Mass layoffs have lost their novelty in 2025, with major enterprises announcing sweeping job cuts on a rolling basis throughout the year. Companies across different sectors have been affected: Target terminated 1,800 corporate roles in October, while UPS has now eliminated a total of 48,000 positions this year alone. But there’s a new trend shaping a lot of these employment cuts, one that is keeping CIOs on their toes: Consistently, it’s AI that is named as the reason behind job elimination.
In a memo to staff, Amazon referred to the 14,000 layoffs it announced this week as part of “shifting resources to ensure we’re investing in our biggest bets.” Later, it referenced AI as “the most transformative technology we’ve seen since the Internet.” At Salesforce, the company attributed its recent layoffs of 4,000 employees in part to the benefits of AI. Even finance has joined in, with Goldman Sachs sharing its plans to reduce human roles where AI replacements were feasible.
For CIOs, these layoff announcements are an unavoidable signpost that AI is going to shape employment strategy for the foreseeable future — and it’s the CIO’s responsibility to forge that path. But is this a warning, an opportunity, or even a PR spin?
How Responsible Is AI for Layoffs?
While AI may be referenced as a consistent contributor to recent layoffs, not all experts are convinced that this is the honest truth.
“Most claims that AI use is leading to layoffs are largely overstated, given the current maturation of that technology within enterprises,” said David Linthicum, a cloud and AI subject-matter expert and former chief cloud strategy officer at Deloitte Consulting. “While there have been some productivity gains, it’s not to the point where the ability to lay off employees is at the level we’re seeing.”
Rather than being a direct result of AI automation, Linthicum said he views the layoffs as both a correction of previous over-hiring in the post-pandemic period and a reaction to the slowing of sales. The reference to AI might instead be a way to put an optimistic spin on the news: While layoffs might be a necessary loss, they’re also paving the way for better performance. Lisa Palmer, CEO and chief AI strategist at Dr. Lisa AI, describes this phenomenon as “AI washing.”
“Companies claiming that they have gained so much productivity from AI use that they are laying off unnecessary staff — in most cases, that’s PR spin,” she said.
Ramesh Dontha, an AI expert, author, entrepreneur, and thought leader, agreed that attributing job cuts to AI isn’t the full picture — especially when it comes to IT teams. He described AI as redefining, rather than replacing, IT. In every major layoff wave citing AI, the trend isn’t that tech teams are being gutted, he said; it’s that IT is becoming more strategic and less operational.
“The real shift is from maintenance to model management — from fixing systems to training them,” Dontha said.
While AI’s responsibility is debatable, there are two things everyone agrees on: AI is the primary area of focus going forward, and it will change what jobs look like.
Leading IT Teams in the AI Era
For CIOs, the public emphasis on AI is a double-edged sword. While it may seem like the IT department has been elevated in terms of company value, it is not impervious to staffing changes or even job cuts.
“Many assume IT is protected because it’s the implementer of AI — it’s not,” said Wendy Turner-Williams, founder and executive managing director of TheAssociation-AI.org, and strategic advisor for data and AI at the University of Maryland Global Campus. “The same automation that IT deploys across the business is being aimed right back at its own operations: incident response, QA, service tickets, documentation, even coding.”
Turner-Williams and Dontha both spoke of the vulnerability of IT teams to automation if they aren’t purposefully redirected toward new ways of working. Linthicum was more optimistic about IT teams’ security, arguing that they’ll be needed to achieve the lofty AI goals that companies are articulating. However, this protected class status may be only temporary until the AI solutions have been developed and launched.
CIOs may be tempted to try and protect their teams from future layoffs — and this is a noble goal — but Dontha and others warn that this focus is the wrong approach to the biggest question of working in the AI age.
“Protecting people from AI isn’t the answer; preparing them for AI is,” Dontha said. “The CIO’s job is to redeploy human talent toward high-value work, not preserve yesterday’s org chart.”
For Palmer, it is imperative that CIOs not get distracted by preserving the status quo. While it may be tempting to dig in their heels and take the safest route through the AI quagmire, this will not reap the rewards they need to actually AI-proof their organization. She said she sees employees at every level, from frontline to C-suite, as at risk if they don’t actively adapt, upskill, and move fast.
“Many CIOs have created AI policies, built AI governance teams, even launched pilots,” Palmer said. “This is all extremely low-risk, necessary work. It’s also a long way from creating value for their businesses. That is what puts leaders and their teams at risk of downsizing or replacement.”
CIOs Under Greater AI Pressure
When a company describes its layoffs as part of a redistribution of resources into AI, it shines a spotlight on its future AI performance. CIOs were already feeling the pressure to find productivity gains and cost savings through AI tools, but the stakes are now higher — and very public.
“When AI is cited as the reason for layoffs, the CIO inherits the clock,” Turner-Williams said. “Boards and CEOs will expect visible ROI, and fast.”
Unsurprisingly, this pressure often leads to unproductive outcomes. According to Turner-Williams, it is common for pressure to drive a surge in proofs of concept that focus narrowly on cost takeout, rather than sustainable value creation. “But rushing ROI rarely builds it,” she added.
It’s not just CIOs at the companies affected that may be feeling this pressure. Several industry experts described these layoffs as signposts for other organizations: That AI strategy needs an overhaul, and that there is a new operational model to test, with fewer layers, faster cycles, and more automation in the middle. While they could be interpreted as warning signs, Turner-Williams stressed that this isn’t a time to panic.
Instead, CIOs should use this as an opportunity to get proactive. She acknowledged that when hyper-scalers restructure, midmarket and enterprise CIOs often feel pressured to follow suit, to prove greater efficiency to the board.
“But imitation isn’t transformation,” she warned. “The smarter response is to pause, not panic. Don’t copy the symptom, study the signal. AI doesn’t eliminate jobs; bad AI strategy does.”
After Layoffs, Now What?
There is no one-size-fits-all approach to AI strategy, but industry experts are notably split on what action should look like in response to a mass layoff, whether it occurs internally or at an industry counterpart.
Dontha spoke of several ways that CIOs can earn some goodwill from the rest of the executive team through early AI wins. Some boards will expect results in 90-180 days, whether that looks like faster deployments, tangible cost savings, or shorter incident response times. For IT leaders facing those demands, he recommended copilot-assisted service desks to cut resolution time by 25% to 30%; AI code assistants to boost developer throughput by 15% to 20%; and cloud FinOps AI to reduce inference costs by up to 40%.
Palmer was less prescriptive but still adamant about the need to take action. “Too many leaders are protecting their titles instead of protecting their companies, paralyzed by the fear of doing something risky rather than the consequences of doing nothing,” she said. “[But] competitors aren’t waiting.”
She advocated for clear, thoughtful action that’s led by courage, rather than fear. Rather than focusing on the potential fallout of an ineffective AI push, she argued that inaction is the biggest risk of all.
On the opposite side, Linthicum advised leaders to resist the push to find quick wins. He observed that, for all the expectations and excitement around AI’s impact, ROI is still quite elusive when it comes to AI projects. To actually see success, CIOs will indeed need to dedicate more resources to their AI programs, but he said he believes the sense of urgency created by these layoffs is “largely misplaced.”
“I would focus on their own needs and move to AI, or any other technology, when it makes sense for them,” he said. “Don’t follow the crowd.”
Suggesting a strategy somewhat in between these two stances, Turner-Williams said she believes successful CIOs will be the ones who can work along two separate timelines: the AI initiatives that will have measurable impact in 90 days, and the ones that will transform operations over 18 months. She agreed with Dontha’s short-term solutions, saying that those early gains will come from improved operation efficiency, but she added the importance of pursuing a bolder reinvention strategy alongside.
Ultimately, Turner-Williams said, “AI isn’t just a technology investment — it’s a leadership stress test.”
