55% of Companies That Slashed Jobs for AI Now Regret It After Restaffing Costs Soar

The corporate rush to swap staff for artificial intelligence is quietly going into reverse, and the retreat is proving expensive.

More than half of the employers who cut jobs on the promise of AI now regret it. Forrester's Predictions 2026 report put the figure at 55%, matched almost exactly by the workforce analytics firm Orgvue. The explanation is consistent across the research: the technology absorbed the routine work but stumbled on the judgement, nuance, and institutional knowledge that made those roles worth paying for.

What began as a cost-cutting story has become a rehiring one. A February 2026 survey by the outplacement firm Careerminds, which polled 600 HR leaders who oversaw layoffs in the previous year, found two in three companies making AI-driven cuts were already bringing staff back. More than a third had rehired over half the roles they eliminated, and 52% did so within six months.

The 55% figure has since ricocheted across social feeds, where the trend has earned a nickname: the AI boomerang. The cuts behind it were real: Challenger, Gray & Christmas attributed about 55,000 job losses to AI in 2025, some 4.5% of all US layoffs.

Why Restaffing Is Costing More Than the AI Layoffs Ever Saved

The savings that justified the cuts have largely failed to show up. Careerminds found that nearly a third of organisations, 30.9%, spent more on rehiring than they had saved by automating, leaving them worse off than if they had never made the redundancies at all.

A further 42.4% said the savings and the restaffing costs roughly cancelled each other out. Only about a quarter finished ahead.

Orgvue's arithmetic is blunter still. Once severance, lost productivity, and the cost of recruiting replacements are tallied, the firm estimates companies spend about $1.27 (95p) for every $1 (75p) they claw back through workforce reductions.

Commonwealth Bank of Australia supplied a textbook case. In July 2025, the lender cut 45 customer service roles, crediting an AI 'voice-bot' with reducing call volumes. Weeks later it backtracked, conceding its assessment 'did not adequately consider all relevant business considerations and this error meant the roles were not redundant.'

Call volumes had in fact been climbing, and team leaders were pulled onto the phones to cope. The reversal came the same year the bank booked a record A$10.25B (about $6.8B, £5B) cash profit.

The Swedish fintech Klarna became the movement's cautionary tale. It had cut its workforce from around 5,500 to roughly 3,400 and boasted that its OpenAI-powered assistant did the work of 700 agents. Then satisfaction slipped.

Chief executive Sebastian Siemiatkowski told Bloomberg the all-AI approach had produced 'lower quality' service, and said it was vital that customers know 'there will always be a human if you want.' The firm started recruiting people again.

The Rehiring Wave Is No Clean Win for Workers

Not every viral example survives scrutiny. IBM has been widely cited as a firm that sacked thousands of HR staff for AI, then rehired them all, yet the record is more prosaic.

Chief executive Arvind Krishna told The Wall Street Journal that its AskHR assistant, which automates about 94% of routine HR tasks, replaced only 'a couple hundred' roles, and that total headcount actually rose as savings shifted into engineering, sales, and marketing. 'Our total employment has actually gone up,' he said.

For anyone reading this as a return to secure work, the picture is mixed. Gartner expects half of the companies that trimmed customer service headcount for AI to rehire for similar functions by 2027.

Forrester predicts half of all AI-attributed layoffs will be reversed in some form by the end of 2026. Robert Half already counts 32% of US hiring managers who axed a role for AI as having refilled it.

The terms are not always the same. Forrester notes that many of these jobs return offshore or at noticeably lower pay, which means the correction can fall on the worker rather than the employer who ordered the cut.

The thread running through the numbers is not that AI failed outright, but that it was cast as a replacement when it worked best as a support. The firms now quietly restaffing have not turned against the technology. They are relearning, at a price, the parts of the job it could not do.