AI-related layoffs have captured everyone’s attention lately. Last month, Meta laid off 10% of its workforce—just months after committing up to $135 billion toward AI development this year.
Other companies, such as Cloudflare, Coinbase, and PayPal, have also laid off or plan to lay off employees as they become “AI native.”
Last year, a report from Forrester Research highlighted that 55% of employers regretted their decision to lay off staff due to artificial intelligence. And a Gartner prediction published earlier this year claims that 50% of all companies that replaced customer service or operational employees with AI will be forced to restaff those roles under different titles by next year.
A trend called the “AI boomerang” effect is emerging: Companies that laid off employees due to AI or automation are now rehiring for those roles for a number of reasons.
According to new research from the consulting firm Robert Half that was reviewed by Fast Company, nearly a third (32%) of hiring managers say that their organizations eliminated a role or let someone go primarily due to productivity gains from AI or automation, only later to rehire for that exact role.
“Companies that moved too quickly on AI are now seeing where it falls short in practice,” says Megan Slabinski, district president of technology talent solutions at Robert Half. “While they may have seen early efficiency gains, those efforts also surfaced gaps in quality, oversight, and decision-making, especially as business demands picked up.”
“In many cases, organizations have had to reassess their expectations, recognizing that while AI can be effective in certain areas, it’s not the end-all-be-all solution some initially believed it would be,” Slabinski adds. “That’s prompting leaders to consider the shift from cutting roles to rethinking them instead, with a clearer understanding of where AI works best alongside their employees, not in place of them.”
The survey is based on responses from 2,000 U.S. hiring managers across a range of industries. Of the group, finance (44%), tech (32%), and HR (35%) were the sectors with the most hiring managers who say they have rehired for the same roles—but marketing and creative, legal, healthcare, and administrative and customer support followed closely behind.
“While it varies by industry, it’s mostly areas where AI may be able to support the work but can’t fully own the outcome,” Slabinski says. “Our data shows companies are rehiring positions that rely more on institutional knowledge, relationship building, or simply more hands-on support.”
Of those hiring managers, 40% say that they rehired because the role required institutional knowledge or context that AI couldn’t replace.
More than a third (35%) say that the productivity gains were smaller than expected, and 38% say that AI required more human oversight or quality control than expected. Other reasons included an increase in business demand, risk or compliance concerns without a human in the role, team burnout or workload strain, and AI tools not being fully adopted or used consistently across teams.
“At a broader level, I think it reflects a realization that they are missing some skills that can’t be automated, like judgment, cross-collaboration, and accountability,” Slabinski says. “The ‘boomerang’ effect is often more about the role being brought back than the same person—although candidates who can step in quickly with strong industry experience are especially appealing.”
Some CEOs are struggling to see the ROI on AI, which, it turns out, is really expensive. Uber recently capped its employees’ monthly AI spend budget, while Microsoft canceled its Claude Code licenses to mitigate spend and focus on using in-house models instead. Uber’s co-president and COO, Andrew Macdonald, said in a podcast episode last week that “it’s very hard to draw a line” between AI adoption and new consumer products.
Other CEOs have been vocal about how humans will need to work with AI.
In a recent X post, Box CEO Aaron Levie used software engineering as an example of a field widely expected to be displaced by AI. He pointed out that AI has caused companies to take on more projects, which can require more engineers with deep technical knowledge. “You can get by for a while by being nontechnical building software,” Levie wrote. “But eventually, someone has to understand what the thing is that got built, has to maintain it, has to fix security issues that come up, upgrade the systems beneath it, and so on. That’s all jobs.”
He added: “Now apply that to a number of other job functions. AI is going to cause companies to hire more in sales because agents can let them process more leads and do more customer research. AI will cause an explosion of new marketing roles because of how much more efficient it is to launch campaigns and target. The list goes on.”
As for how companies can regain employee trust between mass layoffs and the “boomerang” effect, Slabinski says that transparency is key.
“Companies should be more intentional about explaining how AI fits into the business and what’s expected from day one, which helps set a more realistic foundation,” she adds. “I think it’s also just as important to consistently recognize employee contributions—more specifically, the people behind the work. That goes a long way in reinforcing trust and showing that even with new technology, people are still at the center of the work being done.”