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Companies rushed to cut jobs in the name of “AI efficiency” and now many of those same firms are sheepishly begging former employees to come back. The new SHL survey makes a blunt point: rush to automate, and you may end up paying twice for the same skill. Call it “AI rebounding” — and call it avoidable.
SHL survey: the AI rebounding story
The SHL report found that about 16 percent of surveyed workers said they were laid off or replaced by AI and later asked to return, with roughly 19 percent of U.S. respondents reporting that experience. That is not a tiny glitch; it is a pattern. Lucy Beaumont, Global Senior Vice President of Product and Design at SHL, bluntly says many employers “pulled the plug too quickly.” Workers are not dreamy abstractions — they are the institutional memory and judgment that most AI systems simply cannot copy.
Numbers, examples, and the messy reality
Other studies back the pattern. Orgvue reported that 32 percent of organizations that cut roles citing AI later had to rehire. Robert Half’s research shows a similar “boomerang” from the employer side. The most obvious corporate faceplant came from Ford, which rehired hundreds of veteran engineers after automated systems failed to match human judgment. So yes, the cost-cutting math looked pretty on a spreadsheet until reality and quality control walked back in the door.
Why companies are paying twice (and losing trust)
The logic behind the layoffs is familiar: spend on new tech, find savings by cutting payroll. Joseph Fuller, Professor of Management Practice at Harvard Business School, explains that this budgeting mindset has happened before with new tech rollouts — and it can backfire. Employers often pay severance, then pay again to rehire at higher pay, or pay contractors to patch problems. Worse, they break trust. SHL data shows returning workers want big raises, written guarantees, and full transparency about how AI will be used — because why would anyone trust a boss who fired them for a robot and then wanted them back?
What should employers do next?
Simple: stop treating AI as a magic replacement and start treating it like a tool that needs human pilots. Test systems on real workflows, map tacit knowledge, and retain the people who know the ropes. If companies refuse to learn this lesson, they will keep cycling through layoffs, rehiring, and higher costs — all while losing credibility with the workforce. That is not innovation. It is sloppy bookkeeping with an ethics problem attached.
