AI News Digest, May 27: What the 99% AI-Driven Layoffs Forecast Actually Means

One number is everywhere this week. 99% of CEOs expect AI to drive layoffs within two years. The figure comes from Mercer’s research, and it has spread across tech headlines over the last few days. But the AI-driven layoffs forecast is being read wrong. The real finding is narrower than the headline, and the rest of the data tells a far more useful story for anyone who runs a team. So before you forward that stat to your board, here is what it actually says, why the cuts may not pay off, and what to do on Monday.

What the AI-Driven Layoffs Forecast Actually Says

The stat traces back to Mercer’s Global Talent Trends 2026 report, a survey of nearly 12,000 executives, HR leaders, investors, and employees worldwide. Among the C-suite leaders polled, 99% expect AI to lead to at least some headcount reduction over the next two years. (Source: Futurism)

Read that line again. It says “at least some” reduction, not “mass layoffs.” A leader who plans to cut two roles and a leader who plans to cut two thousand both land inside that 99%. The headline flattens a wide range into one scary number.

The same survey found that 98% of executives are planning major organizational design changes around AI. Meanwhile, 65% expect 11% to 30% of their workforce to be redeployed or reskilled, not removed. (Source: Mercer) So the dominant plan is to restructure work, not to empty the building. That distinction changes how you should brief your team.

One more thing the coverage skips: the underlying survey ran in late 2025, and the report first published in February. The forecast resurfaced this week, but it is not breaking news. The panic is new. The data is not.

Why the AI-Driven Layoffs Forecast Won’t Deliver ROI on Its Own

Here is the part the headlines bury. Cutting jobs to fund AI mostly does not work. Gartner surveyed 350 global executives at companies with at least $1 billion in revenue, all of them already deploying AI agents or automation. About 80% reported workforce reductions. Yet those cuts showed almost no link to stronger returns. (Source: Fortune on Gartner)

“Workforce reductions may create budget room, but they do not create return,” said Helen Poitevin, a Distinguished VP Analyst at Gartner. The firms that did see ROI were the ones that invested more in skills, roles, and operating models, so people could guide and scale AI systems instead of being swapped out by them.

Now put the two studies side by side. The AI-driven layoffs forecast says nearly every leader expects cuts. The ROI data says cuts alone are a dead end. Picture a 200-person company that sheds 30 roles to free up budget for an agent rollout. If nobody owns the redesign, the work those 30 people did does not vanish. Instead, it scatters across the survivors, output dips, and the savings get spent rehiring a year later. You pay twice: once in severance, then again when the AI underdelivers.

Under the Hood: The Numbers Most Coverage Ignored

The Mercer data carries a second story, and it is about people, not models.

Wellbeing is cratering

Only 44% of employees said they were thriving at work in 2026, down from 66% in 2024. Over the same stretch, worry about losing a job to AI climbed from 28% to 40%. (Source: Mercer) That is a 22-point morale drop during the exact window when companies need focus and output the most. Early-career staff feel it hardest, because entry-level tasks are usually the first ones automated.

Leaders and HR are not aligned

62% of employees believe leaders underestimate AI’s emotional impact. Yet only 19% of HR leaders fold that impact into their digital rollout plans. Confidence is slipping at the top, too. Just 51% of the C-suite feel prepared for the human-machine era, down from 65% in 2024. And 63% of employees say they would trade a 10% raise for the chance to upskill in AI. The appetite to adapt is clearly there. The support around it is not, and that gap is where good people quietly start to leave.

Investors are watching the human side

This is not just an HR concern. In the same survey, 72% of investors agreed that companies combining human and AI capabilities gain a competitive edge. Another 77% said they are more likely to back firms that invest in AI education and training. In short, the money is rewarding teams that grow their people, not the ones racing to shrink them.

What HR Leaders Do Monday

You do not need a transformation office to act on this. Instead, start small and concrete.

First, separate “reduction” from “redesign” in your own plan. Map which roles change, which tasks get automated, and which people you move instead of cut. Use the 65% redeployment figure as your benchmark, not the 99% layoff line. The framing you choose sets the tone everyone else hears.

Second, fund the skills side now. Gartner’s ROI gap and Mercer’s upskilling appetite point in the same direction. A reskilling budget beats a severance budget almost every time. If you are not sure where your gaps sit, our breakdown of the AI skills gap in HR is a useful place to start.

Third, build the human-machine operating model on purpose. 82% of the C-suite expect HR to manage people and digital agents side by side. But AI agents for HR workflows only pay off when someone actually owns the handoffs between human and system. So assign that owner before you scale, not after.

Fourth, measure morale the way you measure adoption. If thriving fell 22 points while AI spend rose, your dashboard is tracking the wrong number. Add a wellbeing pulse next to your tool-usage metrics, then read them together.

The AI-driven layoffs forecast is a stress test for how you lead, not a script to follow. The companies that treat AI as a way to amplify people, rather than just trim them, are the ones the same research rewards. If you are rethinking how AI fits your stack, Asanify’s work on AI in human resource management covers the practical side, from hiring to payroll.

Frequently Asked Questions

Do 99% of CEOs really plan layoffs because of AI?

Not exactly. Mercer’s survey found that 99% of C-suite leaders expect AI to cause at least some headcount reduction over two years, which can mean a few roles or many. The same report shows 65% expect to redeploy or reskill 11% to 30% of staff, so restructuring, not mass layoffs, is the more common plan.

Do AI-driven layoffs improve a company’s returns?

Usually not on their own. Gartner found that about 80% of firms deploying AI cut staff, but those cuts had little link to better ROI. The companies that gained instead invested in skills and new roles so people could guide AI, rather than simply reducing headcount.

What should HR leaders do about the AI-driven layoffs forecast?

Treat it as a planning prompt, not a mandate to cut. Separate role redesign from reduction, fund reskilling before severance, decide who owns the human-and-agent handoffs, and track employee wellbeing alongside AI adoption. Mercer’s data ties both morale and ROI directly to that human-centered approach.

Not to be considered as tax, legal, financial or HR advice. Regulations change over time so please consult a lawyer, accountant  or Labour Law  expert for specific guidance.