Companies that laid off technology workers to replace them with AI are now trying to rehire those same employees, according to an analysis published by InformationWeek. The effort faces a major obstacle: workers who lost their jobs don't trust the employers who let them go. The analysis draws on industry data and interviews with human resources executives and recruitment specialists to examine whether companies can successfully rebuild teams after mass layoffs.
More than 122,000 technology workers lost their jobs in 2025, with another 126,000 laid off in 2026, according to Layoffs.fyi data cited in the report. Many of these professionals have spent months searching for new positions in a difficult hiring environment. The report notes that AI eliminated opportunities across the entire industry, not just at individual companies, leaving openings that were once abundant now scarce.
Rehiring former employees typically costs one and a half to two times the salary a company "saved" through layoffs, according to Lee McCabe, founder of private equity growth-execution firm Claymore Partners. Bringing on entirely new workers to replace institutional knowledge costs roughly one to two times the former employee's annual salary before the new hire reaches full productivity, the report finds, citing Ali Gohar, chief human resources officer at Software Finder. Senior and specialized roles take three to six months to fill, and many companies have eliminated their junior talent pipeline, leaving no one available to step into midlevel positions.
The analysis explains that broken trust represents the toughest barrier to overcome, affecting not only laid-off workers but also those who remained employed. When leadership publicly positioned AI as a substitute for human expertise, professionals who watched colleagues lose their jobs naturally question whether their own positions will survive the next wave of automation, the report notes—a problem that compensation alone can't solve. Companies get labor but not loyalty from employees who return out of necessity, while the workers they most want back are those who left and continued advancing their careers, who won't forget how they were treated. Successful rehires tend to happen when leadership acknowledges mistakes and offers a clearly improved role in an environment that has undergone meaningful change, according to the report. Without these elements, most former employees become very difficult recruiting prospects.
The report concludes that companies must stop announcing head count reductions as strategy and instead redeploy people onto the processes that AI actually changes. Rehired workers don't simply resume old duties—they must also be proficient in using AI tools and performing their previous job differently, which requires pitching the opportunity as "come back and fix what we broke" with real authority attached, or the trust gap won't close. The report suggests that using AI to rehire workers whose jobs were threatened by that same technology risks reputational damage when AI appears to make important hiring decisions without meaningful human oversight, though candidates are generally comfortable with technology supporting administrative tasks if it's transparent and fair. The lesson for employers is clear: institutional knowledge and team cohesiveness can't be replaced by automation, and rebuilding what was lost costs far more than what was saved. Organizations that announced layoffs as an AI efficiency play may discover that the real cost shows up when they need to compete for talent they once discarded, facing candidates who now know exactly what corporate loyalty is worth in practice.