Splunk for Windows has a high-severity flaw that lets local users escalate privileges through misconfigured file permissions. Learn how to fix it.
The post New Splunk Windows Flaw Enables Privilege Escalation Attacks appeared first on TechRepublic.
For todayโs CIO, the multi-cloud landscape,ย extending across hyperscalers, enterprise platforms, and AI-native cloud providers, is a non-negotiable strategy forย business resilienceย and innovation velocity. Yet, this very flexibility can become a liability, often leading to fragmented automation, vendor sprawl, and costly data silos. The next frontier in cloud optimization isnโt better scriptingโitโsย Agentic AI systems.
These autonomous, goal-driven systems, deployed as coordinated multi-agent ecosystems, act as an enterpriseโs โMAESTRO.โย They donโt just follow instructions; they observe, plan, and execute tasks across cloud boundaries in real-time, effectively transforming vendor sprawl from a complexity tax into a strategic asset.
The core challenge in a multi-cloud environment is not the platforms themselves, but the lack of seamlessย interoperabilityย between the automation layers running on them. The MAESTRO architecture (referencing the Cloud Security Allianceโsย MAESTRO agentic AI threat modeling framework; MAESTRO stands for multi-agent environment, security, threat, risk and outcome) solves this by standardizing the language and deployment of these autonomous agents:
For agents to coordinate effectivelyโto enable a FinOps agent on one cloud to negotiate compute resources with an AIOps agent on another cloudโthey must speak a common, vendor-agnostic language.ย This is where the emergingย Agent2Agent (A2A) protocolย becomes crucial.
The A2A protocol is an open, universal standard that enables intelligent agents, regardless of vendor or underlying model, to discover, communicate, and collaborate.ย It provides the technical foundation for:
To fully appreciate the power of the Maestro architecture, consider a critical cross-cloud workflow:ย strategic capacity arbitrage and failover. Aย FinOps agentย on a general-purpose cloud is continuously monitoring an AI inference workloadโs service level objectives(SLOs) and cost-per-inference. When a sudden regional outage is detected by anย AIOps agentย on the same cloud, the AIOps agent broadcasts a high-priority โcapacity sourcingโ intent using the A2A protocol. The Maestro orchestrates an immediate response, allowing the FinOps agent to automatically negotiate and provision the required GPU capacity with a specializedย neocloud agent. Simultaneously, a security agentย ensures the new data pipeline adheres to the required data sovereignty rules before theย workload migration agentย seamlessly shifts the portable Kubernetes container to the new, available capacity, all in under a minute to maintain continuous model performance. This complex, real-time coordination is impossible without the standardized language and interoperability provided by the A2A protocol and the Kubernetes-native deployment foundation.
To ensure agents can be deployed, scaled, and managed consistently across clouds, we must leverage aย Kubernetes-nativeย approach. Kubernetes is already the de facto orchestration layer for enterprise cloud-native applications. New Kubernetes-native agent frameworks, like kagent, are emerging to extend this capability directly to multi-agent systems.
This approach allows the Maestro to:
The Maestro architecture fundamentally shifts the economics and risk profile of a multi-cloud strategy.
The shift to the Maestro architecture represents more than just a technological upgrade; it signals the true democratization of the multi-cloud ecosystem. By leveraging open standards like A2A, the enterprise is moving away from monolithic vendor platforms and toward a vibrant, decentralizedย marketplace of agentic services. In this future state, enterprises will gain access to specialized, hyper-optimized capabilities from a wide array of providers, treating every compute, data, or AI service as a modular, plug-and-play component. This level of strategic flexibility fundamentally alters the competitive landscape, transforming the IT organization from a consumer of platform-centric services to a strategic orchestrator of autonomous, best-of-breed intelligence. This approach delivers the โstrategic freedom from vendor lock-inโ necessary to continuously adapt to market changes and accelerate innovation velocity, effectively turning multi-cloud complexity into a decisive competitive advantage.
The power of autonomous agents comes with the risk of โmisaligned autonomyโโagents doing what they were optimized to do, but without the constraints and guardrails the enterprise forgot to encode.ย Success requires a robustย governance frameworkย to manage the burgeoning population of agents.
By embracing this Maestro architecture, CIOs can transform their multi-cloud complexity into a competitive advantage, achieving unprecedented levels of resilience, cost optimization, and, most importantly, strategic freedom from vendor lock-in.
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The move reflects a rapidly intensifying race among technology giants to strengthen the data foundations required for generative and agentic AI.
The post IBM Pursues AI Expansion With $11B Confluent Acquisition appeared first on TechRepublic.
X shut down the European Commissionโs ad account after a โฌ120M DSA fine, sparking a tense clash over transparency, platform rules, and rising political fallout.
The post X Blocks EU Ads Account After โฌ120m Fine, Escalating Clash Between Elon Musk and Brussels appeared first on TechRepublic.
Collaboration tools are core to every remote teamโs success. These remote work solutions improve communication, support smoother workflows, and help distributed teams get more work done efficiently.
The post 10 Best Remote Work Tools for Team Collaboration in 2026 appeared first on TechRepublic.
As one of the worldโs foremost voices on cybersecurity and crisis leadership, Sarah Armstrong-Smith has spent her career at the intersection of technology, resilience and human decision-making. Formerly chief security advisor at Microsoft Europe, and now a member of the UK Government Cyber Advisory Board, she is widely recognized for her ability to translate complex technical challenges into actionable business strategy.
In this exclusive interview with The Cyber Security Speakers Agency, Sarah explores how todayโs CIOs must evolve from technology enablers to resilience architects โ embedding cyber preparedness into the core of business strategy. Drawing on decades of experience leading crisis management and resilience functions at global organizations, she offers a masterclass in how technology leaders can balance innovation with security, manage disruption with clarity and build cultures of trust in an era defined by volatility and digital interdependence.
For business and technology leaders navigating the next wave of transformation, Sarahโs insights offer a rare blend of strategic depth and practical foresight โ a roadmap for leadership in the age of perpetual disruption.
Cyber resilience should be recognised as a strategic enabler, not merely a technical safeguard. CIOs must champion a holistic approach where resilience is woven into every stage of digital transformation โ from initial design through to deployment and ongoing operations.
This requires close collaboration with business leaders to ensure risk management and security controls are embedded from the outset, rather than being an afterthought. By aligning cyber resilience objectives with business outcomes, CIOs can work alongside CISOs to help their organizations anticipate threats, adapt rapidly to disruptions and maintain stakeholder trust.
Embedding resilience also demands a shift in organizational mindset. CIOs should help to foster a culture where every employee understands their role in protecting digital assets and maintaining operational service.
This involves education and cross-functional exercises that simulate real-world incidents, aligned to current threats. By making resilience a shared responsibility and a key performance metric, CIOs can ensure their organizations are not only prepared to withstand a range of threats but are also positioned to recover quickly and thrive in the face of adversity.
Balancing innovation and security are constant challenges that require CIOs to act as both risk managers and business catalysts. The key is to embed security and resilience considerations early into the innovation lifecycle, ensuring new technologies and processes are assessed for risk early and often.
CIOs should promote agile governance frameworks that allow for rapid experimentation while maintaining clear guardrails around information protection, compliance and operational integrity. By involving security teams from the outset, organizations can identify potential vulnerabilities before they become systemic issues.
At the same time, CISOs must avoid creating a culture of fear that stifles creativity. Instead, they should encourage responsible risk-taking by providing teams with the tools, guidance and autonomy to innovate securely.
This includes leveraging automation, zero-trust architectures and continuous monitoring to reduce vulnerabilities and enable faster, safer deployment of solutions. Ultimately, the goal is to create an environment where innovation and security are mutually reinforcing, driving competitive advantage and organizational resilience.
Effective crisis leadership is built on preparation, decisiveness and transparent communication. CIOs must ensure their teams are well-versed in incident response and empowered to act swiftly when an incident occurs.
This means investing in due diligence, having clear escalation paths and robust playbooks that outline the critical path, and designated roles and responsibilities. During a crisis, leaders must remain calm, protect critical assets and make informed decisions based on real-time intelligence.
Equally important is the ability to communicate clearly with both internal and external stakeholders. CIOs and CISOs should work in unison to provide timely updates to the board, regulators and customers, balancing transparency with the need to protect vulnerable people and sensitive data.
Demonstrating accountability and empathy during a crisis can help preserve trust and minimise reputational damage. After the incident, leaders should be thoroughly committed to post-mortems to identify โno blameโ lessons learned and drive continuous improvement, ensuring the organization emerges stronger and more resilient.
CIOs are uniquely positioned to guide the ethical deployment of AI and emerging tech, balancing innovation with risk management and societal responsibility. They should contribute to governance frameworks that address data privacy, algorithmic bias and transparency, ensuring AI systems are designed and operated in accordance with core organizational policies and regulatory requirements. This involves collaborating with legal, compliance and HR teams to develop policies that safeguard against unintended consequences and consequential impact.
Additionally, CIOs should champion ongoing education and awareness around AI ethics, both within IT and across the wider organization. By fostering a culture of accountability and continuous learning, CIOs can help teams identify and mitigate risks associated with AI through the implementation of rigorous engineering principles.
Regular technical and security assessments and stakeholder engagement is essential to maintaining trust and ensuring AI adoption delivers positive outcomes for those most impacted by it.
Organizations that recover stronger from cyber incidents typically demonstrate resilience through proactive planning, transparent communication and a commitment to continuous improvement. They invest in proactive and reactive capabilities and a positive culture driven by empathetic leadership, empowerment and accountability.
When an incident occurs, these organizations respond swiftly, contain the threat and communicate transparently with stakeholders about the actions being taken to remediate and reduce future occurrences.
Conversely, organizations that struggle often lack preparedness and fail to engage stakeholders effectively. Delayed or inconsistent communication can erode trust and amplify reputational damage.
The most resilient organizations treat incidents and near-misses as learning opportunities, conducting thorough post-incident reviews and implementing changes to strengthen their defences. By prioritising transparency, accountability and a culture of resilience, CIOs can help their organizations not only recover but also enhance their reputation and stakeholder confidence.
Cultivating a security-first culture requires CIOs and CISOs to make cybersecurity relevant and accessible to all employees, regardless of technical expertise. This starts with tailored training programmes that address the specific risks faced by different stakeholders, rather than a one-size-fits-all approach.
This should leverage engaging formats โ like interactive workshops, gamified learning and real-world simulations to reinforce positive behaviors and outcomes
Beyond training, CIOs and CISOs must embed security into everyday workflows by providing user-friendly tools and clear guidance. Regular communication, visible leadership and recognition of positive security behaviors can help sustain momentum.
In hybrid environments, CIOs should ensure policies are dynamic and adaptive to evolving threats, enabling employees to work securely without sacrificing productivity. By fostering a sense of shared responsibility and empowering non-technical teams, CIOs can build a resilient culture that extends beyond the IT department.
To effectively engage boards, CIOs must translate technical issues into enterprise risks, framing cybersecurity and resilience as a strategic imperative rather than a technical challenge. This involves articulating how exposure to specific threats could affect safety, revenue, reputation, regulatory compliance and operational services. CIOs and CISOs should use clear, non-technical language, supported by real-world scenarios, to illustrate the potential consequences of ineffective controls and the value of resilience investments.
Regular, structured and diligent reporting โ such as dashboards, heat maps and risk registers โ can help boards visualise enterprise risk exposure and track progress over time. CIOs should foster open dialogue, encouraging board members to ask questions and participate in scenario planning.
By aligning security discussions with business objectives and demonstrating the ROI of resilience initiatives, technology and security leaders can build trust and secure the support needed to drive meaningful change.
CIOs must stay ahead of a rapidly evolving threat landscape, characterised by the proliferation of AI-enabled attacks, supply chain vulnerabilities and targeted campaigns. The rise of quantum computing poses long-term risks to traditional encryption methods, necessitating understanding and early exploration of quantum-safe solutions.
Additionally, regulatory scrutiny around data sovereignty and ethical AI is intensifying, requiring codes of conduct and governance strategies.
Beyond technology, CIOs should anticipate continuous shifts in workforce dynamics, such as the increase in human-related threats. Societal risks, geopolitical instability and the convergence of physical and cyber threats are also shaping the resilience agenda. By maintaining a forward-looking perspective and investing in adaptive capabilities, leaders can position their organizations to navigate uncertainty and capitalize on emerging opportunities.
Collaboration across the entire C-suite is essential for building holistic resilience that encompasses people, technology, finance and processes. CIOs must work closely with CFOs to align resilience investments with business priorities and CROs to ensure risk management strategies are financially sustainable. Engaging CHROs is equally important, as workforce readiness and culture play a critical role in responding to and recovering from disruptions.
Joint initiatives such as cross-functional crisis simulations, integrated risk assessments and shared accountability frameworks can help break down silos and foster a unified approach to resilience.
By leveraging diverse perspectives and expertise, CIOs can drive more effective decision-making and ensure resilience is embedded throughout the organization. Ultimately, strong collaboration enables organizations to reduce assumptions, anticipate challenges, respond cohesively and emerge stronger in times of adversity.
Future-ready CIOs must embody adaptability, strategic vision and emotional intelligence. The pace of technological change and the frequency of disruptive events demand leaders who can pivot quickly, embrace uncertainty and inspire confidence in their teams. CIOs should cultivate an inquisitive mindset, continuously seeking new knowledge and challenging conventional wisdom to stay ahead of emerging trends.
Equally important are communication and collaboration skills. CIOs must be able to articulate complex ideas clearly, build consensus across diverse stakeholders and foster a culture of trust and accountability.
Resilience, empathy and a commitment to ethical leadership will enable CIOs to navigate challenges with integrity and guide their organizations through periods of uncertainty and transformation. By developing these qualities, CIOs can lead with purpose and drive sustainable success in an ever-changing landscape.
This article is published as part of the Foundry Expert Contributor Network.
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ๆๅใฎไธๆญฉใจใใฆ้่ฆใชใฎใฏใLLMใจใผใธใงใณใใทในใใ ใฎๅบๆฌ็ใชใขใผใญใใฏใใฃใ้ ญใฎไธญใงๆใใใใใซใใใใจใงใใๅคใใฎๅ ดๅใไธญๆ ธใซใฏLLMๆจ่ซAPIใใใใใใฎๅจๅฒใซใใญใณใใใใณใใฌใผใใใใผใซ็พคใใกใขใชในใใขใRAG็จใฎใใฏใใซใใผใฟใใผในใใญใฐใใขใใฟใชใณใฐใฎไป็ตใฟใ้ ็ฝฎใใใพใใใจใผใธใงใณใ่ชไฝใฏใใใใใ็ตใฟๅใใใใใชใผใฑในใใฌใผใทใงใณๅฑคใใจใใฆๅฎ่ฃ ใใใ่ฆณๅฏใปๆ่ใป่กๅใฎใซใผใใ็ฎก็ใใพใใ
ใฏใฉใคใขใณใใใใฎใชใฏใจในใใฏใใพใใขใใชใฑใผใทใงใณใตใผใใผใ้ใใฆใจใผใธใงใณใใซๆธกใใใพใใใจใผใธใงใณใใฏใ็พๅจใฎใณใณใใญในใใจใกใขใชใใใจใซใใญใณใใใๆง็ฏใใLLM APIใๅผใณๅบใใพใใLLMใใ่ฟใฃใฆใใๅบๅใฎใใกใใใผใซๅผใณๅบใใๅซใพใใฆใใ้จๅใฏใใผในใใใๅฏพๅฟใใใใผใซ้ขๆฐใๅค้จAPIใๅฎ่กใใใพใใใใฎ็ตๆใๅใณใจใผใธใงใณใใซๆปใใๆฌกใฎในใใใใฎใใญใณใใใซ็ตใฟ่พผใพใใใซใผใใ็ถใใพใใ
RAGใ็ตใฟ่พผใๅ ดๅใฏใใจใผใธใงใณใใๅฟ ่ฆใซๅฟใใฆๆค็ดขใใผใซใๅผใณๅบใใใฆใผใถใผใฎ่ณชๅใใฟในใฏใซ้ข้ฃใใใใญใฅใกใณใใใใฏใใซใใผใฟใใผในใใๅๅพใใพใใๅๅพใใใใญในใใฏใLLMใฎใณใณใใญในใใซ็ตใฟ่พผใพใใไบๅฎใใผในใฎๅ็ญใๅคๆญใๆฏใใพใใใกใขใชในใใขใฏใใฆใผใถใผใใจใฎ้ทๆ็ใชๆ ๅ ฑใใฟในใฏใฎไธญ้็ถๆ ใไฟๆใใๆฌกๅไปฅ้ใฎใคใณใฟใฉใฏใทใงใณใงใๆดป็จใใใพใใ
ใใฎใใใชๆง้ ใๆ่ญใใใใจใงใใใฉใใๅ ใซไฝใใใฉใใๅพใใๅทฎใๆฟใๅฏ่ฝใซไฟใคใใใจใใ่จญ่จๅคๆญใใใใใใชใใพใใใใจใใฐใๆๅใฏๅ็ดใชRDBMSใใกใขใชในใใขใจใใฆไฝฟใใๅพใใๅฐ็จใฎใใฏใใซใใผใฟใใผในใใญใฃใใทใฅๅฑคใ่ฟฝๅ ใใใจใใฃใๆฎต้็ใชใขใใญใผใใๅฏ่ฝใซใชใใพใใ
ๅฎ่ฃ ๆๆฎตใจใใฆใฏใๅ็คพใใณใใฅใใใฃใๆไพใใใจใผใธใงใณใใใฌใผใ ใฏใผใฏใใฏใผใฏใใญใผใจใณใธใณใๅฉ็จใใๆนๆณใจใ่ชๅใง่ใใชใผใฑในใใฌใผใทใงใณใฌใคใคใผใๆธใๆนๆณใใใใพใใใฉใกใใ้ธใถใซใใใใๆๅใใๅฎ็งใชๅบ็คใไฝใใใจใใชใใใใจใๆๅใฎ้ตใงใใ
ใใฌใผใ ใฏใผใฏใ้ธใถ้ใซใฏใๅฏพๅฟใใฆใใLLMใใญใใคใใใใผใซ้ฃๆบใฎใใใใใในใใผใ็ฎก็ใฎไป็ตใฟใใญใฐใใขใใฟใชใณใฐใฎๆฉ่ฝใชใฉใ็ขบ่ชใใพใใใพใใใณใผใใฎ่ชญใฟใใใใๆกๅผตใฎใใใใใ้่ฆใงใใใจใผใธใงใณใใฎๆฏใ่ใใ็ดฐใใๅถๅพกใใใใชใๅ ด้ขใฏๅฟ ใ่จชใใใใใใใฉใใฏใใใฏในใซ่ฆใใใใฌใผใ ใฏใผใฏใใใใไธญ่บซใ็่งฃใใใใใใฎใ้ธใถๆนใ้ทๆ็ใซใฏๅฎๅ จใงใใ
ๆๅใฎใใญใใฟใคใใจใใฆใฏใไธใคใฎๆ็ขบใชใฆใผในใฑใผในใซ็นๅใใใจใผใธใงใณใใไฝใใฎใใใใงใใใใใใจใใฐใใฆใงใๆค็ดขใจ็คพๅ RAGใ็ตใฟๅใใใฆใฌใใผใ่ๆกใไฝใใชใตใผใใจใผใธใงใณใใใ็คพๅ ใฎFAQใๅ็ งใใชใใๅพๆฅญๅกใฎๅใๅใใใซ็ญใใใใซใใในใฏใจใผใธใงใณใใชใฉใงใใใใฎๆฎต้ใงใฏใ่ช่จผใ่ค้ใชๆจฉ้็ฎก็ใในใฑใผใชใณใฐๆฆ็ฅใชใฉใฏๆไฝ้ใซใจใฉใใใจใซใใใจใผใธใงใณใใฎใๆ่งฆใใใใใผใ ใงๅ ฑๆใใใใจใ็ฎ็ใซใชใใพใใ
ใใญใใฟใคใใฎไธญใงใฏใใใผใซใไบใไธๅใซ็ตใใใกใขใชใใปใใทใงใณๅ ใฎ็ฐกๆใชใใฎใซ็ใใใจๅฎ่ฃ ใๆฅฝใซใชใใพใใใใฎไปฃใใใใญใฐใไธๅฏงใซๆฎใใใฉใฎใใใชใใญใณใใใใฉใฎใใใชๅบๅใ็ใใ ใฎใใใใผใซใฎๅผใณๅบใใๆๅใใใฎใๅคฑๆใใใฎใใๅฏ่ฆๅใใไป็ตใฟใๆดใใฆใใใจใๅพใฎๆนๅใซๅฝน็ซใกใพใใ
LLMใจใผใธใงใณใ้็บใงใจใณใธใใขใๆธๆใใใใใฎใใใในใใฎ้ฃใใใงใใๅใๅ ฅๅใซๅฏพใใฆๅใๅฟ็ญใ่ฟใใชใใใจใๅคใใๅพๆฅใฎๅไฝใในใใในใใใใทใงใใใในใใฎๆๆณใใใฎใพใพ้ฉ็จใใใใจใฏๅฐ้ฃใงใใใใใง้่ฆใซใชใใฎใใใทใใชใชใใผในใฎ่ฉไพกใจใ่ชๅ่ฉไพกใจไบบๆ่ฉไพกใฎ็ตใฟๅใใใงใใ
ๅ ทไฝ็ใซใฏใๅ ธๅ็ใชใฟในใฏใทใใชใชใ่คๆฐ็จๆใใใใใใใซใคใใฆๆๅพ ใใใๆฏใ่ใใฎๆกไปถใๅฎ็พฉใใพใใใใจใใฐใใใฎๅใๅใใใซๅฏพใใฆใฏใ็คพๅ ่ฆ็จใฎ่ฉฒๅฝ็ฎๆใๅผ็จใใคใคใไธใคใฎ้ธๆ่ขใๆ็คบใใใใจใใฃใใฌใใซใงใใใจใผใธใงใณใใๅฎๆ็ใซใใใใฎใทใใชใชใซๅฏพใใฆๅฎ่กใใLLMใ็จใใ่ชๅ่ฉไพกใใซใผใซใใผในใฎใใงใใซใผใงๅๅฆใๅคๅฎใใพใใใใใซๅ ใใฆใ้่ฆใชใทใใชใชใซใคใใฆใฏไบบๆใซใใใฌใใฅใผใ่กใใไธป่ฆณ็ใชๅ่ณชใ็ขบ่ชใใพใใ
้็บใใญใปในใจใใฆใฏใใใญใณใใใใใผใซๆงๆใ้ ป็นใซๅคๆดใงใใใใใซใใคใคใๅคๆดใฎๅฝฑ้ฟ็ฏๅฒใๆๆกใใใใใฎ่ฉไพกใธใงใใCIใซ็ตใฟ่พผใใจใใใงใใใใใจใผใธใงใณใใฎ่จญๅฎใๅคๆดใใใใณใซใใทใใชใช่ฉไพกใ่ตฐใใใ้่ฆๆๆจใฎๅคๅใๅฏ่ฆๅใใพใใใใใซใใใใไธใคใฎใฆใผในใฑใผในใๆนๅใใใคใใใใๅฅใฎใฆใผในใฑใผในใๅฃๅใใใฆใใพใฃใใใจใใฃใไบๆ ใๆฉๆใซๆค็ฅใงใใพใใ
ๆๅพใซใ้็จใใงใผใบใงใฏใใฆใผใถใผใฎใใฃใผใใใใฏใจใญใฐๅๆใ้่ฆใชๆ ๅ ฑๆบใซใชใใพใใใฆใผใถใผใซ็ฐกๅใซใใใฎๅ็ญใฏๅฝนใซ็ซใฃใใใใใฉใใๅ้กใ ใฃใใใใ้ไฟกใใฆใใใใใคใณใฟใผใใงใผในใ็จๆใใใใฎๆ ๅ ฑใใญใฐใจ็ดใฅใใฆๅๆใใใใจใงใๆนๅใฎๅชๅ ้ ไฝใๆฑบใใใใจใใงใใพใใใจใณใธใใขใฏใใขใใซใใใญใณใใใฎ่ชฟๆดใ ใใงใชใใใใผใซใฎ่ฟฝๅ ใปๅ้คใใกใขใชๆฆ็ฅใฎ่ฆ็ดใใใจใฉใผๅฆ็ใฎๅผทๅใชใฉใใทในใใ ๅ จไฝใๅฏพ่ฑกใจใใๆนๅใ็ถ็ถ็ใซ่กใใใจใซใชใใพใใ
LLMใจใผใธใงใณใๅฎ่ฃ ใฏใๅใชใAPIๅผใณๅบใใฎใฉใใใผไฝใใงใฏใชใใๆจ่ซใทในใใ ใใฏใผใฏใใญใผใใใผใฟๅบ็คใUXใไบคๅทฎใใ็ทๅๆ ผ้ๆใฎใใใช้ ๅใงใใใใใใๅฐใใชใใญใใฟใคใใใๅงใใใขใผใญใใฏใใฃใฎ้ชจๆ ผใๆ่ญใใชใใๅพใ ใซๆกๅผตใใฆใใใฐใ็พๅฎ็ใชใณในใใงๆฌ็ช้็จใซ่ใใใใจใผใธใงใณใใ่ฒใฆใฆใใใใจใใงใใพใใ
ใพใๆผใใใฆใใใใใฎใฏใLLMใจใผใธใงใณใใฎใชในใฏใฏใๅไธใฎๆ่ก็ๅ้กใงใฏใชใใ่คๆฐใฎใฌใคใคใผใซใพใใใฃใฆใใใจใใ็นใงใใใฒใจใคใฏใLLMใใฎใใฎใๆใคๅนป่ฆใฎๅ้กใงใใใใฃใจใใใใใ่ชคใฃใๆ ๅ ฑใ่ชไฟกๆบใ ใซ่ชใฃใฆใใพใๆฏใ่ใใฏใใ็ฅใใใฆใใพใใใใจใผใธใงใณใใจใใฆๅค้จใใผใซใซใขใฏใปในใใๅ ดๅใใใฎ่ชคใใๅ ทไฝ็ใชใขใฏใทใงใณใซใคใชใใฃใฆใใพใๅฏ่ฝๆงใใใใพใใๅญๅจใใชใAPIใจใณใใใคใณใใๅผใณๅบใใใจใใใใ่ชคใฃใๆกไปถใงใใผใฟใๆฝๅบใใใใใใใจใฏใๆฅญๅใใญใปในใซ็ดๆฅ็ใชๅฝฑ้ฟใไธใใพใใ
ๆฌกใซใใปใญใฅใชใใฃใจใใฉใคใใทใผใฎใชในใฏใใใใพใใใจใผใธใงใณใใฏใใฆใผใถใผใฎๅ ฅๅๅ ๅฎนใ ใใงใชใใ็คพๅ ใฎๅ็จฎใทในใใ ใใใญใฅใกใณใใซใขใฏใปในใใใใจใๅคใใใใฎ้็จใงๆฉๅฏๆ ๅ ฑใๆฑใใพใใใใใใฎๆ ๅ ฑใใขใใซๆไพ่ ใใญใฐใทในใใ ใ้ใใฆๅค้จใซ้ไฟกใใใๅ ดๅใๆ ๅ ฑ็ฎก็ไธใฎใชในใฏใ็ใใพใใใพใใใจใผใธใงใณใใๆปๆ่ ใซๆช็จใใใๅฏ่ฝๆงใ็ก่ฆใงใใพใใใใใจใใฐใใใญใณใใใคใณใธใงใฏใทใงใณๆปๆใซใใฃใฆใจใผใธใงใณใใฎ่กๅๆน้ใๆธใๆใใใใๆๅณใใชใๆ ๅ ฑ้ไฟกใๆไฝใ่กใใใใจใใฃใใทใใชใชใงใใ
ใใใซใๆณ็่ฒฌไปปใฎๅ้กใใใใพใใใจใผใธใงใณใใ็ๆใใๅ ๅฎนใๅฎ่กใใใขใฏใทใงใณใๆณไปค้ๅใๅฅ็ด้ๅใซใคใชใใฃใๅ ดๅใ่ชฐใ่ฒฌไปปใ่ฒ ใใฎใใใขใใซๆไพ่ ใใใจใผใธใงใณใใ็ตใฟ่พผใใ ใตใผใในๆไพ่ ใใใใใจใๆ็ต็ใซๅฉ็จใใใฆใผใถใผใใใใฎๅใใซๆ็ขบใช็ญใใๅบใฆใใชใ้ ๅใๅคใใใฌใใใณใน่จญ่จใฎ้ฃใใใๅขใใฆใใพใใ
ใใใใใชในใฏใซๅฏพๅฆใใใใใซใฏใๆ่ก็ใป้็จ็ใชใฌใผใใฌใผใซใๅคๅฑค็ใซ่จญ่จใใๅฟ ่ฆใใใใพใใใใฎไธญๅฟใซใใใฎใๆจฉ้็ฎก็ใงใใใจใผใธใงใณใใซไธใใๆจฉ้ใฏใๅๅใจใใฆๅฟ ่ฆๆๅฐ้ใซใจใฉใใใใพใใฏ่ชญใฟๅใๅฐ็จใใๅงใใใใใจใๅฎๅ จใชใขใใญใผใใงใใใใจใใฐใCRMใทในใใ ใจใฎ้ฃๆบใงใฏใๆๅใฏ้กงๅฎขๆ ๅ ฑใฎๅ็ งใฎใฟใซ็ตใใไธๅฎๆ้ๅ้กใใชใใใจใ็ขบ่ชใใใใใงใใฌใณใผใๆดๆฐใฎๆจฉ้ใ้ๅฎ็ใซ่งฃๆพใใฆใใใจใใฃใๆฎต้็ใช่จญ่จใ่ใใใใพใใ
ใพใใๅฑ้บๅบฆใฎ้ซใใขใฏใทใงใณใซใคใใฆใฏใๅฟ ใไบบ้ใฎๆฟ่ชใๆใใฏใผใฏใใญใผใซใใใใจใ้่ฆใงใใ้ซ้กใชๆฏๆใๆ็คบใๅฅ็ดๆกไปถใฎๅคๆดใๅฏพๅค็ใช้่ฆๆๆธใฎ้ไปใชใฉใฏใใจใผใธใงใณใใใใฉใใใๆๆกใ่กใใใจใฏใใฃใฆใใๆ็ตๅฎ่กใฏไบบ้ใ่กใๅฝขใซใในใใงใใใใฎใไบบ้ใฎๆฟ่ชในใใใใใใจใผใธใงใณใใฎใใญใผใฎไธญใซๆ็คบ็ใซ็ตใฟ่พผใใใจใงใ่ชคๅไฝใฎๅฝฑ้ฟใ้ๅฎใงใใพใใ
ใใญใณใใใคใณใธใงใฏใทใงใณใใใผใฟๆผใใใธใฎๅฏพ็ญใจใใฆใฏใๅ ฅๅใจๅบๅใฎใใฃใซใฟใชใณใฐใๆฌ ใใใพใใใใฆใผใถใผๅ ฅๅใๅค้จใตใคใใใๅๅพใใใใญในใใใใฎใพใพใทในใใ ใใญใณใใใซๅใ่พผใพใชใใๅค้จใซ้ไฟกใใฆใฏใชใใชใๆ ๅ ฑใๅบๅใซๅซใพใใฆใใชใใใใใงใใฏใใใ็นๅฎใฎใญใผใฏใผใใใใฟใผใณใๆคๅบใใใๅ ดๅใซใฏๅฆ็ใๅๆญขใใฆใขใฉใผใใไธใใใจใใฃใไป็ตใฟใๆๅนใงใใใใใใฏใใขใใซใฎๅคๅดใฎใขใใชใฑใผใทใงใณใฌใคใคใผใงๅฎ่ฃ ใงใใใใจใๅคใใใฌใผใใฌใผใซใฎ้่ฆใชไธ้จใซใชใใพใใ
ใฌใผใใฌใผใซใ่จญ่จใใใจใใฆใใไธๅบฆๅฐๅ ฅใใใจใผใธใงใณใใใใฎใพใพๆพ็ฝฎใใฆใใใใใงใฏใใใพใใใใจใผใธใงใณใใฏๅญฆ็ฟๆธใฟใขใใซใฎไธใซๆใ็ซใฃใฆใใใจใฏใใใใใฎๆๅใฏใณใณใใญในใใ็ฐๅขใซใใฃใฆๅคๅใใพใใใใใใฃใฆใ้็จ้ๅงๅพใ็ถ็ถ็ใชใขใใฟใชใณใฐใจๆนๅใๅฟ ่ฆใงใใ
ใขใใฟใชใณใฐใฎๅฏพ่ฑกใซใฏใๆๅใใใฟในใฏใจๅคฑๆใใใฟในใฏใฎๆฏ็ใใฆใผใถใผใซใใไฟฎๆญฃ้ ปๅบฆใใจใฉใผใไพๅคใฎ็บ็ใใฟใผใณใใปใญใฅใชใใฃไธใฎ็็พฉใฎใใๆๅใชใฉใๅซใพใใพใใ็นใซ้่ฆใชใฎใฏใใ้ๅคงไบๆ ใซใคใชใใๆๅใฎๆช้ไบไพใใๆฉๆใซๆค็ฅใใใใจใงใใใใจใใฐใใจใผใธใงใณใใ็ฆๆญขใใใฆใใๅค้จใใกใคใณใธใฎใขใฏใปในใ่ฉฆใฟใใใใฌใผใใฌใผใซใซใใใใญใใฏใใใใจใใใญใฐใฏใ่จญ่จใฎๆนๅไฝๅฐใ็คบใ่ฒด้ใชใทใฐใใซใงใใ
ใพใใ่ฒฌไปปใฎๆ็ขบๅใใฌใใใณในใฎไธ้จใงใใ็ต็นๅ ้จใซใใใฆใฏใใจใผใธใงใณใใฎ่จญ่จใจ้็จใซใคใใฆๆ็ต่ฒฌไปปใ่ฒ ใใชใผใใผใๆ็คบใใๅคๆด็ฎก็ใใคใณใทใใณใๅฏพๅฟใฎใใญใปในใๅฎ็พฉใใฆใใๅฟ ่ฆใใใใพใใๅค้จๅใใซใฏใๅฉ็จ่ฆ็ดใใใฉใคใใทใผใใชใทใผใซใใใฆใใจใผใธใงใณใใฎๆฉ่ฝใจ้็ใใฆใผใถใผๅดใซๆฑใใใใ็ขบ่ช็พฉๅใชใฉใๅใใใใใ่ชฌๆใใใใจใๆฑใใใใพใใ
ๅฎๅ จใชLLMใจใผใธใงใณใใจใฏใใชในใฏใใผใญใฎใจใผใธใงใณใใงใฏใชใใใชในใฏใๅฏ่ฆๅใใใใณใณใใญใผใซๅฏ่ฝใชๅฝขใง้็จใใใฆใใใจใผใธใงใณใใงใใๅนป่ฆใ่ชคๅคๆญใๅฎๅ จใซๆ้คใใใใจใฏใงใใชใไปฅไธใใใใใๅๆใจใใฆใใฉใใงๆญขใใใฉใใงไบบ้ใซใคใชใใฎใใๅ้กใ็บ็ใใใจใใซใฉใๆค็ฅใใใฉใๅญฆใณใซๅคใใใฎใใจใใใฌใใใณในใฎๆ ็ตใฟใใใใ่จญ่จใจๅใใใใ้่ฆใซใชใฃใฆใใใพใใ
Evidence shows that certain people have been targeted by malicious actors, often linked to governments or state-backed groups.
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According to Gartner, only 5% of automakers will continue expanding AI investments at current levels by 2029, a steep fall from more than 95% today.
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Common wisdom has long held that a cloud-first approach will gain CIOs benefits such as agility, scalability, and cost-efficiency for their applications and workloads. While cloud remains most IT leadersโ preferred infrastructure platform, many are rethinking their cloud strategies, pivoting from cloud-first to โcloud-smartโ by choosing the best approach for specific workloads rather than just moving everything off-premises and prioritizing cloud over other considerations for new initiatives.
Cloud cost optimization is one factor motivating this rethink, with organizations struggling to control escalating cloud expenses amid rapid growth. An estimated 21% of enterprise cloud infrastructure spend, equivalent to $44.5 billion in 2025, is wasted on underutilized resources โ with 31% of CIOs wasting half of their cloud spend, according to a recent survey from VMware.
The full rush to the cloud is over, says Ryan McElroy, vice president of technology at tech consultancy Hylaine. Cloud-smart organizations have a well-defined and proven process for determining which workloads are best suited for the cloud.
For example, โsomething that must be delivered very quickly and support massive scale in the future should be built in the cloud,โ McElroy says. โSolutions with legacy technology that must be hosted on virtual machines or have very predictable workloads that will last for years should be deployed to well-managed data centers.โ
The cloud-smart trend is being influenced by better on-prem technology, longer hardware cycles, ultra-high margins with hyperscale cloud providers, and the typical hype cycles of the industry, according to McElroy. All favor hybrid infrastructure approaches.
However, โAI has added another major wrinkle with siloed data and compute,โ he adds. โMany organizations arenโt interested in or able to build high-performance GPU datacenters, and need to use the cloud. But if theyโve been conservative or cost-averse, their data may be in the on-prem component of their hybrid infrastructure.โ
These variables have led to complexity or unanticipated costs, either through migration or data egress charges, McElroy says.
He estimates that โonly 10% of the industry has openly admitted theyโre movingโ toward being cloud-smart. While that number may seem low, McElroy says it is significant.
โThere are a lot of prerequisites to moderate on your cloud stance,โ he explains. โFirst, you generally have to be a new CIO or CTO. Anyone who moved to the cloud is going to have a lot of trouble backtracking.โ
Further, organizations need to have retained and upskilled the talent who manage the datacenter they own or at the co-location facility. They must also have infrastructure needs that outweigh the benefits the cloud provides in terms of raw agility and fractional compute, McElroy says.
Procter & Gamble embraced a cloud-first strategy when it began migrating workloads aboutย eight years ago, says Paola Lucetti, CTO and senior vice president. At that time, the mandate was that all new applications would be deployed in the public cloud, and existing workloads would migrate from traditional hosting environments to hyperscalers, Lucetti says.
โThis approach allowed us to modernize quickly, reduce dependency on legacy infrastructure, and tap into the scalability and resilience that cloud platforms offer,โ she says.
Today, nearly all P&Gโs workloads run on cloud. โWe chooseย to keep selected workloadsย outside of the public cloudย because of latency or performance needs that we regularly reassess,โ Lucetti says. โThis foundation gave us speed and flexibility during a critical phase of digital transformation.โ
As the companyโs cloud ecosystem has matured, so have its business priorities. โCost optimization, sustainability, and agility became front and center,โ she says. โCloud-smart for P&G means selecting and regularly reassessing the right hyperscaler for the right workload, embedding FinOps practices for transparency and governance, and leveraging hybrid architectures to support specific use cases.โ
This approach empowers developers through automation, AI, and agentic to drive value faster, Lucetti says. โThis approach isnโt just technical โ itโs cultural. It reflects a mindset of strategic flexibility, where technology decisions align with business outcomes.โ
AI represents a huge potential spend requirement and raises the stakes for infrastructure strategy, says McElroy.
โRenting servers packed with expensive Nvidia GPUs all day every day for three years will be financially ruinous compared to buying them outright,โ he says, โbut the flexibility to use next yearโs models seamlessly may represent a strategic advantage.โ
Cisco, for one, has become far more deliberate about what truly belongs in the public cloud, says Nik Kale, principal engineer and product architect. Cost is one factor, but the main driver is AI data governance.
โBeing cloud-smart isnโt about repatriation โ itโs about aligning AIโs data gravity with the right control plane,โ he says.
IT has parsed out what should be in a private cloud and what goes into a public cloud. โTraining and fine-tuning large models requires strong control over customer and telemetry data,โ Kale explains. โSo we increasingly favor hybrid architectures where inference and data processing happen within secure, private environments, while orchestration and non-sensitive services stay in the public cloud.โ
Ciscoโs cloud-smart strategy starts with data classification and workload profiling. Anything with customer-identifiable information, diagnostic traces, and model feedback loops are processed within regionally compliant private clouds, he says.
Then there are โstateless services, content delivery, and telemetry aggregation that benefit from public-cloud elasticity for scale and efficiency,โ Kale says.
Ciscoโs approach also involves โpackaging previously cloud-resident capabilities for secure deployment within customer environments โ offering the same AI-driven insights and automation locally, without exposing data to shared infrastructure,โ he says. โThis gives customers the flexibility to adopt AI capabilities without compromising on data residency, privacy, or cost.โ
These practices have improved Ciscoโs compliance posture, reduced inference latency, and yielded measurable double-digit reductions in cloud spend, Kale says.
One area where AI has fundamentally changed their approach to cloud is in large-scale threat detection. โEarly versions of our models ran entirely in the public cloud, but once we began fine-tuning on customer-specific telemetry, the sensitivity and volume of that data made cloud egress both costly and difficult to govern,โ he says. โMoving the training and feedback loops into regional private clouds gave us full auditability and significantly reduced transfer costs, while keeping inference hybrid so customers in regulated regions received sub-second response times.โ
IT saw a similar issue with its generative AI support assistant. โInitially, case transcripts and diagnostic logs were processed in public cloud LLMs,โ Kale says. โAs customers in finance and healthcare raised legitimate concerns about data leaving their environments, we re-architected the capability to run directly within their [virtual private clouds] or on-prem clusters.โ
The orchestration layer remains in the public cloud, but the sensitive data never leaves their control plane, Kale adds.
AI has also reshaped how telemetry analytics is handled across Ciscoโs CX portfolio. IT collects petabyte-scale operational data from more than 140,000 customer environments.
โWhen we transitioned to real-time predictive AI, the cost and latency of shipping raw time-series data to the cloud became a bottleneck,โ Kale says. โBy shifting feature extraction and anomaly detection to the customerโs local collector and sending only high-level risk signals to the cloud, we reduced egress dramatically while improving model fidelity.โ
In all instances, โAI made the architectural trade-offs clear: Specific workloads benefit from public-cloud elasticity, but the most sensitive, data-intensive, and latency-critical AI functions need to run closer to the data,โ Kale says. โFor us, cloud-smart has become less about repatriation and more about aligning data gravity, privacy boundaries, and inference economics with the right control plane.โ
Like P&G, World Insurance Associates believes cloud-smart translates to implementing a FinOps framework. CIO Michael Corrigan says that means having an optimized, consistent build for virtual machines based on the business use case, and understanding how much storage and compute is required.
Those are the main drivers to determine costs, โso we have a consistent set of standards of what will size our different environments based off of the use case,โ Corrigan says. This gives World Insurance what Corrigan says is an automated architecture.
โThen we optimize the build to make sure we have things turned on like elasticity. So when services arenโt used typically overnight, they shut down and they reduce the amount of storage to turn off the amount of computeโ so the company isnโt paying for it, he says. โIt starts with the foundation of optimization or standards.โ
World Insurance works with its cloud providers on different levels of commitment. With Microsoft, for example, the insurance company has the option to use virtual machines, or what Corrigan says is a โreserved instance.โ By telling the provider how many machines they plan to consume or how much they intend to spend, he can try to negotiate discounts.
โThatโs where the FinOps framework has to really be in place โฆ because obviously, you donโt want to commit to a level of spend that you wouldnโt consume otherwise,โ Corrigan says. โItโs a good way for the consumer or us as the organization utilizing those cloud services, to get really significant discounts upfront.โ
World Insurance is using AI for automation and alerts. AI tools are typically charged on a compute processing model, โand what you can do is design your query so that if it is something thatโs less complicated, itโs going to hit a less expensive execution pathโ and go to a small language model (SLM), which doesnโt use as much processing power, Corrigan says.
The user gets a satisfactory result, and โthere is less of a cost because youโre not consuming as much,โ he says.
Thatโs the tactic the company is taking โ routing AI queries to the less expensive model. If there is a more complicated workflow or process, it will be routed to the SLM first โand see if it checks the box,โ Corrigan says. If its needs are more complex, it is moved to the next stage, which is more expensive, and generally involves an LLM that requires going through more data to give the end user what theyโre looking for.
โSo we try to manage the costs that way as well so weโre only consuming whatโs really needed to be consumed based on the complexity of the process,โ he says.
Hylaineโs McElroy says CIOs and CTOs need to be more open to discussing the benefits of hybrid infrastructure setups, and how the state of the art has changed in the past few years.
โMany organizations are wrestling with cloud costs they know instinctively are too high, but there are few incentives to take on the risky work of repatriation when a CFO doesnโt know what savings theyโre missing out on,โ he says.
Lucetti characterizes P&Gโs cloud strategy as โa living framework,โ and says that over the next few years, the company will continue to leverage the right cloud capabilities to enable AI and agentic for business value.
โThe goal is simple: Keep technology aligned with business growth, while staying agile in a rapidly changing digital landscape,โ she says. โCloud transformation isnโt a destination โ itโs a journey. At P&G, we know that success comes from aligning technology decisions with business outcomes and by embracing flexibility.โ
When it comes to AI adoption, the gap between ambition and execution can be impossible to bridge. Companies are trying to weave the tech into products, workflows, and strategies, but good intentions often collapse under the weight of the day-to-day realities from messy data and lack of a clear plan.
โThatโs the challenge we see most often across the global manufacturers we work with,โ says Rob McAveney, CTO at software developer Aras. โMany organizations assume they needAI, when the real starting point should be defining the decision you want AI to support, and making sure you have the right data behind it.โ
Nearly two-thirds of leaders say their organizations have struggled to scale AI across the business, according to a recent McKinsey global survey. Often, they canโt move beyond tests of pilot programs, a challenge thatโs even more pronounced among smaller organizations. Often, pilots fail to mature, and investment decisions become harder to justify.
A typical issue is the data simply isnโt ready for AI. Teams try to build sophisticated models on top of fragmented sources or messy data, hoping the technology will smooth over the cracks.
โFrom our perspective, the biggest barriers to meaningful AI outcomes are data quality, data consistency, and data context,โ McAveney says. โWhen data lives in silos or isnโt governed with shared standards, AI will simply reflect those inconsistencies, leading to unreliable or misleading outcomes.โ
Itโs an issue that impacts almost every sector. Before organizations double down on new AI tools, they must first build stronger data governance, enforce quality standards, and clarify who actually owns the data meant to fuel these systems.
In the rush to adopt AI, many organizations forget to ask the fundamental questionofwhat problem actually needs to be solved. Without that clarity, itโs difficult to achieve meaningful results.
Anurag Sharma, CTO of VyStar Credit Union believes AI is just another tool thatโs available to help solve a given business problem, and says every initiative should begin with a clear, simple statement of the business outcome itโs meant to deliver. He encourages his team to isolate issues AI could fix, and urges executives to understand what will change and who will be affected before anything moves forward.
โCIOs and CTOs can keep initiatives grounded by insisting on this discipline, and by slowing down the conversation just long enough to separate the shiny from the strategic,โ Sharma says.
This distinction becomes much easier when an organization has an AI COE or a dedicated working group focused on identifying real opportunities. These teams help sift through ideas, set priorities, and ensure initiatives are grounded in business needs rather than buzz.
The group should also include the people whose work will be affected by AI, along with business leaders, legal and compliance specialists, and security teams. Together, they can define baseline requirements that AI initiatives must meet.
โWhen those requirements are clear up front, teams can avoid pursuing AI projects that look exciting but lack a real business anchor,โ says Kayla Underkoffler, director of AI security and policy advocacy at security and governance platform Zenity.
She adds that someone in the COE should have a solid grasp of the current AI risk landscape. That person should be ready to answer critical questions, knowing what concerns need to be addressed before every initiative goes live.
โA plan could have gaping cracks the team isnโt even aware of,โ Underkoffler says. โItโs critical that security be included from the beginning to ensure the guardrails and risk assessment can be added from the beginning and not bolted on after the initiative is up and running.โ
In addition, there should be clear, measurable business outcomes to make sure the effort is worthwhile. โEvery proposal must define success metrics upfront,โ says Akash Agrawal, VP of DevOps and DevSecOps at cloud-based quality engineering platform LambdaTest, Inc. โAI is never explored, itโs applied.โ
He recommends companies build in regular 30- or 45-day checkpoints to ensure the work continues to align with business objectives. And if the results donโt meet expectations, organizations shouldnโt hesitate to reassess and make honest decisions, he says. Even if that means walking away from the initiative altogether.
Yet even when the technology looks promising, humans still need to remain in the loop. โIn an early pilot of our AI-based lead qualification, removing human review led to ineffective lead categorization,โ says Shridhar Karale, CIO at sustainable waste solutions company, Reworld. โWe quickly retuned the model to include human feedback, so it continually refines and becomes more accurate over time.โ
When decisions are made without human validation, organizations risk acting on faulty assumptions or misinterpreted patterns. The aim isnโt to replace people, but to build a partnership in which humans and machines strengthen one other.
Ensuring data is managed effectively is an often overlooked prerequisite for making AI work as intended. Creating the right conditions means treating data as a strategic asset: organizing it, cleaning it, and having the right policies in place so it stays reliable over time.
โCIOs should focus on data quality, integrity, and relevance,โ says Paul Smith, CIO at Amnesty International. His organization works with unstructured data every day, often coming from external sources. Given the nature of the work, the quality of that data can be variable. Analysts sift through documents, videos, images, and reports, each produced in different formats and conditions. Managing such a high volume of messy, inconsistent, and often incomplete information has taught them the importance of rigor.
โThereโs no such thing as unstructured data, only data that hasnโt yet had structure applied to it,โ Smith says. He also urges organizations to start with the basics of strong, everyday data-governance habits. That means checking whether the data is relevant, and ensuring itโs complete, accurate, and consistent, and outdated information can skew results.
Smith also emphasizes the importance of verifying data lineage. That includes establishing provenance โ knowing where the data came from and whether its use meets legal and ethical standards โ and reviewing any available documentation that details how it was collected or transformed.
In many organizations, messy data comes from legacy systems or manual entry workflows. โWe strengthen reliability by standardizing schemas, enforcing data contracts, automating quality checks at ingestion, and consolidating observability across engineering,โ says Agrawal.
When teams trust the data, their AI outcomes improve. โIf you canโt clearly answer where the data came from and how trustworthy is it, then you arenโt ready,โ Sharma adds. โItโs better to slow down upfront than chase insights that are directionally wrong or operationally harmful, especially in the financial industry where trust is our currency.โ
Karale says that at Reworld, theyโve created a single source of truth data fabric, and assigned data stewards to each domain. They also maintain a living data dictionary that makes definitions and access policies easy to find with a simple search. โEach entry includes lineage and ownership details so every team knows whoโs responsible, and they can trust the data they use,โ Karale adds.
AI has a way of amplifying whatever patterns it finds in the data โ the helpful ones, but also the old biases organizations would rather leave behind. Avoiding that trap starts with recognizing that bias is often a structural issue.
CIOs can do a couple of things to prevent problems from taking root. โVet all data used for training or pilot runs and confirm foundational controls are in place before AI enters the workflow,โ says Underkoffler.
Also, try to understand in detail how agentic AI changes the risk model. โThese systems introduce new forms of autonomy, dependency, and interaction,โ she says. โControls must evolve accordingly.โ
Underkoffler also adds that strong governance frameworks can guide organizations on monitoring, managing risks, and setting guardrails. These frameworks outline whoโs responsible for overseeing AI systems, how decisions are documented, and when human judgment must step in, providing structure in an environment where the technology is evolving faster than most policies can keep up.
And Karale says that fairness metrics, such as disparate impact, play an important role in that oversight. These measures help teams understand whether an AI system is treating different groups equitably or unintentionally favoring one over another. These metrics could be incorporated into the model validation pipeline.
Domain experts can also play a key role in spotting and retraining models that produce biased or off-target outputs. They understand the context behind the data, so theyโre often the first to notice when something doesnโt look right. โContinuous learning is just as important for machines as it is for people,โ says Karale.
Amnesty Internationalโs Smith agrees, saying organizations need to train their people continuously to help them pick out potential biases. โRaise awareness of risks and harms,โ he says. โThe first line of defense or risk mitigation is human.โ
The timing of this upgrade push comes during a wave of reported Windows issues.
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SAS๋ 2025๋ ์ ๋์๋ณด๋ฉด์ AI ๊ธฐ์ ์ ๋น ๋ฅธ ๋ฐ์ ๊ณผ ๋ค์ํ ์ฑ๊ณผ๋ฅผ ์ธ์ ํ๋ฉด์๋, ์ ์ฌ์ ์ธ AI ๊ฑฐํ, ์๋์ง ์ฌ์ฉ ์ฆ๊ฐ์ ๋ฐ๋ฅธ ๋ถ๋ด, ์์ฑํ AI ํ์ผ๋ฟ ํ๋ก์ ํธ์ ๊ธฐ๋ ์ดํ ์ฑ๊ณผ ๋ฑ ์ฌ๋ฌ ์ฐ๋ ค ์์๊ฐ ์กด์ฌํ๋ค๊ณ ๋ฐํ๋ค. SAS ์ ๋ฌธ๊ฐ๋ค์ 2026๋ ์ด AI๋ก๋ถํฐ ์ค์ง์ ์ธ ROI(ํฌ์์์ต๋ฅ )๋ฅผ ํ๋ณดํ๊ณ , ์ค๋ฆฌ์ ยท๊ฒฝ์ ์ ๊ณผ์ ๋ฅผ ๋ณธ๊ฒฉ์ ์ผ๋ก ํด๊ฒฐํด์ผ ํ๋ ์ค์ํ ์๊ธฐ๊ฐ ๋ ๊ฒ์ด๋ผ๊ณ ์ ๋งํ๋ค.
์์ผ๋ก์ ์ ๋ง์๋ ์ฐ๋ ค์ ํจ๊ป ์ ์คํ ๊ธฐ๋๊ฐ๋ ๊ณต์กดํ๋ค. SAS ์ฃผ์ ๋ฆฌ๋๋ค์ AI ๋ฐ์ ์ ํต์ฌ ์์ธ์ผ๋ก โ์ฑ ์์ฑโ์ ๊ฐ์กฐํ๋ฉฐ, AI ๊ณต๊ธ์๋ฟ ์๋๋ผ ์ด๋ฅผ ํ์ฉํ๋ ์กฐ์ง ๋ชจ๋๊ฐ ์ฑ ์ ์๋ ๋ฐฉ์์ผ๋ก ๊ธฐ์ ์ ์ ์ฉํด์ผ ํ๋ค๊ณ ๋งํ๋ค. ๋ํ ๋ฐ์ดํฐ ๊ด๋ฆฌ์ ๊ธฐ๋ณธ์ ๊ฐํํ๊ณ ์ ๋ขฐํ ์ ์๋ AI๋ฅผ ๊ตฌ์ถํ๋ ๊ฒ์ด ๊ธฐ์ ์ฑ์ ๋จ๊ณ๋ก ๋์๊ฐ๊ณ ์กฐ์ง์ ์ญ๋์ ๊ฐํํ๋ฉฐ ํ์ ์๋๋ฅผ ๋์ด๋ ๋ฐ ์ค์ํ ๊ธฐ๋ฐ์ด ๋๋ค๊ณ ์ค๋ช ํ๋ค.
SAS์ ๋ฐ์ดํฐ ๋ฐ AI ๋ฆฌ๋๋ค์ด ์ ์ํ๋ 2026๋ ์ฃผ์ ์ ๋ง์ ์๋์ ๊ฐ๋ค.
์ด์คํ SAS์ฝ๋ฆฌ์ ๋ํ์ด์ฌ๋ โ์ ์ธ๊ณ์ ์ผ๋ก AI ํฌ์์ ๋ํ ROI์ ์ ๋ขฐ์ฑ ํ๋ณด ์๊ตฌ๊ฐ ๋์์ง๋ ๊ฐ์ด๋ฐ, ๊ตญ๋ด ๊ธฐ์ ๋ค๋ AI ๋์ ์ ๋ํด ๋จ๊ธฐ์ ยท์คํ์ ์ ๊ทผ์์ ์ค์ฅ๊ธฐ์ ยท์ ๋ต์ ๊ด์ ์ผ๋ก ์ ํํ๊ณ ์๋คโ๋ผ๊ณ ๋งํ๋ค. ๋ํ โ๋จ์ ์ ๋ฌด์ ์ ์ฉ๋๋ ๋๊ท๋ชจ ์ธ์ด ๋ชจ๋ธ(LLM, Large Language Models) ๊ธฐ๋ฐ ์์ฑํ AI์ ๋น์ฆ๋์ค ์์ต ๊ฐ์ ํจ๊ณผ์ ์๋ฌธ์ ์ ๊ธฐํ๋ ์กฐ์ง์ด ๋์ด๋๋ฉด์, ๋์์ผ๋ก ์์ด์ ํฑ AI๋ฅผ ๊ณ ๋ คํ๋ ์์ง์์ด ํ์ฐ๋๊ณ ์๋คโ๊ณ ์ค๋ช ํ๋ค.
๊ทธ๋ 2026๋ ๊ตญ๋ด ์์ฅ ์ ๋ง์ ๋ํด โ๊ธ์ต๊ถ์์๋ ๋ฆฌ์คํฌ ๊ด๋ฆฌ, ๋ด๋ถํต์ , ALM(์์ฐยท๋ถ์ฑ ์ข ํฉ๊ด๋ฆฌ) ๋ฑ ์ ๋ฌธ ์์ญ์์ AI ์ ์ฉ์ ํ๋ํด ์ค์ง์ ROI๋ฅผ ํ๋ณดํ๋ ค๋ ์๋๊ฐ ๋์ฑ ํ๋ฐํด์ง ๊ฒ์ด๋ฉฐ, ๊ณต๊ณต ๋ถ์ผ๋ ๋์งํธํ๋ซํผ์ ๋ถ 2.0์ ์ค์ฌ์ผ๋ก AIยทํด๋ผ์ฐ๋ยท๋ณด์ ํฌ์๊ฐ ๊ฐํ๋๋ ๋์์, ์์ด์ ํฑ AI ๊ธฐ๋ฐ ์ ๋ฌด ํจ์จํ์ ํฉ์ฑ ๋ฐ์ดํฐ์ ํ์ฉ์ด AI ํฌ์์ ํต์ฌ์ด ๋ ๊ฒโ์ด๋ผ๊ณ ์ ๋งํ๋ค.
์ด์คํ ๋ํ์ด์ฌ๋ ๋ด๋
๋ ์ฌ์
์ ๋ํด โ๊ธ๋ก๋ฒ ์ฑ๊ณต ์ฌ๋ก๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๊ตญ๋ด ๊ณ ๊ฐ๋ค์ด AI ๊ฑฐ๋ฒ๋์ค๋ฅผ ํ๋ณดํ๊ณ ๋น์ฆ๋์ค ๊ฐ์น๋ฅผ ์ฐฝ์ถํ ์ ์๋๋ก ๊ธ์ตยท๊ณต๊ณต ๋ถ๋ฌธ ์๋ฃจ์
๊ณผ ์ ๋ฌธ ์๋น์ค๋ฅผ ํตํด ์ ๊ทน ์ง์ํ๊ฒ ๋คโ๊ณ ๊ฐ์กฐํ๋ค.
dl-ciokorea@foundryco.com
๊ธฐ์ ์ง์, ํนํ ์ ๋ฌธ ์ญ๋์ ๊ฐ์ถ ์ธ์ฌ๋ ์ฌ์ ํ ํ๋ณดํ๊ธฐ ์ด๋ ต๋ค. Gi๊ทธ๋ฃน์ ์ต๊ทผ ๊ธ๋ก๋ฒ IT HR ํธ๋ ๋ ๋ณด๊ณ ์์ ๋ฐ๋ฅด๋ฉด, ๊ธฐ์ ์ 47%๊ฐ ์ ํฉํ ์ธ์ฌ๋ฅผ ์ฐพ๊ณ ์ ์งํ๋ ๋ฐ ์ด๋ ค์์ ๊ฒช๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ์ด์ง๋ฅ ์ญ์ ์ฌ์ ํ ๋์ ์์ค์ ์ ์งํ๊ณ ์๋ค.
๊ธ๋ก๋ฒ ์กฐ์ฌ ์ ์ฒด ์ธ๊ณ ์ค(Cegos)๊ฐ ์ดํ๋ฆฌ์์ ์ ๋ณด์์คํ ์ฑ ์์ 200๋ช ์ ๋์์ผ๋ก ์งํํ ์กฐ์ฌ์์, ์๋ต์์ 53%๋ IT ์ธ์ฌ ํ๋ณด์ ์ ์ง๊ฐ โ๋งค์ผ ์ง๋ฉดํ๋ ๋ฌธ์ โ๋ผ๊ณ ๋ตํ๋ค. IT ๋ถ์์ ๊ฐ์ฅ ์๊ธํ ๊ณผ์ ๋ก๋ ์ฌ์ด๋ฒ๋ณด์์ด ๊ผฝํ์ง๋ง, ์ด ๋ฌธ์ ๋ ๋ค์์ CIO๊ฐ ์ผ์ ์์ค ํด๊ฒฐํ ์ ์๋ค๊ณ ๋๋ผ๋ ์์ญ์ด์๋ค. ๋ฐ๋ฉด IT ์ธ์ฌ ๋ถ์กฑ ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ ์ ์๋ค๊ณ ์์ ํ ๋น์จ์ 8%์ ๋ถ๊ณผํ๋ค. ์ดํ๋ฆฌ์ CIO๋ ์ฌ์ด๋ฒ๋ณด์ ๋ค์์ผ๋ก IT ํ์ ์ญ๋ ๊ฐ๋ฐ๊ณผ ์ธ์ฌ ์ ์ง๋ฅผ ์ค๋ํ ๊ณผ์ ๋ก ๊ผฝ์์ผ๋ฉฐ, ์ด๋ฅผ ํด๊ฒฐํ ์ ์๋ค๊ณ ๋ณธ ๋น์จ๋ ๊ฐ๊ฐ 24%์ 9%์ ๊ทธ์ณค๋ค.
์ดํ๋ฆฌ์ ํต๊ณ์ฒญ ์ด์คํํธ(Istat)์ CIO์ธ ์ฒด์น ๋ฆฌ์ ์ฝ๋ผ์ฐํฐ๋ โ์ธ์ฌ๊ฐ ์์ด์๊ฐ ์๋๋คโ๋ผ๊ณ ๋งํ๋ค. ๊ทธ๋ โ์ธ์ฌ๋ ๋ถ๋ช ํ ์์ง๋ง ์ ๋๋ก ํ๊ฐ๋ฐ์ง ๋ชปํ๋ค. ๊ทธ๋์ ๋ง์ ์ด๋ค์ด ํด์ธ๋ก ๋๊ฐ๋ ๊ธธ์ ํํ๋ค. ์ธ์ฌ๋ โ์ ์ฌ์ ์์ ๋์ธ ์ฌ๋โ์ ์๋ฏธํ๋ค. CIO๋ฅผ ํฌํจํ ๋ฆฌ๋๋ผ๋ฉด ์ธ์ฌ๋ฅผ ์์๋ณด๊ณ , ๊ทธ๋ค์ด ์ธ์ ๋ฐ๊ณ ์๋ค๋ ์ฌ์ค์ ๋๋ผ๊ฒ ํ๋ฉฐ, ์ ์ ํ ๊ธฐํ๋ฅผ ์ ๊ณตํด ์ฑ์ฅ์ํฌ ์ญ๋์ ๊ฐ์ถฐ์ผ ํ๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
์ฝ๋ผ์ฐํฐ๋ ๊ฒฐ์๋ ฅ ์๊ณ ๋๊ธฐ ๋ถ์ฌ๋ ์กฐ์ง์ ๋ง๋ค๊ธฐ ์ํ ์ธ์ฌ ๊ด๋ฆฌ ๋ฐฉ๋ฒ์ ๋ช ํํ ์ ์ํ๋ค. ๊ทธ๋ โCIO๋ก์ ์ค์ค๋ก ์ค์ ํ ๋ชฉํ๋ ๋ด๋ถ์ ์ธ๋ถ์ ์๋น์ค ์ด์ฉ์์๊ฒ ๋ ๋์ ํ์ง์ ๊ฒฐ๊ณผ๋ฌผ์ ๊ณ์ ์ ๊ณตํ๋ ๊ฒ์ด์๋คโ๋ผ๋ฉฐ, โIT ๋ถ์๋ ์ ๋ฌด ์ด์์ ํต์ฌ์ ์ธ ๋๋ ฅ์ด๊ธฐ ๋๋ฌธ์ ์์ํ ํ๋ก์ ํธ๋ฅผ ํ์คํ ๋ง๋ฌด๋ฆฌํ๊ณ , ๊ธฐ๊ด์ด ์ง์์ ์ผ๋ก ๊ฐ์ ํ ์ ์๋๋ก ๊ตฌ์ฒด์ ์ธ ์ฑ๊ณผ๋ฅผ ๋ด๋ ๊ฒ์ด ์ค์ํ๋ค. ๋๋ IT ๊ธฐ๋ฅ ์์ฒด๋ฅผ ๊ณ ๋ํํ๊ณ , ์ ๊ณต๋๋ ์๋น์ค์ ํ์ง์ ๋์ด๋ฉฐ, ์กฐ์ง ์ด์์ ์ ํฉ์ฑ์ ํ๋ณดํ๊ณ , ๊ตฌ์ฑ์์ ๋ณต์ง๋ฅผ ํฅ์ํ๋ ์ญํ ์ ๋งก๊ณ ์๋คโ๋ผ๊ณ ๋งํ๋ค.
์ด์คํํธ์ IT ๋ถ์๋ ํ์ฌ 195๋ช ๊ท๋ชจ๋ก, ๊ธฐ๊ด ์ ์ฒด ์ธ๋ ฅ์ ์ฝ 10%๋ฅผ ์ฐจ์งํ๋ค. ์ฝ๋ผ์ฐํฐ๊ฐ 2023๋ 10์ CIO๋ก ์๋ช ๋ ์งํ ๊ฐ์ฅ ๋จผ์ ํ ์ผ์, ๊ด๋ฆฌ ์กฐ์ง์ ๋ฐฐ์น๋ ๋ชจ๋ ์ธ๋ ฅ์ ์ง์ ๋ง๋ ๋ํ๋ฅผ ๋๋๋ ์ผ์ด์๋ค.
์ฝ๋ผ์ฐํฐ๋ โ2001๋ ๋ถํฐ ์ด์คํํธ์์ ์ผํด์๊ณ , ์๋ก ๋๋ถ๋ถ ์๊ณ ์ง๋ด๋ ์ฌ์ดโ๋ผ๊ณ ๋งํ๋ค. ๊ทธ๋ โIT ๋ถ์์์ ์ฌ๋ฌ ์ญํ ์ ๋งก์์์ผ๋ฉฐ, CIO๊ฐ ๋ ๋ค์๋ ๋ชจ๋์ ์๊ฒฌ์ ๊ฒฝ์ฒญํ๋ ๋ฐ ์ง์คํ๋ค. ์๋ก ์ ์๋ ๋งํผ ๋๋ฃ๋ค์ด ํ์ ์ ํฐ ๊ธฐ๋๋ฅผ ๊ฑธ๊ณ ์๋ค๊ณ ๋๋๋ค. ๊ทธ๋์ ์์งํ ๋ํ๋ฅผ ์ถ๊ตฌํ๊ณ ๋ชจํธํจ์ ํผํ๋ ค๊ณ ํ๋ค. ๋ค๋ง, ๊ฒฝ์ฒญํ๋ค๋ ๊ฒ ์ฑ ์์ ๋๊ธด๋ค๋ ๋ป์ ์๋๋ค. ์ด๋ค ์ ์์ ๋ฐ์๋ค์ด๊ณ ์ด๋ค ์ ์์ ๊ฑฐ์ ํ๋ฉฐ, ์ ํ์๋ ๋๋ฆ์ ์ด์ ๋ฅผ ์ค๋ช ํ๋ ค๊ณ ํ๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
์ฝ๋ผ์ฐํฐ๋ ๋ ๋ค๋ฅธ ์กฐ์น๋ก ์ค๋์ ์ด์คํํธ์์ ์งํ๋๋ โ๋ ๊ฐ์ง ๋ฌธ์ , ๋ ๊ฐ์ง ํด๊ฒฐ์ฑ โ ํ๋ก๊ทธ๋จ์ ๋ค์ ๋์ ํ๋ค. ์ด๋ ์ง์๋ค์๊ฒ ์๋ฐ์ ์ผ๋ก ๋ ๊ฐ์ง ๋ฌธ์ ๋ฅผ ์ ์ํ๊ณ ๋ ๊ฐ์ง ํด๊ฒฐ์ฑ ์ ์ ์ํด ๋ฌ๋ผ๊ณ ์์ฒญํ๋ ๋ฐฉ์์ด๋ค. ๊ทธ๋ ์์ง๋ ๋ด์ฉ์ ์ง์ ๊ฒํ ํด, ๋๋ฉด ๋ฏธํ ์์ ์๊ฒฌ์ ๊ณต์ ํ๊ณ ์ ์์ ํ๋น์ฑ์ ๋ ผ์ํ๋ฉฐ ํ์ ์กฐ์น๊ฐ ํ์ํ ์ฌํญ์ ํ๊ฐํ๋ค. ๊ทธ๋ ์ด ํ๋ก๊ทธ๋จ์ด ๋๋ฃ๋ค๊ณผ์ ์ ๋ขฐ๋ฅผ ๋ค์ง๋ ๋ฐ ๋งค์ฐ ํจ๊ณผ์ ์ด์๋ค๊ณ ๋ถ์ํ๋ค.
์ผ๋ถ ์๊ฒฌ์ ๊ฒฝ๋ ฅ ๊ฐ๋ฐ ๊ธฐํ๋ ๊ธฐ์ ์ ๋ฌธ์ ์ ๊ดํ ๊ฒ์ด์์ง๋ง, ๊ฐ์ฅ ๋ง์ด ์ ๊ธฐ๋ ๋ถ๋ง์ ๋ด๋ถ ์ปค๋ฎค๋์ผ์ด์ ๋ฌธ์ ์ ์ธ๋ ฅ ๋ถ์กฑ์ด์๋ค. ์ฝ๋ผ์ฐํฐ๋ ๋ชจ๋ ์ฌ๋๊ณผ ๋ํ๋ฅผ ๋๋๋ฉฐ, ์์ ์ด ๊ฐ์ ํ ์ ์๋ ๋ถ๋ถ๊ณผ ๊ทธ๋ ์ง ๋ชปํ ๋ถ๋ถ์ ๋ช ํํ ์ค๋ช ํ๋ค. ์๋ฅผ ๋ค์ด ๊ณต๊ณต ๋ถ๋ฌธ์ ๊ฒฝ๋ ฅ ์ฒด๊ณ๋ ์ฑ์ฉ์ ์๊ฒฉํ ์ ์ฐจ์ ๋ฐ๋ผ ์งํ๋๊ธฐ ๋๋ฌธ์ CIO๊ฐ ์ํฅ์ ๋ฏธ์น ์ ์๋ ์ฌ์ง๊ฐ ๊ฑฐ์ ์๋ค.
์ฝ๋ผ์ฐํฐ๋ โ๋ชจ๋ ์ด์๋ฅผ ๋ฅ๋์ ์ผ๋ก ํด๊ฒฐํ๋ ค๊ณ ํ๋ค. ๊ตฌ์ฒด์ ์ธ ๋ฌธ์ ๋ผ๊ธฐ๋ณด๋ค ๋ณํ์ ๋ํ ๋ง์ฐํ ์ ํญ์ฒ๋ผ ๋๊ปด์ง๋ ๋ถ๋ถ์ ๋ํด์๋ ๊ตฌ์ฑ์์ ๋ด์ ๋๊ธฐ์ ์ฑ ์๊ฐ์ ๋์ด๋ด๋ ๋ฐ ์ง์คํ๋ค. ๊ธฐ๊ด์ ์ ๋ต์ด ๋ฌด์์ด๋ฉฐ, ๋ชฉํ๋ฅผ ๋ฌ์ฑํ๊ธฐ ์ํด ๊ฐ์๊ฐ ์ด๋ค ์ญํ ์ ์ํํด์ผ ํ๋์ง ์ค๋ช ํ๋ ๊ณผ์ ์ด ๋งค์ฐ ์ค์ํ๋ค. ๊ฒฐ๊ตญ ์ฌ๋๋ค์ ์์ ์ด ์ด๋ค ํ๊ฒฝ์์ ์ผํ๊ณ ์๋์ง, ๊ทธ๋ฆฌ๊ณ ์์ ์ ์ผ์ด ์ ์ฒด ๊ทธ๋ฆผ์ ์ด๋ค ์ํฅ์ ๋ฏธ์น๋์ง ์ ๊ถ๋ฆฌ๊ฐ ์๋คโ๋ผ๊ณ ๊ฐ์กฐํ๋ค.
์กฐ์ง์ ์ฐธ์ฌ์ ๋ชฐ์ ์ ํ๋ฃจ์์นจ์ ๋ง๋ค์ด์ง์ง ์๊ธฐ ๋๋ฌธ์, ์ฝ๋ผ์ฐํฐ๋ ๋ถ์์ฅ๊ณผ ์๋น์ค ๋งค๋์ ๋ฅผ ํฌํจํ ์ง์๋ค๊ณผ ์ ๊ธฐ์ ์ผ๋ก ๋ง๋๋ฉฐ ์ํต์ ์ด์ด๊ฐ๊ณ ์๋ค.
์ด์คํํธ์ ๊ฒฝ์ฐ IT ๋ถ์ ๊ท๋ชจ๊ฐ ํฐ ํธ์ ์ํ์ง๋ง, ์ค์๊ธฐ์ ์์๋ CIO๋ฅผ ํฌํจํด ๋ช ๋ช ์ ๋๋ ๊ตฌ์ฑ์๋ง์ผ๋ก IT ๋ถ์๋ฅผ ์ด์ํ๋ ๊ฒฝ์ฐ๊ฐ ๋ง๋ค. ์๋น ๋ถ๋ถ์ ์ธ๋ถ ์ปจ์คํดํธ๋ ๋ฒค๋๊ฐ ๋งก์ ์ผ์ ์งํํ๋ค. ์ด๋ฐ ๊ตฌ์กฐ์์๋ ์ฌ๋ฌ ํ๋ก์ ํธ์ ๊ฑธ์ณ ์์์ ์กฐ์จํ๋ ์ ๋ฌด์ ์ค์ IT ์ด์ ์ ๋ฌด๋ฅผ ๋์์ ์ฒ๋ฆฌํด์ผ ํ๋ฏ๋ก ๋ถ๋ด์ด ํฌ๋ค. ํด๋ผ์ฐ๋ ์์์์ฑ์ ํ๋์ ๋ฐฉ๋ฒ์ด ๋ ์ ์์ง๋ง, ๋ง์ CIO๊ฐ ๋ฒค๋ ์ข ์์ ํผํ๊ธฐ ์ํด ๋ด๋ถ ์ญ๋์ ๋ ํ๋ณดํ๊ธธ ์ํ๋ค.
IT ์ธ๋ ฅ์ด 3๋ช ๋ฟ์ธ ํ ์ค์ ์๋ฃ๊ธฐ์ CIO๋ โ์ธ์ฌ๋ฅผ ๋์ด์ค๋ ๊ฒ๋, ๋ถ์ก์๋๋ ๊ฒ๋ ์ด๋ ค์ ๊ฒฐ๊ตญ ์์์์ฑ์ ํ ์๋ฐ์ ์๋คโ๋ผ๊ณ ๋งํ๋ค. ๊ทธ๋ โ์ ๋ฌด๋ฅผ ์ธ๋ถ๋ก ๋๊ฒจ ๋ด๋ถ ์์์ ํ๋ณดํ๋ ค๋ฉด ํ์ฌ์ ๋ ธํ์ฐ๊ฐ ๋น ์ ธ๋๊ฐ ์ํ๋ ๊ฐ์ํด์ผ ํ๋ค. ํ์ง๋ง ์ง๊ธ์ผ๋ก์ ๋ค๋ฅธ ์ ํ์ง๊ฐ ์๋ค. ๋๊ธฐ์ ์์ค์ ์ฐ๋ด์ ์ ์ํ ์ ์๊ณ , ์ด์ง์ด ์ฆ์ IT ์ธ์ฌ์๊ฒ ๊พธ์คํ ๋๊ธฐ๋ฅผ ๋ถ์ฌํ๊ธฐ๊ฐ ๋งค์ฐ ์ด๋ ต๋ค. ์ฌ๋์ ๋ฝ์ ๊ต์กํ๊ณ , ์กฐ๊ธ์ฉ ์ฑ์ฅํ๋ ๋ชจ์ต์ ์ง์ผ๋ณด๋ค๊ฐ ๊ฒฐ๊ตญ ๋ ๋๋ ์ํฉ์ด ๋ฐ๋ณต๋๊ณ ์๋ค. ๊ฒ๋ค๊ฐ ์๋ฃ ์ฐ์ ์ ์ ๋ฌธ์ฑ์ด ๋งค์ฐ ๋์ ํ์ํ ์ญ๋์ ๊ฐ์ถ ์ฌ๋์ด ๋๋ฌผ๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
๊ธฐ์ ์ญ๋์ ๊ฐ์ถ ์ธ์ฌ์๊ฒ ์์ฅ์ ์ธ์ ๋ ๋งค๋ ฅ์ ์ธ ์กฐ๊ฑด์ ๋ด์ธ์ด๋ค. ํนํ ๋ฏผ๊ฐ ๊ธฐ์ ์ ์ฑ์ฉ์ ์ ์ฐ์ฑ๊ณผ ๋ค์ํ ๊ฒฝ๋ ฅ ๊ฒฝ๋ก๋ฅผ ์ ๊ณตํ ์ ์์ด ๊ณต๊ณต ๊ธฐ๊ด๋ณด๋ค ์ธ์ฌ ์ ์น๊ฐ ํจ์ฌ ์ฝ๋ค.
์ฝ๋ผ์ฐํฐ๋ โ๊ณต๊ณต ๋ถ๋ฌธ์ ๋ฏผ๊ฐ ๊ธฐ์ ์ด ์์ต์ฑ์ด ๋ฎ๋ค๊ณ ํ๋จํด ํฌ์ํ์ง ์๋ ์ฃผ์ ๋ฅผ ์ฐ๊ตฌํ๊ณ , ํ๊ตฌํ๊ณ , ๊น์ด ํ๊ณ ๋ค ๊ธฐํ๋ฅผ ์ ๊ณตํ๋ค. ๊ณต๊ณต ๊ธฐ๊ด์ ๊ณต๋์ฒด์ ์ด์ต์ ๋ชฉํ๋ก ํ๊ณ , ์ฅ๊ธฐ์ ์ธ ํฌ์๋ฅผ ๊ฐ๋นํ ์ ์๋ ๊ตฌ์กฐ๋ฅผ ๊ฐ๊ณ ์๋คโ๋ผ๊ณ ๋งํ๋ค.
์ธ๊ณ ์ค์ ๊ธ๋ก๋ฒ ์งํ์ ๋ฐ๋ฅด๋ฉด, CIO๋ IT ์์๋ฅผ ์ถฉ์กฑํ๊ธฐ ์ํด ์๋ก์ด ์ธ์ฌ ์ฑ์ฉ๊ณผ ๊ธฐ์กด ํ์ ๊ต์ก์ ์ฐ์ ์์๋ก ๋๊ณ ์๋ค. ์ด๋ ์ฌ๊ต์ก๊ณผ ์ญ๋ ๊ฐํ๋ ์ธ์ฌ ํ๋ณด์ ์ ์ง ๊ณผ์ ์์ ๋ฐ์ํ๋ ์ฌ๋ฌ ๋ฌธ์ ๋ฅผ ๊ทน๋ณตํ๋ ๋ฐ ํจ๊ณผ์ ์ผ ์ ์๋ค.
์ธ๊ณ ์ค ์ดํ๋ฆฌ์์ ๋น์ฆ๋์ค ํธ๋์คํฌ๋ฉ์ด์ ๋ฐ ์คํ ์ฑ ์์ ์๋ง๋์๋ผ ํผ๋ํ๋ก๋ โ์์ฅ์ด ๋งค์ฐ ๊ฒฝ์์ ์ด๊ธฐ ๋๋ฌธ์, ์ธ์ฌ๋ฅผ ์ ์งํ๋ ค๋ฉด ์ด์ง์ ๋ง์ ๋ฐฉ๋ฒ์ด ํ์ํ๋คโ๋ผ๊ณ ๋งํ๋ค. ๊ทธ๋ โ๊ธฐ์ ์ด ์ถฉ๋ถํ ๋ณด์๊ณผ ํจ๊ป ์๊ทน์ ์ด๊ณ ๋ณด๋ ์๋ ํ๊ฒฝ์ ์กฐ์ฑํ๋ฉด, ๊ตฌ์ฑ์ ์ญ์ ๋ค๋ฅธ ๊ธฐํ๋ฅผ ์ฐพ๋ ๋์ ํ์ฌ ์ ๋ฌด์ ์ง์คํ ์ ์๋ค. ๋ง์ ์ง์์ด ๊ฐ๋นํ๊ธฐ ์ด๋ ค์ด ์ ๋ฌด๋ฅผ ๊ณผ๋ํ๊ฒ ๋ ์๊ณ ์๋ค๊ณ ๋๋ผ๋๋ฐ, ์ด๋ค์ด ํนํ ๊ฐ์น๊ฐ ๋์๋ฐ๋ ๋ถ๊ตฌํ๊ณ ์ง์์ด ๋ถ์กฑํ ๊ฒฝ์ฐ๊ฐ ๋ง๋ค. ๋ฐ๋ผ์ ํ์ฌ๊ฐ ์ด๋ค์ ์ง์ํ ์ ๊ท ์ธ๋ ฅ์ ์ฑ์ฉํ๊ฑฐ๋ ๊ต์ก์ ํฌ์ํ๋ฉด ์ฌ๋ฆฌ์ ์์ ๊ฐ์ ์กฐ์ฑํ๊ณ ์ถฉ์ฑ๋๋ฅผ ๋์ผ ์ ์๋คโ๋ผ๊ณ ๋ถ์ํ๋ค.
์ค์ ๋ก ์ฝ๋ผ์ฐํฐ๋ ์กฐ์ง์ ๊ท ํ ์๋ ์ด์๊ณผ ๊ด๋ฆฌ ์ญ๋์ ๋ท๋ฐ์นจํ๋ โ์ง์์ ํ์ตโ์ ๋ฌด์๋ณด๋ค ์ค์ํ๊ฒ ์ฌ๊ธด๋ค. IT ๊ต์ก ์์ฐ์ ์ถฉ๋ถํ์ง ์์ง๋ง, ๊ตฌ์ฑ์์ด ์ ๊ธฐํ ์๊ตฌ๋ฅผ ์ถฉ์กฑํ ํ์ค์ ๋์์ ์ผ๋ถ ๋ง๋ จ๋ผ ์๋ค.
๋ค๋ง ์ฝ๋ผ์ฐํฐ๋ โ์ด๋ฐ ๊ฒฝ์ฐ์๋ ํ๊ณ ํ ์์ง๊ฐ ํ์ํ๋ค. ๊ธฐ๊ด์ด ํฌ์ ํ ๋น์ฉ์ด ์๋ ๋งํผ ๊ต์ก์ ๊ฒฐ๊ณผ๋ฅผ ๋ด์ผ ํ๋ค. ์ฌ์ด๋ฒ๋ณด์์ฒ๋ผ ๋ณํ๊ฐ ๋น ๋ฅธ ์์ญ์ ๋ ํฐ ํฌ์๋ ์๊ตฌ๋๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
CIO๋ ๊ตฌ์ฑ์์ ์ ๋๋ก ์ง์ํ๊ณ , ๊ถํ์ ๋ถ์ฌํ๋ฉฐ, ๋๊ธฐ๋ฅผ ๋์ด๋ ์ ๋ฌด๋ฅผ ๋ช ํํ ๋ถ์ฌํด์ผ ํ๋ค๋ ์ ์ ์ค์ํ๊ฒ ์ฌ๊ธฐ๊ณ ์๋ค. ๋ํ ๋ณต์ง ์ ๋๋ฅผ ๋ง๋ จํ๊ธฐ ์ํด HR ๋ถ์์ ๊ธด๋ฐํ ํ๋ ฅํ๋ ๊ฒ๋ ํ์ ์์๋ก ๊ผฝํ๋ค.
Gi๊ทธ๋ฃน ์กฐ์ฌ์ ๋ฐ๋ฅด๋ฉด, ์ดํ๋ฆฌ์ IT ๊ตฌ์ง์๊ฐ ์ฑ์ฉ ๊ธฐ์ ์ ์ ํํ ๋ ์ฐ์ ์์๋ก ๊ณ ๋ คํ๋ ์์๋ ๊ธ์ฌ, ํ์ด๋ธ๋ฆฌ๋ ๊ทผ๋ฌด ํํ, ์ผ๊ณผ ์ํ์ ๊ท ํ, ๊ณผ๋ํ ์คํธ๋ ์ค๊ฐ ์๋ ์ง๋ฌด, ๊ฒฝ๋ ฅ ๊ฐ๋ฐ ๋ฐ ์ฑ์ฅ ๊ธฐํ ์์ด์๋ค.
๋ค๋ง ์ธ์ฌ ๊ด๋ฆฌ๋ผ๋ ๊ณผ์ ๋ฅผ ํด๊ฒฐํ๊ธฐ ์ํด์๋ ๋ ๋ค๋ฅธ ์์๊ฐ ํ์ํ๋ค. CIO ์ค์ค๋ก ์์ ์ ๋ฆฌ๋์ญ ์ญํ ์ ๋ ๋ช ํํ ์๊ฐํด์ผ ํ๋ค๋ ์ ์ด๋ค. ํ์ฌ ์ดํ๋ฆฌ์ IT ์ฑ ์์๋ค์ ๋ฆฌ๋์ญ ๊ด๋ จ ์์๋ฅผ ํต์ฌ ์ญ๋ ์ค ๊ฐ์ฅ ๋ฎ์ ์์์ ๋๊ณ ์๋ค. ์ธ๊ณ ์ค ์กฐ์ฌ์์๋ ๊ธฐ์ ์ ๋ฌธ์ฑ, ์ ๋ต์ ๋น์ , ํ์ ์ญ๋์ด ์ต์ฐ์ ์ผ๋ก ๊ผฝํ ๋ฐ๋ฉด, ๋ฆฌ๋์ญ์ ํ์ฐธ ๋ค๋ก ๋ฐ๋ ธ๋ค. ํ์ง๋ง CIO์ ๋ฆฌ๋์ญ์ ์กฐ์ง ์ด์์ ๊ทผ๊ฐ์ด์ด์ผ ํ๋ค. ์ด๋ ํน์ ๊ฒฐ์ ์ ์๊ฒฌ ์ฐจ์ด๊ฐ ์์ ๋์๋ ๋ณํจ์์ด ์ค์ํ ์ญํ ์ ํ๋ค.
์ฝ๋ผ์ฐํฐ๋ โ๋ฆฌ๋๋ก์ ์
๋ฌด ๊ณต๊ฐ์์์ ์กด์ฌ๊ฐ์ ์ค์ํ๊ฒ ์๊ฐํ๋คโ๋ผ๊ณ ๋งํ๋ค. ๊ทธ๋ โ์ด์คํํธ๋ ์ค๋์ ๋ถํฐ ์ฌํ ๊ทผ๋ฌด์ ์ค๋งํธ ์
๋ฌด๋ฅผ ์ ๋ํํด ๋๊ตฌ๋ ํ์ํ๋ฉด ์ด์ฉํ ์ ์๋ค. ๊ฐ์ธ์ ์ผ๋ก๋ ์ฌ๋ฌด์ค์์ ์ผํ๋ ๊ฒ์ ์ ํธํ์ง๋ง, ์ฌ์ํ๊ณผ ์
๋ฌด์ ๋ฐธ๋ฐ์ค๋ฅผ ์กด์คํ๋ฉฐ ์ ์ฐ ๊ทผ๋ฌด์ ๋ฐ๋ํ์ง ์๋๋ค. ๋ค๋ง ๋๋ ๋งค์ผ ํ์ฅ์ ๋์จ๋ค. ๋๋ฃ๋ค๋ ๋ด๊ฐ ์ด๊ณณ์ ์๋ค๋ ์ฌ์ค์ ์๊ณ ์๋คโ๋ผ๊ณ ์ ํ๋ค.
dl-ciokorea@foundryco.com
์ด๋ฒ MOU๋ ๊ฐ์ ๋ ์ด์ฌ๋ช ๋ํต๋ น์ด ์ํํธ๋ฑ ํฌ ์์ ์ ํ์ฅ, Arm์ ๋ฅด๋ค ํ์ค CEO์ ๋ฉด๋ดํ ๊ฒ์ ๊ณ๊ธฐ๋ก ์ถ์ง๋ ๊ฒ์ผ๋ก, ํ๊ตญ๊ณผ ์ํํธ๋ฑ ํฌยทArm ๊ฐ ํ๋ ฅ ํ๋ ๊ฐ๋ฅ์ฑ์ ๋ ผ์ํ ๋ฐ ๋ฐ๋ฅธ ๊ฒ์ด๋ค.
ํ์ฝ์๋ โฒ์ฐ์ ๋ง์ถคํ ์ธ์ฌ 1,400๋ช ์์ฑ โฒ๊ธฐ์ ๊ต๋ฅ ๋ฐ ์ํ๊ณ ๊ฐํ โฒ๋ํ ๊ฐ ์ฐ๊ณ ํ๋ โฒR&D ํ๋ ฅ ๋ฑ์ด ํฌํจ๋๋ค. ์ฐ์ ๋ถ์ Arm์ ํ์ ๋ ผ์๋ฅผ ์ํ ์ค๋ฌดํ์์ฒด๋ฅผ ๊ตฌ์ฑํด ์ธ๋ถ ์ถ์ง ๋ฐฉ์์ ๋ง๋ จํ ๊ณํ์ด๋ค.
ํนํ ์ฐ์ ๋ถ๋ Arm๊ณผ ํจ๊ป โArm ์ค์ฟจ(Arm School, ๊ฐ์นญ)โ์ ์ค๋ฆฝํด 2026๋ ๋ถํฐ 2030๋ ๊น์ง ์ฝ 1,400๋ช ์ IP ์ค๊ณ ์ ๋ฌธ ์ธ๋ ฅ์ ์์ฑํ๋ค๋ ๊ตฌ์์ด๋ค. Arm์ ์ ํยท๊ตฌ๊ธยทMS ๋ฑ ๊ธ๋ก๋ฒ ๋น ํ ํฌ ๋ฐ ์ผ์ฑยท์๋น๋์ยทํ์ปด ๋ฑ ์ฃผ์ ๋ฐ๋์ฒด ๊ธฐ์ ์ด ํ์ฉํ๋ ํต์ฌ ์ค๊ณ ํ๋ซํผ์ผ๋ก, ์ ๋ถ๋ ์ด๋ฒ ํ๋ ฅ์ด ๊ตญ๋ด ์์คํ ๋ฐ๋์ฒด ๊ฒฝ์๋ ฅ ๊ฐํ์ ๊ธฐ์ฌํ ๊ฒ์ผ๋ก ๊ธฐ๋ํ๊ณ ์๋ค.
๊ณต์ ์ ์ฅ๋ฌธ์ ๋ฐ๋ฅด๋ฉด ์ฐ์ ๋ถ๋ ๋ฐ๋์ฒด ํน์ฑํ ๋ํ์ ์ง์ ์ ํฌํจํ ๊ด๋ จ ์ ์ฐจ๋ฅผ ์ฐจ์ง ์์ด ์ถ์งํ ๊ณํ์ด๋ฉฐ, ๊ด์ฃผ๊ณผํ๊ธฐ์ ์์ ์ฐ์ ๊ฒํ ๋์์ ๋๊ณ ์๋ค.
๊น์ ๊ด ์ฐ์ ๋ถ ์ฅ๊ด์ โ์ด๋ฒ ์ํด๊ฐ์๋ฅผ ํตํด AI ๋ฐ๋์ฒด ์ฐ์ ์ ์ด๋ ํต์ฌ ์ธ๋ ฅ ์์ฑ ๊ธฐ๋ฐ์ ๋ง๋ จํ๋คโ๋ฉฐ โAI ์๋์ ๋๋นํด ๊ธ๋ก๋ฒ ๊ธฐ์ ๋ค๊ณผ์ ํ๋ ฅ์ ์ง์ ํ๋ํ๊ฒ ๋คโ๋ผ๊ณ ๋งํ๋ค.
ํํธ, Arm์ ์ง๋ถ ์ฝ 90%๋ฅผ ๋ณด์ ํ ์ผ๋ณธ ์ํํธ๋ฑ ํฌ์ ์์ ์ ํ์ฅ์ ์ด๋ฒ ํ์ฝ์ ์ํ ์ ๊ฒฌ์์ โ์์ผ๋ก ๋ชจ๋ ๊ตญ๊ฐ์ ๊ธฐ์ ๋ค์ ASI ์๋๋ฅผ ์ค๋นํ์ฌ์ผ ํ๊ณ , ๊ตญ๋ฏผ๋ค์๊ฒ ๋ณดํธ์ ์ ๊ทผ๊ถ์ ๋ณด์ฅํ ์ ์๋๋ก ์ญ๋์ ์ง์คํด์ผ ํ๋คโ๋ผ๋ฉฐ โASI๋ฅผ ๊ตฌํํ๊ธฐ ์ํด์๋ ์๋์ง, ๋ฐ๋์ฒด, ๋ฐ์ดํฐ, ๊ต์ก์ ๋ค ๊ฐ์ง ์์์ด ํ์์ โ์ด๋ผ๊ณ ๊ฐ์กฐํ๋ค.
์ ํ์ฅ์ ๋ํ ํ๊ตญ์ ์ํฉ์ ๊ณ ๋ คํ ๋, ASI ๊ตฌ์ถ์ ์ํด์๋ ๋ฐ์ดํฐ์ผํฐ์ ๋ํญ์ ์ธ ์ฆ์ค์ด ํ์ํ๋ฉฐ, ์ด๋ฅผ ์์ ์ ์ผ๋ก ๋ท๋ฐ์นจํ ์ ์๋ ์๋์ง ํ๋ณด์ ๋์ฑ ํ์จ์ผ ํ๋ค๊ณ ์กฐ์ธํ๋ค.
jihyun.lee@foundryco.com
Q: ์์ง๋์ด๋ก์์ ๊ฒฝ๋ ฅ์ ์์ํ ์ด๊ธฐ ์์ ๊ณผ, ์ดํ ์ปค๋ฆฌ์ด์ ๋ฐฉํฅ์ ๋ฐ๊พธ๊ฒ ๋ ๊ณ๊ธฐ๋ ๋ฌด์์ธ๊ฐ?
A: 1989๋
๋๋ ๋ฏธ์ฐ๋น์๊ฐ์ธ์ด(ํ ๋ฏธ์ฐ๋น์์ผ๋ฏธ์ปฌ)์ ์์ฐ๊ธฐ์ ์์ง๋์ด๋ก ์ ์
์
์ฌํ๋ค. ๋ฐฐ์น๋ ๊ณณ์ ์ค์นด์ผ๋งํ ๊ตฌ๋ผ์ํค์์ ๋ฏธ์ฆ์๋ง ์ฌ์
์๋ก, ๋๊ท๋ชจ ์์ ยทํํ ์ฐ์
๋จ์ง์์ ํ๋ ์์ง๋์ด๋ง ์
๋ฌด๋ฅผ ๋งก์ผ๋ฉฐ ์ปค๋ฆฌ์ด์ ์ฒซ๊ฑธ์์ ๋ด๋๋ ๋ค.
์ ํ์ ์ 1996๋ ์ ์ฐพ์์๋ค. ๋ฏธ๊ตญ ๋๋ถ์ ๋ณด์คํด๊ณผ ์๋ถ ์ํ๋์์ค์ฝ์ ์ ๊ท ๊ฑฐ์ ์ ์ค๋ฆฝํ๋ค๋ ๊ณํ์ด ์ถ์ง๋๋ฉด์, ๋ฏธ ์๋ถ ๊ฑฐ์ ์ ์ด๊ธฐ ๋ฉค๋ฒ๋ก ์ ๋ฐ๋ผ ์ค๋ฆฌ์ฝ๋ฐธ๋ฆฌ์ ์ฃผ์ฌํ๊ฒ ๋๋ค. ๋น์์๋ ์๋์ฐ 95์ ๋ฑ์ฅ, ์ธํฐ๋ท์ ๋์คํ, e๋น์ฆ๋์ค๊ฐ ๋ง ํ๋ํ๋ ์๊ธฐ์๋ค. ๋ฏธ๊ตญ ์ ์ฒด ํฌ์๊ธ์ ์ฝ 3๋ถ์ 1์ด ๋ชจ์ธ๋ค๋, ์ธ๊ณ ์ต์ ์ ์ ๊ธฐ์ ๊ณผ ์๋ณธ์ด ์ง๊ฒฐํ ํ์ฅ์ ๋ชธ์ ๋๊ฒ ๋ ๊ฒ์ด๋ค.
3๋ ๊ฐ์ ์ฃผ์ฌ๋ฅผ ๋ง์น๊ณ ๋ฏธ์ฆ์๋ง๋ก ๋ณต๊ทํด ๋ค์ ์์ฐ๊ธฐ์ ์ ๋ฌด๋ฅผ ๋งก์์ง๋ง, ๋ง์ ์์๋ โ๋์๊ฐ๊ธฐ ์ด๋ ค์ด ์ธ๊ณ๋ฅผ ๋ณด์๋ฒ๋ ธ๋คโ๋ ๊ฐ๊ฐ์ด ์๋ฆฌ ์ก์๋ค. ์ค๋ฆฌ์ฝ๋ฐธ๋ฆฌ์์ ๊ฒฝํํ ์๋๊ฐ, ํ์ , ๋ฏธ๋๋ฅผ ํฅํ ๋์ ์ ์ ์ ์๊ณ ๋ ๋ค์๋ ์ด์ ์ ์ผ์์ผ๋ก ๋ณต๊ทํ ์ ์์๋ค.
๊ฒฐ๊ตญ ์ ๋ ์ค์ค๋ก ์ง์ํด ์ ๋ณด์์คํ ๋ถ๋ฌธ์ผ๋ก ๋ถ์๋ฅผ ์ฎ๊ธฐ๊ธฐ๋ก ํ๋ค. ์ดํ DX๋ฅผ ํฌํจํ ๋ค์ํ ํ๋ก์ ํธ๋ฅผ ๋ด๋นํ๋ฉฐ ๊ธฐ์ ๊ณผ ๊ฒฝ์์ ์๋ ์ญํ ์ ํ๊ฒ ๋๋ค. ๊ทธ๋ฆฌ๊ณ 2021๋ , ๋ฏธ์ฐ๋น์ ๋จธํฐ๋ฆฌ์ผ์ CIO๋ก ์๋ฆฌ๋ฅผ ์ฎ๊ฒผ๊ณ , ์ง๊ธ์ ๊ธฐ์ ์ ๋์งํธ ์ ๋ต์ ์ด๋๋ ์์น์์ ๋ฏธ๋๋ฅผ ํฅํ ๋์ ์ ์ด์ด๊ฐ๊ณ ์๋ค.
Q: ERP ํ๋ก์ ํธ๋ฅผ ์ธ ๋ฒ์ด๋ ์ถ์งํ๋ค๊ณ ๋ค์๋ค. ์ด๋ค ์ ์ด ๊ฐ์ฅ ์ด๋ ค์ ๋?
A: ๋์ ๊ฒฝ๋ ฅ์์ ๊ฐ์ฅ ํฐ ๋์ ์ ๋จ์ฐ ERP ๋์
ํ๋ก์ ํธ์๋ค. ์ง๊ธ๊น์ง ์ด ์ธ ๋ฒ, ์ค๋จ ์๊ธฐ์ ๋น ์ง ERP ํ๋ก์ ํธ๋ฅผ ๋ค์ ์ด๋ ค๋ธ ๊ฒฝํ์ด ์๋ค. ๊ฐ๊ฐ์ ํ๋ก์ ํธ๋ ์ ์์๊ฐ ๋ํญ์ ๋น ์ ธ ์ฌ์ค์ ๋ฉ์ถฐ์ ์ํ์์ ์ ๊ฐ ํฌ์
๋ผ, ์ ์ฒด ๊ตฌ์กฐ๋ฅผ ์ ๋นํ๊ณ ๋ค์ ๊ถค๋์ ์ฌ๋ ค ์์ฑ๊น์ง ์ด๋์ด์ผ ํ๋ ์ํฉ์ด์๋ค. ๊ธ์ก๋ ๊ท๋ชจ๋ ๋ฐฉ๋ํด, CIO๋ก์์ ์ฌ๊ณ ๋ฐฉ์๊ณผ ํ๋ ์์น์ ํ์ฑํ ๋งค์ฐ ์ค์ํ ๊ฒฝํ์ด์๋ค.
๋ด ๊ฒฝ๋ ฅ์์ ๋ ํนํ ์ ์ด ์๋ค๋ฉด, ์์ฐ๊ธฐ์ ์์ IT๋ก ์ปค๋ฆฌ์ด๋ฅผ ์ ํํ ์ , ๊ทธ๋ฆฌ๊ณ ์ค๋ฆฌ์ฝ๋ฐธ๋ฆฌ ํ๊ฐ์ด๋ฐ์ ์ผํ ๊ฒฝํ์์ ๋น๋กฏ๋ ๊ฒ์ด๋ผ ์๊ฐํ๋ค. ๊ท๊ตญ ํ์๋ ๊ธฐ์ ๋ด๋ถ ์ ๋ฌด์ ๊ทธ์น์ง ์๊ณ ๋ค์ํ ์ ๊ณ์์ ๊ฒฝํ์ ์์๋ค. ์๋ฅผ ๋ค์ด ์์ ํํ๊ณต์ ํํ์์์ IT ๊ด๋ จ ํ๋, ๊ธฐ์ ๊ฐ ๊ฑฐ๋์ ์ ์ํ(EDI) ์ถ์ง, ๊ตญ๋ด์ธ ๋ํ ๋์ข ๊ธฐ์ 22๊ฐ์ฌ๊ฐ ์ฐธ์ฌํ ๊ธ๋ก๋ฒ ํํ์ ํ ์ด์ปค๋จธ์ค ํ๋ซํผ ๊ตฌ์ถ ๋ฑ ์ ๊ณ ์ ์ฒด๋ฅผ ์์ฐ๋ฅด๋ ํ๋ก์ ํธ์๋ ๊ด์ฌํ๋ค.
โํ์ฅ๊ณผ ๋ณธ์ฌโ, โ๊ตญ๋ด์ ํด์ธโ, โ์ ๋ฌด์ ITโ ๊ฐ์ด ๊ฒฝ๊ณ๋ฅผ ๋๋๋ค๋ฉฐ ์ผํด์จ ๊ฒฝํ์ ํ์ฌ CIO๋ก์์ ์์ผ์ ํ๋จ๋ ฅ์ผ๋ก ์ด์ด์ง๊ณ ์๋ค.
์ ๊ฐ ์ค์ํ๊ฒ ์ฌ๊ธฐ๋ ๊ฒ์ โ๋์์ ์ผ์ ์ง์คํด ์ต์ ์ ๋คํ๋ ๊ฒโ์ด๋ค. ์ง๋์น๊ฒ ๊ตฌ์ฒด์ ์ธ ๋ชฉํ๋ฅผ ์ธ์ฐ๋ฉด ์คํ๋ ค ์ฅ๊ธฐ์ ๊ฐ๋ฅ์ฑ์ ์ขํ๋ค๊ณ ์๊ฐํ๊ธฐ ๋๋ฌธ์, ์๋์ ์ผ๋ก ๋ช ํํ ๋ชฉํ๋ฅผ ์ ํด๋์ง ์๊ณ ์ง๊ธ ์ด ์๊ฐ์ ๋ชฐ์ ํ๋ ํ๋๋ฅผ ์ ์งํ๊ณ ์๋ค.
ERP์ฒ๋ผ ๋๊ท๋ชจ ํ๋ก์ ํธ์์๋ ์์์น ๋ชปํ ๋ฌธ์ ์ ๋๊ด์ด ๋์์์ด ๋ฐ์ํ๋ค. ๊ทธ ์์์๋ โ๋๋ง์น์ง ์๋๋คโ, โ๋๊น์ง ์ฑ ์์ ๋คํ๋คโ๋ ์์ธ๋ฅผ ์ผ๊ด๋๊ฒ ์ง์ผ์๋ค. ๊ฒฝํ์ ์๊ณ , ์ค์ค๋ก ์ฌ๊ณ ํ๊ณ , ์์ ์ ๊ธฐ์ค์ ๋ฐํ์ผ๋ก ์ ๋ต์ ์ธ์ฐ๋ ๊ฒ. ์ด ๋ถ๋ถ์ด ๋์ ๋ฆฌ๋์ญ์ ๊ทผ๊ฐ์ด๋ค.
๊ทธ๋ฆฌ๊ณ ๋ฌด์๋ณด๋ค ์ค์ํ ๊นจ๋ฌ์์ ์ด๊ฒ์ด๋ค. โํด์ธ๋ฅผ ์์์ผ ์ผ๋ณธ์ ์ดํดํ ์ ์๊ณ , ํ์ฌ๋ฅผ ์์์ผ ์์ฌ๋ฅผ ๋ณผ ์ ์์ผ๋ฉฐ, ์ฌ๋์ ์ดํดํด์ผ ๋น๋ก์ ์์ ์ ์ดํดํ ์ ์๋ค.โ ์ด ํต์ฐฐ์ด ์ ๊ฒ๋ ๊ฐ์ฅ ํฐ ์์ฐ์ด๋ฉฐ, CIO๋ก์ ์์ผ๋ก ๋์๊ฐ๋ ์๋๋ ฅ์ด ๋๊ณ ์๋ค.
Q: ์๋ก์ด ํ๊ฒฝ์์ CIO๋ก ์ผํ๋ฉด์ ๋๋ ๊นจ๋ฌ์์ ๋ฌด์์ด์๋?
57์ธ์ ์ ํํ ์ด์ง์ ๊ฒฐ์ฝ ๋น ๋ฅธ ๊ฒฐ์ ์ด๋ผ๊ณ ํ ์ ์์๋ค. ๊ทธ๋ฌ๋ ๋ง์ ์๋ก์ด ํ๊ฒฝ์ ๋ค์ด์๊ณ ๋ณด๋, ๊ทธ์ ๊น์ง ๋ณด์ด์ง ์์๋ ๊ฒ๋ค์ด ์ ๋ช
ํ๊ฒ ๋ณด์ด๊ธฐ ์์ํ๋ค. ๊ทธ์ค์์๋ ํนํ ๊ฐํ๊ฒ ๋จ์ ๊ฒ์ IT ์ ๋ต์ ์ดํดํ๋ ๋ฐ ํต์ฌ์ด ๋๋ ๋ ๊ฐ์ง ํค์๋, โ๊ฑฐ๋ฒ๋์คโ์ โ์๋์งโ์๋ค.
์ด์ ์ง์ฅ์์๋ ์ฌ๋ฌ ์์ฅ ์ํ์ฌ๋ฅผ ํฌํจํ ๋๊ท๋ชจ ๊ทธ๋ฃน ์ ์ฒด์ ์ ๋ณด์์คํ ์ ํตํฉ์ ์ผ๋ก ๊ด๋ฆฌํ๋ ๋ฏธ์ ์ ๋งก์๋ค. ๋ ๋ฆฝ์ฑ์ด ๊ฐํ ๊ฐ ํ์ฌ๋ฅผ ํ ๋ฐฉํฅ ์๋ ๋ชจ์ผ๊ธฐ ์ํด์๋ ๋จ์ํ ๊ท์ ์ ๊ฐ์ํ๊ฑฐ๋ ์ง์นจ์ ๋ด๋ ค๋ณด๋ด๋ ๋ฐฉ์๋ง์ผ๋ก๋ ์ถฉ๋ถํ์ง ์์๋ค. ๊ฐ ์ ์ฑ ์ด๋ ๋ฐฉ์นจ์ด ํ์ฅ์ ์ด๋ค ์ด์ต์ ์ฃผ๋์ง, ์ ํ์ํ์ง ์ค๋๋ ฅ ์๊ฒ ์ค๋ช ํ๋ ๊ณผ์ ์ด ํ์ํ๋ค.
๊ฑฐ๋ฒ๋์ค์ ๊ธฐ๋ฐ ์์์ ์๋์ง๊ฐ ์๊ธฐ๊ณ , ๊ตฌ์ฑ์ ํ ์ฌ๋ ํ ์ฌ๋์ด ๋ฉ๋ํด ์ค์ค๋ก ์์ง์ด๊ธฐ ์์ํ๋ ๊ตฌ์กฐ๋ฅผ ๋ง๋๋ ๊ฒ. ์ ๋ ๊ทธ ๊ตฌ์กฐ ์ค๊ณ์ผ๋ง๋ก ์ง์ ๊ฐ๋ฅํ IT ์ ๋ต์ ๋ณธ์ง์ด๋ผ๋ ์ ์ ์๋กญ๊ฒ ๊นจ๋ฌ์๋ค.
DX๋ฅผ ์ถ์งํ๋ ๊ณผ์ ์์๋ ๊ฐ์ ๊ตํ์ ์ป์๋ค. ํฑ๋ค์ด ๋ฐฉ์์ ์ ์ฌ์ ๋ณํ๋ฅผ ์ผ์ผํฌ ์ ์๋ ๊ฐํ ์ถ์ง๋ ฅ์ด ์์ง๋ง, ๋ฐํ ์ ์ ํ์ฅ์ ์ ์ ์ธ์ฌ๊ฐ ๊ณผ์ ๋ฅผ ์ค์ค๋ก์ ์ผ๋ก ๋ฐ์๋ค์ด๊ณ ๋์ ํ๋ฉด์ ์ฑ์ฅ์ ๊ธฐํ๋ฅผ ๋ง๋ค์ด๋ธ๋ค. ์ด ๋ ์ถ์ด ์๋ก ๋ง๋ฌผ๋ฆด ๋, DX๋ ๋น๋ก์ ์กฐ์ง ์ ์ฒด๋ก ํ์ฐ๋๊ณ ์ค์ง์ ์ธ ๋ณํ๋ก ์ด์ด์ง๋ค.
Q: ๋ฆฌ๋์ญ์์ ๊ฐ์ฅ ์ค์ํ๋ค๊ณ ๋๋ผ๋ ์์๋ ๋ฌด์์ธ๊ฐ?
37๋
์ ๊ฑธ์น ๋น์ฆ๋์ค ๊ฒฝ๋ ฅ ์์์ ์ ๊ฐ ๊ฐ์ฅ ๊น์ด ๋๋ ๊ฒ์ โ์ฌ๋์ ์ด๋ป๊ฒ ์์ง์ด๊ฒ ํ ๊ฒ์ธ๊ฐโ๋ผ๋ ๊ณผ์ ์ ์ค์์ฑ์ด๋ค. ํ๋ก์ ํธ, ๋ถํ ์ง์, ๋๋ฃ, ์ดํด๊ด๊ณ์, ๊ทธ๋ฆฌ๊ณ ์์ฌ๊น์ง ๋ชจ๋ ๊ด๊ณ ์์์ ๊ฐ์ฅ ์ด๋ ต๊ณ ๋์์ ๊ฐ์ฅ ํฐ ๊ฐ์น๋ฅผ ๊ฐ์ง ๋์ ์ ๊ฒฐ๊ตญ โ๊ฒฝ์์ ์ด๋ป๊ฒ ์์ง์ผ ๊ฒ์ธ๊ฐโ๋ผ๋ ์ ์ด์๋ค.
์ด๋ฅผ ์ํด์๋ ๋จผ์ , ์์ ์ด ๋ฌด์์ ํ๊ณ ์ถ์์ง, ๋ฌด์์ ์ ๋ฌํ๊ณ ์ถ์์ง์ ๋ํ ํ๊ณ ํ ์ถ์ ๊ฐ์ ธ์ผ ํ๋ค. ๊ทธ ์ถ์ด ํ๋ค๋ฆฌ๋ฉด ์ฌ๋๋ค์ ๋ฐ๋ผ์ค์ง ์๋๋ค. ๋๋ถ์ด ๊ทธ ์ถ์ ๋ช ํํ ์ธ์ด๋ก ํํํ๋ ๋ฅ๋ ฅ๋ ํ์ํ๋ค. ๋ง๋ก ํํ๋ฅผ ๊ฐ์ถ์ง ์์ผ๋ฉด ์๊ฐ๊ณผ ์์ง๋ ๊ฒฐ์ฝ ์ ๋ฌ๋์ง ์๋๋ค.
๋ง์ด ์ ๋ฌ๋๊ธฐ ์ํด์๋ ์ ๋ขฐ๊ฐ ์ ์ ๋์ด์ผ ํ๋ค. ์ ๋ขฐ๊ฐ ํ์ฑ๋๋ฉด ์๋๋ ๊ณต๊ฐํ๊ณ , ๊ณต๊ฐ์ ํ๋์ ๋ณํ๋ฅผ ์ด๋๋ค. ์ด ์ผ๋ จ์ ๊ณผ์ ์ฆ ์ถ์ ์ธ์ฐ๊ณ , ์ธ์ด๋ก ์ ๋ฆฌํ๊ณ , ์ ๋ขฐ๋ฅผ ์๊ณ , ๊ณต๊ฐ์ ์ป์ด, ํ๋์ ์ ๋ํ๋ ๊ณผ์ ์ ์ผ๋ง๋ ์๋ฆ๋ต๊ฒ ์ํ์ํค๋๋๊ฐ ๋ฆฌ๋์๊ฒ ์ฃผ์ด์ง ๊ฐ์ฅ ํฐ ๊ณผ์ ๋ผ๊ณ ๋๋ผ๊ณ ์๋ค.
๊ทธ ๊ธฐ๋ฐ์๋ โ์๊ธฐ๋ฅผ ์๋ ๊ฒโ์ด ์๋ค. ๋ฌผ๋ก ์์ ์ ์๋ค๋ ๊ฒ์ ์ฒ ํ์ ์ด๋ฉฐ ๊ฒฐ์ฝ ์ฌ์ด ์ผ์ด ์๋๋ค. ํ์ง๋ง โํด์ธ๋ฅผ ์๋ฉด ์ผ๋ณธ์ด ๋ณด์ด๊ณ , ์ผ๋ณธ์ ์๋ฉด ์์ฌ๊ฐ ๋ณด์ด๋ฉฐ, ์์ฌ๋ฅผ ์๋ฉด ์์ ์ด ๋ณด์ธ๋คโ๋ ์ํ์ ๊นจ๋ฌ์์ด ๋ฆฌ๋๋ก์์ ์์ผ๋ฅผ ํ์ธต ๋ํ์ค๋ค.
Q: CIO๊ฐ ๊ฒฝ์์๊ฐ ๋ ์ ์์๊น?
์ง๊ธ CIO๋ก์์ ์ญํ ์ ๋์๋ณด๋ฉด, ๋ ๊ฐ์ง ์ ํ์ด ์๋ค๊ณ ๋๋๋ค. ํ๋๋ โ์ ๋ณด์์คํ
์ ์ด๊ดํ๋ CIOโ, ๊ทธ๋ฆฌ๊ณ ๋ค๋ฅธ ํ๋๋ โ๊ฒฝ์์ ํ ์ถ์ ๋ด๋นํ๋ CIOโ๋ค.
๋๋ ์ง๊ธ๊น์ง ํ์๋ฅผ ๋ชฉํ๋ก ํด ์๋ค. IT ์ ๋ฌธ์ฑ์๋ง ๋จธ๋ฌด๋ฅด์ง ์๊ณ , ๋ฐ๊นฅ์ธ์์ ์ดํดํ๊ณ , ์ ๊ณ๋ฅผ ๋๋๋ค๋ฉฐ, ํ์ฅ๊ณผ ๊ฒฝ์์ ์๋ ์๊ฐ์ด CIO์ ๊ฐ๋ฅ์ฑ์ ๋ํ ์ค๋ค๊ณ ๋ฏฟ๊ณ ์๋ค.
๊ทธ๋์ ๋ด๊ฐ ์ค์ํ๊ฒ ์๊ฐํ๋ ๊ฒ์ด ๋ฐ๋ก ์ธ๋ฌธํ ์ฆ ์ธ๋ฅ๊ฐ ์ถ์ ํด ์จ ์งํ๋ค.
์๋ก์ด ๊ฒ์ ๋ฌด(็ก)์์ ๊ฐ์๊ธฐ ์๊ฒจ๋๋ ๊ฒ ์๋๋ผ, ์ฌ๋ฌ ์งํ๊ฐ ๊ฒฐํฉ๋๋ฉฐ ์ฐฝ๋ฐํ๋ ๊ฒ์ด๋ค. ์์ฑํ AI๊ฐ ๋ฑ์ฅํ๋ฉด์, ์ฐ๋ฆฌ๋ ๊ทธ ์ด๋ ๋๋ณด๋ค ์ฐฝ์กฐ์ ์ธ ๊ฐ์น๋ฅผ ๋ง๋ค์ด๋ผ ๊ธฐํ๋ฅผ ๊ฐ๊ฒ ๋๋ค.
์ ๋ณด์์คํ ๋ถ์ ์ฌ๋ฌ๋ถ๋ ์ด๋ฐ ๊ด์ ์ ๊ผญ ๊ฐ์ ธ ๋ณด๊ธธ ๋ฐ๋๋ค. ๋๋ก๋ ์ ๋ฌธ ์์ญ์ ๋์ด์ ๋ค๋ฅธ ๋ถ์ผ๋ก ๊ฑด๋๊ฐ ๋ณด๊ณ , ํ์ฅ์ ๋ค๊ฐ๊ฐ๊ณ , ๊ฒฝ์๊ณผ ๋ํํด ๋ณด๋ ๊ฒฝํ๋ค์ด ์์ผ ๋, CIO๋ก์์ ์๋ก์ด ๊ฐ๋ฅ์ฑ์ด ์ด๋ฆด ๊ฑฐ๋ผ๊ณ ํ์ ํ๋ค.
๋ํ ์ผ๋ณธ IT ์ฐ์ ์๋ ๊ตฌ์กฐ์ ํน์ง์ด ์๋ค. ์์คํ ์์ง๋์ด์ ์ฝ 70%๊ฐ ์ธ๋ถ ํํธ๋ ์์์ด๋ผ๋ ํ์ค์ด๋ค. ๋ด์ฌํ์ ํ์์ฑ์ด ๊ฐ์กฐ๋์ง๋ง ํ๊ณ๋ ๋๋ ทํ๋ค. ๊ทธ๋์ ๋ฒค๋๋ ์ปจ์คํดํธ๋ฅผ ๋จ์ํ ๊ณต๊ธ์๊ฐ ์๋๋ผ ํจ๊ป ์ธ์ฐ๋ โ์ ์ฐโ๋ก ์ธ์ํ๊ณ ํ๋ ฅ ๊ด๊ณ๋ฅผ ๊ตฌ์ถํด์ผ ํ๋ค๊ณ ์๊ฐํ๋ค.
๊ณ ๊ฐ์ฌ๊ฐ ์ผ๋ฐฉ์ ์ผ๋ก ์ง์ํ๋ ๊ด๊ณ๋ฅผ ๋์ด์, ์๋ก ๋ฐฐ์ฐ๊ณ ์งํ๋ฅผ ๋ชจ์ผ๋ ํํธ๋์ญ์ ๋ง๋๋ ๊ฒ. ์ด๋ฌํ ๊ด๊ณ๊ฐ ์์ผ๋ก์ ITยทDX ๋ถ์ผ์์ ์ง์ ํ ๊ฐ์น ์ฐฝ์ถ์ ์ด๋ ํต์ฌ์ด๋ผ๊ณ ๋ฏฟ๊ณ ์๋ค.
Q: CIO๋ก์ ์ค์ํ๊ฒ ์ฌ๊ธฐ๋ ์ฒ ํ์ด๋ ๊ฐ์น๊ด์ ๋ฌด์์ธ๊ฐ?
๊ฐ์ธ์ ์ผ๋ก ์ค์ํ๊ฒ ์ฌ๊ธฐ๋ ๋ ๊ฐ์ง ํค์๋๊ฐ ์๋ค. 21์ธ๊ธฐ๋ฅผ ์ด์๊ฐ๋ ์ธ๋ฅ๊ฐ ๋ฐ๋์ ์์คํ ํด์ผ ํ๋ค๊ณ ์๊ฐํ๋ ๊ฐ์น, ๋ฐ๋ก โ์ด์จ์ด๋์ค(๊นจ๋ฌ์ยท์์)โ์ โ์ปดํจ์
(์ดํ์ฑยท๋ฐฐ๋ ค)โ์ด๋ค. ์ด ๋ ๊ฐ์ง๋ ์ ๊ฐ ๋ฏธ์ฐ๋น์ ๋จธํฐ๋ฆฌ์ผ์ CIO๋ก ๋ถ์ํ์ ๋๋ถํฐ, ํ์ฌ๊ฐ ๊ธฐ๋ํ๋ ์ญํ ๊ณผ ์ผ๋ณธ ์ ์กฐ์
์ ์ฒด๋ฅผ ๋ ๊ฐํ๊ฒ ๋ง๋ค๊ณ ์ ํ๋ ์ ๊ฐ์ธ์ ์๋ง ๋ชจ๋์์ ์ค์ฌ์ถ์ด ๋์ด์๋ค.
๋ฏธ์ฐ๋น์ ๋จธํฐ๋ฆฌ์ผ์ โ๋ฏธ์ฐ๋น์ ๋จธํฐ๋ฆฌ์ผ ๊ทธ๋ฃน IT Wayโ๋ผ๋ ์์น์ ์๋ฆฝํ๊ณ , ์ด๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ๋ค์ํ IT ์ ๋ต์ ์ถ์งํ๊ณ ์๋ค. ์ง๊ธ ์์ฑํ AI๋ ํผํ ์ ์๋ ํต์ฌ ์ฃผ์ ๋ก ๋ ์ฌ๋๊ณ , ์ค์ํ ๊ฒ์ AI๊ฐ ๋ฌด์์ ๋ง๋๋๊ฐ๊ฐ ์๋๋ผ โ์ฌ๋์ด ์์ฑํ AI๋ฅผ ํ์ฉํด ์ด๋ค ๊ฐ์น๋ฅผ ๋ง๋ค์ด๋ด๋๊ฐโ์ ์๋ค. ์์ฑํ AI๋ ์ด๋๊น์ง๋ IT ๋๊ตฌ์ ํ๋์ด๊ณ , ์ฃผ์ฒด๋ ์ธ๊ฐ์ด๋ค. ๊ทธ๋์ ์ ๋ ์ธ์ ๋ โ์ฌ๋ ์ค์ฌโ์ด๋ผ๋ ์ฌ๊ณ ๋ฐฉ์์ ์ํ์ผ๋ก ๊พธ์คํ ๊ฐ์กฐํด ์๊ณ , ์ด ์ฒ ํ์ ๊ธฐ๋ฐ์ผ๋ก ์ฌ๋ฌ ์ ์ฑ ์ ํผ์ณ์๋ค.
์ผ๋ณธ ์ ์กฐ์ ์ด ๊ฐํด์ง๊ธฐ ์ํด์๋ ๊ธฐ์ ๊ฐ์ ๊ฒฝ๊ณ๋ฅผ ๋์ด์๋ ์ฐ๋์ ๋ํ๊ฐ ํ์์ ์ด๋ค. ์ ๋ ์ด์ง ์ ์ ํฌํจํ ์ฝ 5๋ ๋์ 70์ฌ ๊ฐ ๊ธฐ์ , 6,000๋ช ์ด์์ ๊ด๊ณ์๋ค๊ณผ ์คํฐ๋, ๊ฐ์ฐ ๋ฑ์ ํตํด ์ง์์ ์ผ๋ก ์๊ฒฌ์ ๋๋์ด ์๋ค. ๊ทธ ๊ณผ์ ์์ ์ ์๊ฐ์ ๊ณต๊ฐํด์ฃผ๋ ์ฌ๋๋ค์ ๋ง์ด ๋ง๋ฌ๊ณ , ๊ทธ๋ถ๋ค๊ณผ์ ๊ต๋ฅ ์์์ ์ ์์ ๋ ์ฑ์ฅํ๊ณ ์์์ ์ค๊ฐํ๊ณ ์๋ค. ์ด๋ฌํ ์ง์ ์ถ์ ์ด ์๋ก์ด ์ ์ฑ ๊ณผ ์๋๋ฅผ ๋ง๋ค์ด๋ด๋ ์ค์ํ ์๋๋ ฅ์ด ๋๋ค๊ณ ๋ฏฟ๋๋ค.
๋ด๊ฐ ๋ฌด์๋ณด๋ค๋ ์ ๋ฌํ๊ณ ์ถ์ ๋ฉ์์ง๋ ๋จ์ํ๋ค. ๋ฐ๋ก โ๋ชจ๋ ๊ธฐ์ ์ ์ฌ๋์ ํ๋ณตํ๊ฒ ํ๋ ๋ฐฉํฅ์ ์งํฅํด์ผ ํ๋คโ์ด๋ค. 100๋ , 200๋ ํ ์ฐ๋ฆฌ์ ํ์์ด ๋์๋ดค์ ๋, โ๊ทธ ์๋๋ฅผ ๊ธฐ์ ์ผ๋ก ๋ฌด์ธ๊ฐ๊ฐ ๋ฐ๋์๋คโ๊ณ ๋งํ ์ ์๋ค๋ฉด, ๊ทธ๊ฒ์ ์ธํฐ๋ท๊ณผ ๊ฐ์ ์ปค๋ค๋ ํ์ ์ผ ๊ฒ์ด๋ฉฐ, ์ง๊ธ ์งํ ์ค์ธ ์์ฑํ AI ์ญ์ ๊ทธ ๋ณ๊ณก์ ์ค ํ๋๋ค.
๊ทธ๋ฆฌ๊ณ ์ฐ๋ฆฌ๊ฐ ์ง๊ธ ๋ฐ๋์ ๋์ ํด์ผ ํ ๋ ํ๋์ ๊ณผ์ ๋ ๋ฏธ๋ ์ธ๋๊ฐ โ์ง๊ตฌ ํ๊ฒฝ์ ์งํค๋ฉด์๋ ๋น์ฆ๋์ค๋ฅผ ํ ์ ์๊ฒ ๋์๋คโ๊ณ ๋งํ ์ ์๋ ์๋๋ฅผ ๋ง๋๋ ๊ฒ์ด๋ค. ๋ฏธ์ฐ๋น์ ๋จธํฐ๋ฆฌ์ผ์ ์์์ํ์ ํต์ฌ์ผ๋ก ์ผ๋ ๊ธฐ์ ์ผ๋ก, ์ด๋ฌํ ๋ฏธ๋์์ ์คํํ๋ ๋ฐ ์ค์ํ ์ญํ ์ ๋งก๊ณ ์๋ค. ๋น์ฆ๋์ค ์ธ๊ณ์์๋ ์ข ์ข โ๋ฌ์ฝคํ ์ด์ผ๊ธฐ๋ง ํด์๋ ์ ๋๋คโ๊ณ ํ์ง๋ง, ์ง๊ตฌ ํ๊ฒฝ์ ์งํค๋ ๋ฌธ์ ์์๋ ์ดํ์ฑ๊ณผ ๋ฐฐ๋ ค๊ฐ ๋ฐ๋์ ํ์ํ๋ค๊ณ ์๊ฐํ๋ค. ์ด๋ ์ธ๋ฅ ์ ์ฒด๊ฐ ๋ ๊น์ด ์ธ์ํด์ผ ํ ๊ฐ์น๋ค.
CIO๋ ๋๊ฐ ํน์ ์ ๋ฌธ ๋ถ์ผ์ ๊ฐ์ ์ ์ง๋ ๊ฒฝ์ฐ๊ฐ ๋ง๊ณ , ๊ฒฝ์์ง๊ณผ ๋๋ฑํ ์์ค์์ ๋ ผ์ํ ์ ์๋ ๋ฅ๋ ฅ์ด ์๊ตฌ๋๋ค. ๊ทธ๋ฌ๋ IT๋ง ์๊ณ ์์ด์๋ ์ถฉ๋ถํ์ง ์๋ค. ํด์ธ์ ์๊ฐ, ์ ๊ณ์ ํ๋ฆ, ๊ทธ๋ฆฌ๊ณ ์ธ๋ฌธํ ๋ฆฌ๊ฐ์ ๋น(้) IT ์์ญ์ ๋ํ ๊ด์ฌ์ด ๋ฐ๋์ ํ์ํ๋ค. ๊ธฐ์ ๊ณผ ์ฐ์ ๋ง๋ค ๊ณผ์ ๋ ๋ค๋ฅด์ง๋ง, IT๋ง ์๊ฐํด์๋ ๋ณธ์ง์ ์ธ ๋ฌธ์ ํด๊ฒฐ์ ๋๋ฌํ ์ ์๋ค. ๊ทธ๋ ๊ธฐ ๋๋ฌธ์ ๊ฐ์์ ์ ๋ฌธ์ฑ์ ์ด๋ฆฌ๋ฉด์๋ ๋ณตํฉ์ ์๊ฐ์ผ๋ก ์ ๊ทผํ๋ ํ๋๊ฐ ์์ผ๋ก์ CIO์๊ฒ ์๊ตฌ๋๋ ์์ธ๋ผ๊ณ ๋ฏฟ๊ณ ์๋ค.
*์ด ๊ธฐ์ฌ๋ CIO ์ฌํฌ์์ ์งํ๋ โ๋ฆฌ๋์ญ ๋ผ์ด๋ธ ์ฌํฌโ์ ๋ด์ฉ์ ๋ฐํ์ผ๋ก ์ผ๋ถ ๊ฐ์ํ์ฌ ๊ตฌ์ฑํ ๊ฒ์
๋๋ค.
dl-ciokorea@foundryco.com
M365 ๊ณ ๊ฐ์ 2026๋ 7์ 1์ผ๋ถํฐ ๋ ๋์ ๊ตฌ๋ ์๊ธ์ ๋ถ๋ดํ๊ฒ ๋ ์ ๋ง์ด๋ค. ๋น์ฆ๋์ค์ฉ์ ๋น๋กฏํด E3ยทE5, ํ๋ก ํธ๋ผ์ธ, ์ ๋ถ์ฉ ๊ตฌ๋ ๋ฑ ๋๋ถ๋ถ์ ์๊ธ์ ๊ฐ ์ํฅ์ ๋ฐ๋๋ค.
MS๋ ์ง๋ 4์ผ ๋ธ๋ก๊ทธ๋ฅผ ํตํด ์ฌ๋ฌ ์๊ธ์ ์ ์ ๊ธฐ๋ฅ์ด ์ถ๊ฐ๋๋ฉด์ ์ธ์์ด ์ด๋ค์ก๋ค๊ณ ๋ฐํ๋ค. ์ฌ๊ธฐ์๋ ํ์ฅ๋ ์ฝํ์ผ๋ฟ ์ฑ ๊ธฐ๋ฅ๊ณผ E3์ ํฌํจ๋๋ MS ๋ํ๋ ํฌ ์คํผ์ค(Microsoft Defender for Office), E5์ ์ ์ฉ๋๋ ์ํ๋ฆฌํฐ ์ฝํ์ผ๋ฟ, ๊ทธ๋ฆฌ๊ณ E3ยทE5๋ฅผ ๋์์ผ๋ก ํ ์ธํ (Intune)์ ์๊ฒฉ ์ง์ ๋ฐ ๊ณ ๊ธ ๋ถ์ ๊ธฐ๋ฅ ๋ฑ์ด ์๋ค.
์๋ก์ด ๊ตฌ๋ ์๊ธ์ ๋ค์๊ณผ ๊ฐ๋ค.
์ด ๊ฐ์ด๋ฐ M365 ๋น์ฆ๋์ค ํ๋ฆฌ๋ฏธ์์ ์ ์ฌ์ฉ์๋น 22๋ฌ๋ฌ, ์คํผ์ค 365 E1์ 10๋ฌ๋ฌ๋ก ๊ธฐ์กด ๊ฐ๊ฒฉ์ ์ ์งํ๋ค. ์ ๋ถ์ฉ M365 ์๊ธ์ ๋ ํ๋์ ๋ฐ๋ผ 5%์์ 10% ์์ค์ ์ธ์์ด ์ ์ฉ๋๋ค. ๋ชจ๋ ์๊ธ์๋ ํ์ ์ฑ์ธ ํ์ฆ(Teams)๊ฐ ํฌํจ๋ผ ์์ผ๋ฉฐ, ํ์ฆ๋ฅผ ์ ์ธํ ๊ฒฝ์ฐ ๋ ๋ฎ์ ์๊ธ์ด ์ฑ ์ ๋๋ค.
๊ฐํธ๋ ์ ๋๋ฆฌ์คํธ ์ญ ๋ค์ด๊ธ๊ณผ ์คํฐ๋ธ ํ์ดํธ๋ ์ด๋ฒ ์กฐ์น์ ๋ํด โ์ต๊ทผ ์ด์ด์ง๋ ๊ฐ๊ฒฉ ์ ์ฑ ๋ณํ๋ ๊ณ ๊ฐ์ ์ฐ๋ ค์ ํผ๋ก๊ฐ์ ๋์ฑ ์ฌํ์ํฌ ๊ฒโ์ด๋ผ๊ณ ์ง์ ํ๋ค.
MS๋ 2022๋ ์๋ M365 ๊ฐ๊ฒฉ์ 9%์์ 25% ๋ฒ์๋ก ์ธ์ํ ๋ฐ ์๋ค. ์ต๊ทผ์๋ M365 ๋ฑ ์ฃผ์ ์ ํ์ ์ํฐํ๋ผ์ด์ฆ ๊ณ์ฝ(EA) ์กฐ๊ฑด์ ๋ณ๊ฒฝํด, ๋๊ท๋ชจ ๊ณ ๊ฐ์๊ฒ ์ ๊ณต๋๋ ์ฌ์ฉ์ ์ ๊ธฐ๋ฐ ํ ์ธ ์ ์ฑ ์ ๋จ๊ณ์ ์ผ๋ก ํ์งํ๋ค.
๊ฐํธ๋ ์ ๋๋ฆฌ์คํธ๋ค์ ๊ธฐ์ ์ด ์ด๋ฒ ์ธ์์ ๋ฐ๋ฅธ ์ฌ๋ฌด์ ๋ถ๋ด์ ์ค์ด๋ ค๋ฉด โํ์ ์ ๋ต์ ์ ๊ทน ํ์ฉํ๊ณ , ๋์์ ๊ฒํ ํ๋ฉฐ, ๋ผ์ด์ ์ค ํ ๋น์ ์ต์ ํํด์ผ ํ๋คโ๋ผ๊ณ ์กฐ์ธํ๋ค.
๋ํ ๊ฐ๋ฅํ๋ค๋ฉด 7์ 1์ผ ๊ฐ๊ฒฉ ๋ณ๊ฒฝ ์ด์ ์ ๊ณ์ฝ์ ์กฐ๊ธฐ ๊ฐฑ์ ํ๋ ๋ฐฉ์์ ๊ณ ๋ คํ ๊ฒ์ ์ ์ํ๋ค. ์ด๋ ๊ฒ ํ๋ฉด ์๊ธ ์ธ์์ ๋ค์ ๊ฐฑ์ ์์ ๊น์ง ๋ฆ์ถ ์ ์๊ธฐ ๋๋ฌธ์ด๋ค.
๊ฐํธ๋๊ฐ ์ต๊ทผ IT ๋ฆฌ๋ 215๋ช ์ ๋์์ผ๋ก ์งํํ ์กฐ์ฌ์ ๋ฐ๋ฅด๋ฉด, M365 ๊ณ ๊ฐ์ 17%๋ ๋์ ์๋ฃจ์ ์ ๊ฒํ ์ค์ด๋ฉฐ, ๊ตฌ๋ ๋น์ฉ์ ์ถฉ๋ถํ ๊ฐ์น๋ฅผ ๋๋๋ค๊ณ ๋ตํ ๋น์จ์ 5%์ ๋ถ๊ณผํ๋ค.
MS๋ ์ฌํด ์ด ์ค์ ๋ฐํ์์ ์ ์ธ๊ณ ์์ ์ฉ M365 ์ฌ์ฉ์๊ฐ 4์ต 3์ฒ๋ง ๋ช ์ ๋์ด์ฐ๋ค๊ณ ๋ฐํ๋ค.
J. ๊ณจ๋ ์ด์์์์ด์ธ ์ ์ ๋๋ฆฌ์คํธ ์ญ ๊ณจ๋๋ MS๊ฐ ์ด์ ๋ถํฐ ์ฃผ๊ธฐ์ ์ผ๋ก ๊ฐ๊ฒฉ์ ์ธ์ํด ์๋ค๊ณ ์ธ๊ธํ๋ฉฐ, โAI ๊ธฐ๋ฅ์ ์ด์ํ๊ธฐ ์ํด ์๋นํ ์ถ๊ฐ ์ฐ์ฐ์ด ํ์ํด์ง ๋งํผ, ์ด๋ฅผ ์ง์ํ๋ ๋๊ท๋ชจ ํด๋ผ์ฐ๋ ์ธํ๋ผ ์ด์ ๋น์ฉ์ ํ์ํ๋ ค๋ ์๋๋ ์ดํดํ ๋งํ๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
๊ณจ๋๋ ์ด๋ฒ ๊ฐ๊ฒฉ ์ธ์์ด ๊ณ ๊ฐ ์์ ํฐ ์ํฅ์ ๋ฏธ์น์ง๋ ์์ ๊ฒ์ผ๋ก ๋ด๋ค๋ดค๋ค. ๊ทธ๋ โ๋๋ถ๋ถ์ ๊ณ ๊ฐ์ด ์ด๋ฏธ MS ์ํ๊ณ์ ๊น์ด ๋ฌถ์ฌ ์์ด ๊ฒฐ๊ตญ ์ด๋ฒ ์กฐ์ ๋ ๋ฐ์๋ค์ด๊ฒ ๋ ๊ฒโ์ด๋ผ๋ฉฐ โ์์ฆ ๊ตฌ๊ธ๊ณผ์ ๊ฐ๊ฒฉ ๊ฒฝ์์ด ์น์ดํ๊ธด ํ์ง๋ง, ์ํฐํ๋ผ์ด์ฆ ์์ฅ์์ MS์์ ๊ตฌ๊ธ ์คํผ์ค๋ก ๋๊ฑฐ ์ด๋ํ๋ ํ๋ฆ์ ๋ณด์ด์ง ์๋๋ค. ๋ค๋ง ์ค์๊ธฐ์
๋ฐ ์ค๊ธฐ์
์์๋ ๊ตฌ๊ธ์ ์ฑ์ฅ์ธ๊ฐ ๋๋ ทํ๋คโ๋ผ๊ณ ์ง๋จํ๋ค.
dl-ciokorea@foundryco.com
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