞋がっおも、株䟡がれロにならない限り資産䟡倀が残りたす。この「䟡倀がれロになりにくい」ずいう特城は、すでに時䟡総額が高くなり、これ以䞊の急激な株䟡倍増が芋蟌みにくいレむタヌ期や䞊堎埌の䌁業においお、埓業員のリテンション匕き留め斜策ずしお極めお匷力です。

RSRestricted Stock譲枡制限付株匏は、今の日本の䌚瀟法でも比范的導入しやすい制床です。䌚瀟が埓業員に金銭債暩ボヌナスなどを支絊し、埓業員がそのお金を䌚瀟に珟物出資するこずで、代わりに株匏を受け取りたす。ただし、「3幎間は売っおはいけない」「退職したら没収」ずいった譲枡制限が付いおいるため、すぐに珟金化するこずはできたせん。埓業員は「株䞻」ずしおの議決暩を持぀ため、圓事者意識が高たるメリットがありたすが、受け取った時点でただ売れないのに所埗皎がかかる堎合があるなど、皎務䞊の取り扱いには泚意が必芁です。

䞀方、RSURestricted Stock Unit事埌亀付型株匏は、もう少し䜿い勝手が良い仕組みです。これは「条件勀続幎数などを満たしたら、将来株匏をあげたすよ」ずいう玄束ナニットを付䞎するものです。RSずは異なり、付䞎された時点では株は手に入りたせん。条件達成埌、実際に株が亀付されたタむミングで初めお課皎されたす。埓業員にずっおは、株を手に入れるのず同時に玍皎矩務が発生するため、䞀郚の株を売っお玍皎資金に充おるずいった察応がしやすく、キャッシュフロヌの芳点でRSよりも優れおいたす。

日本においおも法解釈の敎理が進み、RSUのような「事埌亀付」の仕組みが導入可胜になりたした。特にグロヌバルに展開し、海倖の人材を採甚したいスタヌトアップにずっおは、䞖界共通蚀語であるRSUを甚意しおおくこずは、採甚競争力を高める必須条件ずなり぀぀ありたす。


4. フェヌズ別・最適なむンセンティブプランの遞び方チャヌト

倚様な遞択肢が出揃った今、自瀟はどれを遞ぶべきなのでしょうか。䌁業の成長フェヌズごずに掚奚されるポヌトフォリオ組み合わせを敎理したす。

① シヌド・アヌリヌ期創業〜シリヌズA前埌 このフェヌズの正解は、シンプルに「皎制適栌ストックオプション」の䞀択です。 䌁業䟡倀がただ䜎く、将来のアップサむド䌞び代が倧きいため、ストックオプションの「レバレッゞ効果」が最倧化したす。埓業員にお金を払わせる有償SOや、株䟡蚈算が耇雑なRSなどは時期尚早です。たずは皎制適栌の枠を最倧限掻甚し、初期メンバヌに倢を芋せるこずが最優先です。

② ミドル・レむタヌ期シリヌズB〜IPO盎前 組織が拡倧し、倚様な人材が入っおくるこの時期は、「皎制適栌SO」「有償SO」のハむブリッド型が有効です。 基本的には皎制適栌SOを䜿い぀぀、幎間限床額を超えるような高額報酬が必芁なCFOや、アドバむザヌなどの瀟倖協力者には有償SOを組み合わせお提䟛したす。たた、䞊堎が芋えおくるず株䟡も䞊がっおくるため、ストックオプションの行䜿䟡額が高くなりすぎ、魅力が薄れる堎合がありたす。その堎合は、入瀟時の株䟡に巊右されず䟡倀を提䟛できるRSUの導入怜蚎を始めるず良いでしょう。

③ IPO埌・䞊堎䌁業 䞊堎埌は、株䟡のボラティリティ倉動が安定しおくるため、ストックオプションの魅力が盞察的に䜎䞋したす。代わっお䞻圹ずなるのが「RS譲枡制限付株匏」や「RSU」です。 既存瀟員に察しお、「長く働き続ければ確実に株がもらえる」ずいう安定的な報酬を提䟛するこずで、離職を防ぎたす。たた、圹員報酬の䞀郚を株匏報酬RSに眮き換えるこずで、株䞻ずの利害䞀臎同じ船に乗るをアピヌルするこずも䞀般的です。


5. 皎制改正による「プヌル信蚗」など新スキヌムの可胜性

最埌に、今埌の展望に぀いお觊れおおきたす。信蚗型SOショック以降、囜や実務家たちは「安心しお䜿える、柔軟なむンセンティブ制床」の構築に向けお動き続けおいたす。

その䞀぀が、2024幎の皎制改正に関連しお議論されおいる新たなプヌル運甚の枠組みです。詳现な制床蚭蚈は珟圚進行圢ですが、将来的には「䞀床発行したストックオプションを䌚瀟が取埗・保有し、それを新たな察象者に再付䞎する」ずいった柔軟な運甚が、皎務リスクなしに行えるようになる可胜性がありたす。これが実珟すれば、信蚗型SOが目指しおいた「埌決め」のメリットを、より安党な圢で享受できるようになるでしょう。

スタヌトアップの報酬蚭蚈は、もはや人事郚だけで完結する話ではありたせん。CFO、法務、そしお経営者が䞀䜓ずなっお、法改正の動向をりォッチし、最適な「報酬のポヌトフォリオ」を組み替えおいく柔軟性が求められたす。

たずめ

トレンドは移り倉わりたすが、本質は倉わりたせん。それは「リスクを取っお挑戊する人間に、適切な報いを甚意する」ずいうこずです。

  • 基本は、王道の「皎制適栌SO」を䜿い倒すこず。
  • それではカバヌできない察象瀟倖協力者・倧口付䞎者には「有償SO」で補完するこず。
  • 安定期やグロヌバル採甚には「RS/RSU」ずいう歊噚を持぀こず。

流行のスキヌムに惑わされず、自瀟のフェヌズず採甚戊略に最もフィットした制床を遞ぶこずこそが、最匷の組織を䜜る第䞀歩です。

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