Nearly 1 in 5 Workers Replaced by AI Were Asked to Come Back, and Almost Half Want a Big Raise

For much of 2026, AI was the reason executives gave for cutting jobs. In May, employers cited it as the primary reason for almost 40% of announced job cuts, according to outplacement firm Challenger, Gray & Christmas. Now a growing number of those employers are picking up the phone to call the same people back. CNBC reported on October 30 that nearly 1 in 5 U.S. workers surveyed by talent assessment firm SHL said they had been laid off or replaced by AI and were later asked to return to their former employer.

The rehire call sounds like good news for the people who get it. For HR, it is evidence of an expensive sequence: a cut made on an assumption, a capability gap that surfaced after the people were gone, and a negotiation with former employees who now hold most of the leverage.

The Cut Came Before the Analysis

The SHL survey, fielded by Propeller Insights in June and July 2026 among more than 1,000 U.S. workers and more than 1,000 in the U.K., is the worker-side view. The employer-side view came earlier. Orgvue's research, based on 300 full-time U.S. HR managers surveyed with Watermelon Research in September 2025, found that 32% of organizations that cut jobs expecting AI cost savings have since rehired staff. Orgvue called it a fire-and-rehire cycle.

The same research explains how companies got there. 23% of layoffs tied to AI were based on general assumptions rather than detailed role analysis, and 42% of companies were still in early "testing" or "research" stages of using AI for workforce transformation. In other words, a meaningful share of employers removed roles to make room for a technology they had not yet finished evaluating. "That's not an AI problem; it's a workforce intelligence problem," said Jessica Modrall, Orgvue's chief product officer.

AI is also not always the real driver. In the Orgvue data, economic conditions (43%) and company restructuring (31%) accounted for 74% of workforce reductions, and 69% of HR leaders said AI is used to justify broader change initiatives. When AI becomes the headline reason for a cut that was really about cost or reorganization, the business case for the cut is rarely tested against what the technology can actually do.

The pattern is not new. An earlier Orgvue survey of 1,000 senior decision-makers, reported by HRreview in April 2025, found that 39% of leaders had made redundancies after introducing AI, and 55% of that group acknowledged mistakes in their redundancy choices. 30% said they did not know which roles were most at risk of automation, and 34% reported employee resignations directly linked to the introduction of AI.

Returning Workers Want It in Writing

The workers who get the call are not coming back on the old terms. Among U.S. respondents in the SHL survey, almost half would require a significant pay increase to return, 43% want written job-security guarantees, 40% want full transparency about AI's role in their job, and 30% say an apology or acknowledgment from leadership is a key condition. Only 6.6% would refuse to come back under any circumstances.

That combination tells HR where the real cost sits. Most former employees are willing to return, which means the employer can usually recover the capability it lost. But it recovers it at a higher price, with new contractual commitments, and with a trust deficit that the old employment relationship did not carry. "You've really broken the trust with those people," Lucy Beaumont, SHL's global senior vice president of product and design, told CNBC. The question returning workers ask, in her words, is "How do I know that this isn't going to happen again?"

Beaumont's broader point is that companies "pulled the plug too quickly" on people who know the business and its customers. Joseph Fuller, a professor of management practice at Harvard Business School, made a similar argument, tying AI's value to the "contextual intelligence" employees bring. Coverage from People Matters notes that experts now describe the pattern as "AI rebounding," and both reports cite Ford and Amazon among the large employers that have reversed AI-related layoffs.

The Workers Are Retooling Either Way

The SHL data also shows what the displaced are doing while employers reconsider. 44% of U.S. respondents are teaching themselves AI tools, 42.6% are building industry-specific skills that AI cannot easily replicate, 40% are working on interpersonal and leadership skills, and 38% are developing creative and strategic thinking. The people an employer cut may come back more capable than when they left, and more aware of their market value.

That raises the stakes on how the next round of AI decisions gets made. Fuller predicts AI will create "permanent tumult" inside many organizations. If role changes are going to keep coming, the companies that avoid a second fire-and-rehire cycle will be the ones that do the role analysis first and treat the people closest to the work as part of the evidence.

• Require role-level analysis before any AI-justified cut. 23% of AI-linked layoffs rested on general assumptions. Document which tasks the technology performs today, which it does not, and who currently carries the knowledge that makes those tasks work.
• Separate the AI case from the cost case. With 69% of HR leaders saying AI is used to justify broader change, ask leaders to state plainly whether a reduction is driven by economics, restructuring, or proven automation, and test each claim on its own terms.
• Pilot before you remove the people. 42% of companies were still testing or researching AI for workforce transformation. Run the tool alongside the team until output quality is proven, rather than cutting first and discovering the gap later.
• Budget for the rehire scenario. Almost half of workers asked back want a significant raise. Model the cost of reacquiring critical skills at a premium before approving cuts in roles that are hard to replace.
• Make returning offers credible. 43% want written job security and 40% want transparency about AI's role. Put both in the offer, and have leadership acknowledge the earlier decision, which 30% call a key condition.
• Keep alumni relationships warm. Departed employees are actively building AI and industry skills. Exit conversations, alumni networks, and accurate records make a later return faster and less adversarial.

The AI rehire is a correction, not a scandal. But each correction costs more than the decision it reverses. HR's job in the next round of AI-driven change is to make sure the analysis happens before the layoff, not in the call asking someone to come back.