보고서에 따르면, 2025년 한 해 동안 전 세계 기술 업계에서 약 24만 4,851개의 일자리가 사라진 것으로 나타났다. 영국에 본사를 둔 금융 서비스 기업 래셔널FX는 전 세계 기업이 효율성과 수익성, AI 기반 생산성에 초점을 맞추기 위해 운영 방식을 재편한 결과라고 분석했다.

트루업(TrueUp), 테크크런치(TechCrunch), 미국 여러 주의 WARN 데이터베이스에 보고된 감원 사례를 분석한 래셔널FX는 경제적 불확실성과 고금리 환경, AI와 자동화 도입을 주요 배경으로 지목했다. 보고서는 이 같은 요인으로 인해 2025년이 “2022년 팬데믹 이후 조정 국면에 이어 또 한번 지속적인 구조조정이 이어진 시기”라고 진단했다.

기업은 2025년 감원의 가장 빈번한 원인으로 AI와 자동화를 꼽았다. 래셔널FX에 따르면 일부 기업은 새로운 기술에 대응해 직원 재교육을 진행했지만, 상당수는 직무를 완전히 대체하는 방식으로 인력 구조를 조정했다.

래셔널FX의 애널리스트 앨런 코언은 성명을 통해 “2025년 기술업계 감원은 단기적인 비용 절감이 아니라 구조적 재편을 가속화하는 과정에서 전 세계 수십만 명의 근로자를 일터에서 밀어냈다”라고 설명했다. 그는 “고금리, 무역 제한, 지정학적 불확실성 같은 거시경제적 압박이 기업 신뢰에 계속 부담으로 작용했지만, 지난해 일자리 감소의 가장 지배적인 요인은 자동화와 인공지능의 빠른 확산이었다”라고 분석했다.

이번 분석에서는 미국 기술 기업이 전체 글로벌 기술업계 감원의 대부분을 차지한 사실도 드러났다. 이들 기업은 전 세계 기술업계 감원의 약 69.7%를 차지했으며, 이에 따라 미국 기술 기업의 국내외 사업장에서 17만 명이 넘는 인력이 감축된 것으로 나타났다.

미국 내 기술업계 감원, 캘리포니아가 최다

래셔널FX 보고서에 따르면, 2025년 미국 기술 업계에서 최다 감원을 기록한 곳은 캘리포니아주였다. 캘리포니아에서는 올해 7만 3,499개의 일자리가 줄어들며, 이는 미국 전체 기술업계 감원의 약 43.08%를 차지했다. 보고서는 워싱턴주에서도 연초 이후 4만 2,221개의 기술 관련 일자리가 사라졌으며, 이는 전체의 24.74%에 해당한다고 밝혔다.

래셔널FX에 의하면 2025년 미국에서 기술업계 감원이 가장 많았던 주는 다음과 같다.

• 캘리포니아: 7만 3,499개(43.08%)
• 워싱턴: 4만 2,221개(24.74%)
• 뉴욕: 2만 6,900개(15.8%)
• 텍사스: 9,816개(6%)
• 매사추세츠: 3,477개

“2025년 최다 인력 감축 기업은 인텔”

래셔널FX 보고서에 따르면 2025년 한 해 동안 가장 많은 인력 감축을 단행한 기업은 인텔이었다.

보고서는 2024년 말 기준 약 10만 9,000명을 고용하고 있던 인텔이 2025년 말까지 인력을 약 7만 5,000명 수준으로, 약 3만 4,000개의 직무를 줄일 계획을 발표했다고 밝혔다. 보고서는 2025년 대규모 감원을 겪은 다른 주요 미국 기술 기업으로 아마존, 마이크로소프트(MS), 버라이즌, 타타컨설턴시서비스, 액센추어, IBM, HP를 꼽았다.

• 아마존: 2만 명 이상 감원
• 마이크로소프트: 1만 9,215명 감원
• 버라이즌: 1만 5,000명(전체 인력의 15%)
• 타타 컨설팅 서비스: 1만 2,000명 감원
• 액센추어: 1만 1,000명 감원
• IBM: 9,000명 감원
• HP: 6,000명 감원(전체 인력의 10%)

코언은 “과거 과잉 채용에 따른 감원과 달리, 2025년의 인력 감축 상당수는 일시적인 조정이 아닌 영구적인 변화였다. 기업이 AI 중심 운영 모델로 재편되는 과정에서 직무 자체가 사라진 경우가 많았다”라고 설명했다. 그는 이어 “자동화에 대규모 투자가 이뤄졌음에도 이런 구조조정이 즉각적인 효율성 개선으로 이어지지 않은 경우도 적지 않다. 이는 AI 기반 생산성에 대한 기대와 대규모 인력 전환의 현실 사이의 괴리가 점점 커지고 있음을 시사한다”라고 분석했다.

AI와 자동화, 일자리 축소의 핵심 요인

래셔널FX는 2025년 인력 감원의 가장 빈번한 원인으로 AI와 자동화를 지목했다. 보고서에 따르면 일부 기업은 직원 재교육을 선택했지만, 일부는 직무 자체를 대체하는 방향으로 대응했다. 특히 데이터 처리, 고객 지원, 인사, 행정 부문에서 변화가 두드러졌다.

아마존은 지난해 10월 28일 1만 4,000명 감원을 확정하며, 회사의 전략적 초점이 AI에 맞춰져 있고 해당 기술이 가져올 변화에 적응하고 있다고 밝혔다. 앞서 2023년 영국 통신사 BT는 2030년까지 직원과 계약직을 포함해 5만 5,000개의 일자리를 감축할 계획이라고 발표했다. 보고서에 따르면, 2025년 3월 말 기준 BT의 직원 수는 약 8만 5,300명으로, 2024년 같은 시점보다 약 6,400명 줄어든 것으로 나타났다.

전문 서비스 기업 액센추어는 AI 역량 재교육 전략의 일환으로 불과 3개월 만에 1만 1,000명의 인력을 감축했다고 밝혔다. HP 역시 2025년 11월, 전사적인 AI 통합을 추진하는 과정에서 6,000개 직무를 줄이겠다고 발표했다. 세일즈포스의 CEO 마크 베니오프도 AI가 세일즈포스 운영 전반에 미치는 영향을 이유로 고객 지원 인력을 4,000명 감축했다고 설명했다.

코언은 “자동화와 전략적 전환, 경제적 불확실성 등 구조적인 압박 요인이 지속되고 있어 2026년에도 감원이 끝나지는 않을 가능성이 크다. 적어도 1분기까지는 이 흐름이 이어질 것”이라고 전망했다. 그는 이어 “일부 세부 산업은 위축이 계속되겠지만, AI 관련 직무를 중심으로 다른 영역에서는 비교적 활발한 채용이 나타날 수 있다”라고 내다봤다.
dl-ciokorea@foundryco.com

Today’s CIOs face increasing expectations on multiple fronts: They’re driving operational and business strategy while simultaneously leading AI initiatives and balancing related compliance and governance concerns.

Additionally, Ranjit Rajan, vice president and head of research at IDC, says CIOs will be called to justify previous investment in automation while managing related costs.

“CIOs will be tasked with creating enterprise AI value playbooks, featuring expanded ROI models to define, measure, and showcase impact across efficiency, growth, and innovation,” Rajan says.

Meanwhile, tech leaders who spent the past decade or more focused on digital transformation are now driving cultural change within their organizations. CIOs emphasize that transformation in 2026 requires a focus on people as well as technology.

Here’s how CIOs say they’re preparing to address and overcome these and other challenges in 2026.

Talent gap and training

The most often cited challenge by CIOs is a consistent and widening shortage of tech talent. Because it’s impossible to meet their objectives without the right people to execute them, tech leaders are training internally as well as exploring non-traditional paths for new hires.

In CIO’s most recent State of the CIO survey 2025, more than half the respondents said staffing and skills shortages “took time away from more strategic and innovation pursuits.” Tech leaders expect that trend to continue in 2026.

“As we look at our talent roadmap from an IT perspective, we feel like AI, cloud, and cybersecurity are the three areas that are going to be extremely pivotal to our organizational strategy,” says Josh Hamit, CIO of Altra Federal Credit Union.

Hamit said the company will address the need by bringing in specialized talent, where necessary, and helping existing staff expand their skillsets. “As an example, traditional cybersecurity professionals will need upskilling to properly assess the risks of AI and understand the different attack vectors,” he says.

Pegasystems CIO David Vidoni has had success identifying staff with a mix of technology and business skills and then pairing them with AI experts who can mentor them.

“We’ve found that business-savvy technologists with creative mindsets are best positioned to effectively apply AI to business situations with the right guidance,” Vidoni says. “After a few projects, new people can quickly become self-sufficient and make a greater impact on the organization.”

Daryl Clark, CTO of Washington Trust, says the financial services company has moved away from degree requirements and focused on demonstrated competencies. He said they’ve had luck partnering with Year Up United, a nonprofit that offers job training for young people.

“We currently have seven full-time employees in our IT department who started with us at Year Up United interns,” Clark says. “One of them is now an assistant vice president of information assurance. It’s a proven pathway for early career talent to enter technology roles, gain mentorship, and grow into future high impact contributors.”

Coordinated AI integration

CIOs say in 2026 AI must move from experimentation and pilot projects to a unified approach that shows measurable results. Specifically, tech leaders say a comprehensive AI plan should integrate data, workflows, and governance rather than relying on scattered initiatives that are more likely to fail.

By 2026, 40% of organizations will miss AI goals, IDC’s Rajan claims. Why? “Implementation complexity, fragmented tools, and poor lifecycle integration,” he says, which is prompting CIOs to increase investment in unified platforms and workflows.

“We simply cannot afford more AI investments that operate in the dark,” says Flexera CIO Conal Gallagher. “Success with AI today depends on discipline, transparency, and the ability to connect every dollar spent to a business result.”

Trevor Schulze, CIO of Genesys, argues AI pilot programs weren’t wasted — as long as they provide lessons that can be applied going forward to drive business value.

“Those early efforts gave CIOs critical insight into what it takes to build the right foundations for the next phase of AI maturity. The organizations that rapidly apply those lessons will be best positioned to capture real ROI.”

Governance for rapidly expanding AI efforts

IDC’s Rajan says that by the end of the decade organizations will see lawsuits, fines, and CIO dismissals due to disruptions from inadequate AI controls. As a result, CIOs say, governance has become an urgent concern — not an afterthought.

“The biggest challenge I’m preparing for in 2026 is scaling AI enterprise-wide without losing control,” says Barracuda CIO Siroui Mushegian. “AI requests flood in from every department. Without proper governance, organizations risk conflicting data pipelines, inconsistent architectures, and compliance gaps that undermine the entire tech stack.”

To stay on top of the requests, Mushegian created an AI council that prioritizes projects, determines business value, and ensures compliance.

“The key is building governance that encourages experimentation rather than bottlenecking it,” she says. “CIOs need frameworks that give visibility and control as they scale, especially in industries like finance and healthcare where regulatory pressures are intensifying.”

Morgan Watts, vice president of IT and business systems at cloud-based VoIP company 8×8, says AI-generated code has accelerated productivity and freed up IT teams for other important tasks such as improving user experience. But those gains come with risks.

“Leading IT organizations are adapting existing guardrails around model usage, code review, security validation, and data integrity,” Watts says. “Scaling AI without governance invites cost overruns, trust issues, and technical debt, so embedding safeguards from the beginning is essential.”

Aligning people and culture

CIOs say one of their top challenges is aligning their organization’s people and culture with the rapid pace of change. Technology, always fast-moving, is now outpacing teams’ ability to keep up. AI in particular requires staff who work responsibly and securely.

Maria Cardow, CIO of cybersecurity company LevelBlue, says organizations often mistakenly believe technology can solve anything if they just choose the right tool. This leads to a lack of attention and investment in people.

“The key is building resilient systems and resilient people,” she says. “That means investing in continuous learning, integrating security early in every project, and fostering a culture that encourages diverse thinking.”

Rishi Kaushal, CIO of digital identity and data protection services company Entrust, says he’s preparing for 2026 with a focus on cultural readiness, continuous learning, and preparing people and the tech stack for rapid AI-driven changes.

“The CIO role has moved beyond managing applications and infrastructure,” Kaushal says. “It’s now about shaping the future. As AI reshapes enterprise ecosystems, accelerating adoption without alignment risks technical debt, skills gaps, and greater cyber vulnerabilities. Ultimately, the true measure of a modern CIO isn’t how quickly we deploy new applications or AI — it’s how effectively we prepare our people and businesses for what’s next.”

Balancing cost and agility

CIOs say 2026 will see an end to unchecked spending on AI projects, where cost discipline must go hand-in-hand with strategy and innovation.

“We’re focusing on practical applications of AI that augment our workforce and streamline operations,” says Pegasystems’ Vidoni. “Every technology investment must be aligned with business goals and financial discipline.”

When modernizing applications, Vidoni argues that teams need to stay outcome-focused, phasing in improvements that directly support their goals.

“This means application modernization and cloud cost-optimization initiatives are required to stay competitive and relevant,” he says. “The challenge is to modernize and become more agile without letting costs spiral. By empowering an organization to develop applications faster and more efficiently, we can accelerate modernization efforts, respond more quickly to the pace of tech change, and maintain control over cloud expenditures.”

Tech leaders also face challenges in driving efficiency through AI while vendors are increasing prices to cover their own investments in the technology, says Mark Troller, CIO of Tangoe.

“Balancing these competing expectations — to deliver more AI-driven value, absorb rising costs, and protect customer data — will be a defining challenge for CIOs in the year ahead,” Troller says. “Complicating matters further, many of my peers in our customer base are embracing AI internally but are understandably drawing the line that their data cannot be used in training models or automation to enhance third-party services and applications they use.”

Cybersecurity

Marc Rubbinaccio, vice president of information security at Secureframe, expects a dramatic shift in the sophistication of security attacks that looks nothing like current phishing attempts.

“In 2026, we’ll see AI-powered social engineering attacks that are indistinguishable from legitimate communications,” Rubbinaccio says. “With social engineering linked to almost every successful cyberattack, threat actors are already using AI to clone voices, copy writing styles, and generate deepfake videos of executives.”

Rubbinaccio says these attacks will require adaptive, behavior-based detection and identity verification along with simulations tailored to AI-driven threats.

In the most recent State of the CIO survey, about a third of respondents said they anticipated difficulty in finding cybersecurity talent who can address modern attacks.

“We feel it’s extremely important for our team to look at training and certifications that drill down into these areas,” says Altra’s Hamit. He suggests the certifications such as ISACA Advanced in AI Security Management (AAISM) and the upcoming ISACA Advanced in AI Risk (AAIR).

Managing workload and rising demands on CIOs

Pegasystems’s Vidoni says it’s an exciting time as AI prompts CIOs to solve problems in new ways. The role requires blending strategy, business savvy, and day-to-day operations. At the same time the pace of transformation can lead to increased workload and stress.

“My approach is simple: Focus on the highest-priority initiatives that will drive better outcomes through automation, scale, and end-user experience. By automating manual, repetitive tasks, we free up our teams to focus on higher-value, more engaging work,” he says. “Ultimately, the CIO of 2026 must be a business leader first and a technologist second. The challenge is leading organizations through a cultural and operational shift — using AI not just for efficiency, but to build a more agile, intelligent, and human-centric enterprise.”

Tech industry sentiment suggests that AI agents will automate entire business processes, potentially transforming companies worldwide.

Today’s reality is starkly different.

Fifty-eight percent of enterprise IT decision-makers say their organizations are piloting AI agents, with the majority targeting process automation, workflow efficiencies, or customer service, among other use cases, according to AI adoption research published by Wharton and the GBK Collective.

Again, these are pilots — not production implementations. There isn’t yet a playbook for fully baked human-AI agent workflows.

Still, as IT departments wrestle with the best path forward for using AI to automate operations, close partnership with human resources departments will be essential to minimize disruption and ensure the organization is primed to capitalize on the new roles, processes, and team structures that will arise as true human-AI coworking arrives.

Bringing AI agents into the fold

Tight interaction between IT and HR is crucial for the change management required for responsible AI deployment, says Sophos CIO Tony Young, who is spearheading the deployment of AI at the MDR vendor, including Microsoft Copilot. “The right approach is engaging with your HR pros and understanding how we bring the workforce along,” Young says.

For example, Young envisions more companies will employ automation experts, along with those who understand how to curate content and work with data to smooth the transition to agentic AI. HR can help blend the budding array of specialists.

Moreover, a little anthropomorphization can go a long way toward easing the transition to digital colleagues, Young adds.

The marketing organization at Sophos now includes AI agents in org charts as part of its teams, working alongside humans. New agents get new team member announcements — just like humans, says Young.

And Sophos’ IT service desk function now features a leaderboard that allows humans to see how they stack up against their digital coworkers. Human staffers monitor the AI agents to validate their work, consistent with human-in-the-loop best practices.

“Understanding how to use an LLM, or how to create an agent is like mastering Excel,” Young says. “That’s a new baseline skill that we all need to have.”

To get there, CIOs need to partner with HR leaders to help set the workforce AI training agenda, which could include emerging gen AI certifications as well as coursework for driving AI change.

What the agent-infused organization of the future will look like

What will fully agentic businesses look like in the future? Picture hundreds or thousands of autonomous “bots” working together to facilitate the execution of business processes end-to-end. These worker bots will likely be managed by a “boss” bot that ensures they stay on task.

If this sounds familiar it’s because it’s a symmetrical analogy for how humans have long performed knowledge work.

Yet organizations require a new operating model for working with agents. It will be incumbent on IT departments to stage and manage agent decision trees and the resulting workflows. These workflows will vary by function.

For instance, organizations that choose to automate call center operations with AI will need to train humans to monitor agents — a managerial and technical skill that goes beyond most call center associates’ current toolboxes.

“It requires a new skillset, including understanding the intent of calls and setting boundaries,” says Klemens Hjartar, senior partner at McKinsey. This requires new process management muscles for organizations accustomed to working a certain, human-centric way.

The introduction of AI agents to sales and marketing processes presents different challenges involving various workflows for CRM and other systems of engagement. The same can be said for operations teams and other functions likely to be impacted by agentic AI.

Whatever the workflow, HR can help soften the impact on teams through clear, consistent communication, as well as messaging around how IT and other departments can reskill their teams for the new era.

Microsoft predicted that IT and HR teams will forge new roles such as chief resource officers to help balance human and digital workers, while some organizations may install “agent bosses.” McKinsey envisions new roles for AI ethics and responsible usage, AI quality assurance leads, and agent coaches.

The hurdles are huge but not insurmountable

In short, wholesale changes to organizational dynamics are on the horizon, with IT and HR serving on the front lines of these transformations — mostly in tandem.

While these changes are a ways away, most organizations aren’t ready for it — but need to keep this future in mind as they plan their way forward.

One challenge is the fact that allocating too much decision-making authority to agentic AI architectures poses significant risks, due to technical challenges across disparate platforms and implicit knowledge gaps, says Amit Kinha, field CTO of FinOps platform provider DoiT.

For example, if you give a junior programmer some tasks to accomplish, they can turn to more experienced engineers when they need help. Today there isn’t a mechanism for AI agents to access the same tribal knowledge, Kinha says.

“Where is the source of truth coming from?” Kinha wonders. “Because if it’s not valid the whole decision tree will be invalid as well.” 

The ramifications of agentic actions loom large. A multi-agent system with the power to update across 15 systems could have significant impacts downstream that materially impact the bottom line, Kinha says.

One approach may include instituting checkpoints as part of organizational governance strategies. For instance, while some AI agents may be authorized to make individual decisions, others may have to seek approval from a human.

“The hardest part to master is decision autonomy,” Kinha says. Agents with too little autonomy will regularly check with humans, stunting automation. Those with too much will make mistakes that could be catastrophic. In addition to being explicit with goals and intents, organizations must make sure their data hygiene is sound, Kinha says.

The future looks bright(ish) — but unpredictable

When the technical and process challenges are reconciled, HR and IT partnership will be essential in assisting the transition from humans to human-plus-machine work. Every company introducing AI agents to their organizations must become more intentional about how they execute their business processes and measure outcomes.

“All of us in different functional domains need to up our game in intent-setting, boundary-setting, and measurement,” Hjartar says. “That’s going to take many years for us.”

Young says that every company will proceed at their own pace, which will create new categories of haves and have nots — just like preceding paradigm shifts involving emerging technology. “Some will push hard to automate; others won’t.”

What’s clear is that the challenges of human-machine commingling in the workplace are just beginning.