The labor market seems to be going through a quiet re-valuation of people. Every week brings news of layoffs, and almost every press release points to AI as the reason. The obvious conclusion follows: if machines are taking on more of the work, people have gotten cheaper — so investing in their health, resilience, and development isn't quite as necessary anymore.
But the 2026 data says the opposite — and it's given the reversal a name: AI boomerang hiring. Companies cut headcount citing AI, then quietly hire people back into the same roles once the gap becomes obvious. It turns out AI takes the tasks, not the people — and the entire load now rests on whoever is left.
In short: more than half of employers now regret their AI-driven layoffs. A third have already rehired people back. And the companies that avoided the boomerang aren't the ones that cut the least — they're the ones that never stopped investing in the health and resilience of the people they kept.
On this wave of re-valuation, it's as if everyone rushed in the same direction, racing each other — and in the hurry, forgot a simple thing: experienced people were, and still are, a company's most valuable resource. Not the cheapest — the most valuable.
Let's start with what's pointless to deny: the layoffs are real, and there are a lot of them. In May 2026, U.S. employers announced 97,006 job cuts, and for the third month running AI was named the leading cause — 38,579 of those cuts were attributed directly to it, a record since Challenger, Gray & Christmas began tracking this data in 2023.
Expectations from top management are no more modest: in a Korn Ferry survey of 250 CEOs and board directors, 82% said they plan to cut up to 20% of headcount within three years specifically because of AI.
On paper, the picture looks clear-cut: people are becoming a line item marked "exit."
And then things started happening that don't fit that picture.
Forrester's Predictions 2026: The Future of Work report found that 55% of employers already regret their AI-driven layoffs. Analysts forecast that roughly half of those cuts will be walked back — though usually via offshoring or lower salaries. Meanwhile, 57% of executives making AI decisions expect headcount to grow, not shrink.
Robert Half surveyed around 2,000 U.S. hiring managers: 32% admitted they'd eliminated a role because of AI, then hired a person back into the same or a similar position — what Robert Half's own researchers now call the "AI boomerang." The split by sector is wide: 44% of companies in finance did this, 35% in HR, 32% in tech.
Gartner goes further, predicting that by 2027 about half of the companies that cut people "for AI" will be rehiring for similar functions — just under different job titles.
There's a price tag on this mistake, and it's especially visible to a CFO: among those who regretted the decision, 35.6% rehired more than half of the people they'd let go, and one in three companies ended up spending more on restaffing than they originally saved on the cuts.
The reason turns out to be fairly simple: companies laid people off based on AI capabilities that didn't actually exist yet. As Forrester's analysts put it, "too often, the C-suite lays workers off for the future promise of AI." In the headlines it looked like "layoffs due to AI" — in reality, it was a bet that the technology was about to close the gap on that job. The bet didn't pay off.
The mistake wasn't that companies believed in AI. The mistake was in who, exactly, they decided was replaceable.
A few telling stories:
All these stories share the same side effect: when companies cut "redundant" expertise instead of routine work, they create a key person risk — a smaller and smaller group of people whose departure would stop the process cold. Knowledge that used to be spread across several people now lives in one person's head (what engineers call the "bus factor" shrinking toward 1) — and that's no longer a matter of convenience, it's a matter of the whole business's stability. Mercer Marsh Benefits' own research on people risk names key person risk one of the top issues now raised directly by the C-suite.
The more routine work moves to machines, the more the real value concentrates in people — in their judgment, their client relationships, their quality control, and their oversight of the AI itself.
Here's where the math flips. Companies are getting "leaner" in headcount, but more dependent on whoever remains. A smaller group of people now carries more workload, more responsibility — and more of the emotional weight specialists call survivor guilt: the guilt and anxiety of those who made it through a wave of layoffs around them.
And this lands on top of a backdrop that's already stressful on its own: the pace of change keeps accelerating, and with it the load on each individual person — new tools, processes, and expectations keep arriving faster than teams can absorb them. The uncertainty in this environment — who gets cut next, what task AI will take over next quarter — raises anxiety on its own, and anxiety reliably eats into productivity. That very sense of stability and care that companies spent years building — and which, as we know, delivers a real productivity boost — is being lost far faster than it was built.
This is no longer an abstract HR metric — it's an operational risk. Wellhub's international Return on Wellbeing 2026 report — surveying more than 1,500 HR and benefits leaders across 10 countries — found that 88% name retaining top performers a priority specifically because of AI adaptation.
And that retention costs money — but it pays off. Deloitte's research on mental wellness ROI puts the average return at around $5 for every $1 invested in employee mental health programs. McKinsey's Health Institute finds that employees facing mental-health and wellbeing challenges are four times more likely to want to leave their organization. The Global Wellness Institute reports up to 20–25% higher productivity at companies that integrate wellbeing into leadership and performance management. And Mercer's ongoing research on employee health frames mental health decline as one of the top people risks businesses face today — with the World Health Organization estimating depression and anxiety alone cost the global economy roughly $1 trillion a year in lost productivity.
The swing back doesn't cancel out the cuts themselves — both processes are happening in parallel: some companies are still cutting headcount while others are, at the same time, correcting their own hasty decisions. It's also worth adding that not everything publicly labeled a "layoff because of AI" actually was one: some of those cuts were plain cost optimization wearing a convenient label — a pattern researchers have started calling "AI washing."
But it's precisely in this uncertainty — where it's unclear what can genuinely be trusted to a machine and what can't — that the resilience and health of the people who remain becomes what separates companies that manage this well from those that over-cut and then pay dearly to clean up the mess.
The labor market has clearly entered another cycle of restructuring — this has happened before, with automation, with the shift to remote work, with every prior wave of technology that promised to replace people. And every time the dust settles, the company that ends up ahead isn't the one that cut headcount most aggressively — it's the one that understood, earlier than everyone else, the real value of every key node in the chain — people, processes, expertise — and didn't mistake optimization for amputation.
Meanwhile, the changes aren't going anywhere, and there's no undoing them: whoever ignores them and clings to the old headcount model at any cost risks falling just as far behind as those who cut blindly. But the real winners won't be the fastest or the most radical — they'll be the ones who carry these changes out wisely.
Companies decided that since AI was taking over the work, people had gotten cheaper — and their health was a place to cut costs. It turned out to be the opposite: AI takes the tasks, not the people, and everything now rests on whoever is left. There are fewer of them, and everything depends on them more. Caring about people has stopped being simply kindness — it's become a calculation. And cutting corners on the health of the people everything now depends on is the most expensive kind of saving there is.
Most cut roles based on AI capabilities that weren't production-ready yet. When the technology couldn't fully cover the work, companies quietly hired people back — often into similar roles, sometimes under different titles or at lower cost (offshore, lower salary).
It's the term researchers and outlets like Robert Half now use for the pattern of laying off staff citing AI, then rehiring for the same or a similar position once the AI-driven plan falls short in practice.
Key person risk is the exposure a business has when critical knowledge, relationships, or judgment sit with very few people. When companies cut experienced staff instead of routine tasks, that concentration deepens — the departure of one or two people can now stop a process cold.
Yes — multiple independent studies (Deloitte, Wellhub, McKinsey, Global Wellness Institute) put the return on employee wellbeing programs at several times the amount invested, largely through lower turnover, fewer sick days, and higher productivity among the people companies depend on most.
If the key people at your company are now your key asset, their physical and mental health deserves to be treated accordingly — not as a line item, but as an asset to be managed. That's exactly what we're building WLLNSS for: a single AI-powered health and wellbeing platform that brings diagnostics, telemedicine, mental health support, and long-term programs together into one system for the whole company, in any country. See what health-related productivity loss is costing your company →
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