New research suggests some companies are inviting employees back after AI-related job cuts, challenging assumptions about automation savings and the value of human expertise.
Companies that eliminated positions while introducing artificial intelligence are increasingly confronting an unexpected problem: some of the employees they replaced are being asked to return.
A new SHL workforce survey, published October 29, found that 19% of US respondents and 13% of UK respondents said they had personally experienced being replaced by AI and subsequently invited back by the same employer.
The research, conducted by Propeller Insights in June and July 2026, surveyed 2,036 employed adults across the United States and United Kingdom.
The findings highlight an emerging concern for technology companies and employers: automating individual tasks does not necessarily eliminate the broader responsibilities and expertise associated with a job.
Workers Are Being Asked to Return
SHL describes the phenomenon as AI rebounding, referring to situations where employees lose positions associated with AI adoption before employers reconsider those staffing decisions.
The company found that approximately 24% of surveyed workers aged 18–24 reported personally experiencing such a reversal.
However, these figures represent respondents’ reported experiences, not independently verified employment records. Being invited back also does not establish that an individual accepted the offer or resumed employment.
According to Associated Press reporting, staffing company Robert Half identified employers in finance, marketing, law and healthcare that eliminated positions associated with AI or automation before recruiting workers for similar responsibilities.
Bill Driscoll, senior district president at Robert Half, emphasized the importance of critical thinking, collaboration, creativity and institutional knowledge—capabilities employers may underestimate when evaluating automation.
Rehired Employees Want Different Conditions
The SHL findings also indicate that employees are reconsidering what they expect from organizations adopting AI.
Among respondents considering a return after AI-related displacement, 51% wanted substantially higher compensation, 42% sought explicit employment-security guarantees and 40% wanted transparency about future AI use in their roles.
Another 47% of surveyed workers said they would prefer retraining for a different position rather than losing their job if AI changed their responsibilities.
Lucy Beaumont, SHL’s global senior vice president of product and design, argued that some organizations make workforce decisions without understanding employees’ full capabilities.
The implications extend beyond compensation. Workers asked to return may question whether their employer can provide stable career opportunities as automation expands.
Gartner Warns of Higher Rehiring Costs
The survey follows an October 28 Gartner forecast predicting that 30% of employees terminated and replaced by AI will be rehired by 2029, frequently at greater cost.
The estimate is a forecast, not a measurement of layoffs already reversed.
Gartner vice president analyst Caitlyn McDonough warned that organizations may determine headcount reductions before adequately understanding future work requirements.
A July Gartner survey of 297 chief human resources officers found that only 19% of organizations had workforce-planning practices effectively accounting for changing work, AI’s impact and business strategy.
Automation Needs a Better Business Case
For technology founders and executives, the emerging concern is not whether AI can automate tasks, but whether businesses accurately evaluate the consequences.
An automated customer-service system may resolve routine inquiries while still depending on experienced employees for unusual problems, customer relationships and quality control.
Replacing workers before identifying those dependencies may create additional recruitment costs and operational risks.
The broader lesson is that successful AI adoption depends on understanding human work before deciding how much of it technology should replace.
