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Amazon’s Fire and Rehire: Can Boomerang Hiring Really Work?

With Amazon recruiting back some of the 30,000 people it let go and Gartner expecting 30% of workers replaced by AI to be rehired at higher cost, companies need to weigh what the next round of cuts will cost, from lost skills to damaged trust, before approving it

Corporate layoffs once carried a certain gravity. A company hit a wall, cut costs and announced the decision with visible reluctance. Recent tech job cuts show how far that script has changed, with many companies now announcing record profits in the same breath as job cuts.

Oracle, Microsoft and Amazon have been high-profile examples. However, Amazon has made a move that has raised eyebrows. After cutting more than 30,000 jobs over the past year, the company has been tasking recruiters with contacting former employees about open roles, including positions in AI and cloud. Amazon says boomerang hiring is a longstanding, companywide practice rather than a new program.

There is precedent for this approach. ADP data shows that returning employees made up 35% of US new hires in March 2025, up from 31% a year earlier. Gartner predicts that by 2029, 30% of employees laid off because AI replaced them will need to be rehired.

Although companies may have both the desire and the need to rehire, will the employees they let go be as keen to return? Marcus Mossberger, Chief Market Strategy Officer at Lytiqs, who once had to lay off ten people himself during a reduction in force, is skeptical. His doubts are not about the merits of boomerang hiring itself, but about whether the way companies handle layoffs damages their prospects of bringing former employees back.

What Drives the Cut-Now, Rehire-Later Cycle

Before asking whether this approach will work, we need to ask why companies lay people off only to rehire them later. One answer is that layoffs can signal commercial strength. Mossberger says they "used to be kind of a last resort," but "what's disturbing is that they frequently occur when these organizations are in very solid financial condition." AI supplies the justification. Companies either need to fund AI infrastructure or expect the technology to make people redundant, presenting the cuts as unavoidable.

Companies then take a broad-brush approach to layoffs, only assessing what they need after the cuts have been made. Mossberger traces that failure to poor planning:

"I don't think that a lot of organizations, including Amazon, are doing a very good job of that."

A wave of retirements is expected to hit the global workforce, leaving fewer people available by 2029. Mossberger argues that returning workers will therefore be able to command more money, and that "organizations are literally shooting themselves in the foot by having this short-sighted point of view about what to do with their talent today."

Skills Visibility as the Alternative to Cutting

Mossberger argues that companies should take a different approach before making any decisions about layoffs. Employers should inventory their existing talent, distinguishing skills that quickly become outdated from those that transfer across roles. To do this, Mossberger puts it plainly,

"They should then look beyond adjacent positions, considering opportunities to the left or to the right."

Someone may have the behavioral traits needed to succeed in a role nobody would previously have considered for them.

However, that inventory only helps if it can be trusted, which is where Lytiqs focuses its work. Self-reported skills are a weak basis for redeploying employees, and Mossberger challenges employers directly: "have you actually taken the time to validate what skills people actually possess?" Validated skills data turns a list of job titles into a clearer picture of who could do what and how quickly. Without it, a redeployment plan is guesswork, and cutting jobs can look like the easier option.

A temporary move, Mossberger argues, allows companies to retain institutional knowledge and the "intellectual capital that we've made investments in over time." Employers can avoid both severance costs and the premium they might pay to bring someone back later.

That approach could help companies save money while maintaining the staffing levels they need. Resume Genius found that 86% of laid-off workers say the experience changed how they view job security and employer loyalty. Companies therefore face not only the added cost of rehiring, but also the possibility that the people they let go will not return.

Some cuts will still be unavoidable, but how they are handled can determine whether former employees return. Drawing on his HR experience, Mossberger points to empathy and transparency, which he says are missing from layoffs today. Amazon's own 2023 guidance, in which an AWS HR leader urged managers to "proactively extend an invitation" to former staff, suggests the company understands the value of keeping the door open. However, that approach only works if people leave on decent terms.

Why Readiness Matters More Than Prediction

If Mossberger is right, the labor supply that made routine workforce reductions feel safe will tighten, and employers that have burned through goodwill will find it harder to recruit and rehire.

He argues that companies should spend more time planning their workforces to remain agile without undermining their future hiring prospects. That means looking beyond headcount reductions and considering how existing employees could contribute in different roles as business needs change.

Leaders should therefore watch whether the AI productivity case holds up and whether Gartner's 2029 rehire forecast proves accurate. Before the next restructure, the question is not how many roles AI can eliminate, but where else those employees could contribute. Companies that can answer that question using verified skills data will retain both their institutional knowledge and their credibility. Those that cannot may find themselves, like Amazon's recruiters, making the call to bring former employees back.

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