Laid off staff hard to win back

The wave of AI‑driven layoffs has left many tech workers scrambling for new roles, but companies are now trying to bring some of those employees back, a process that proves more difficult than it sounds.

Mass layoffs and the AI effect

According to a recent report, more than 122,000 technology workers were laid off in 2025, with a similar number—126,000—losing jobs in 2026. The cuts were not limited to a few firms; AI reshaped entire sectors, turning formerly stable tech careers into precarious positions.

Many displaced professionals have spent months handling a hiring market that now favors AI‑augmented skills. The situation is shifting, however, as the same organizations that issued the layoffs are reaching out to former employees, hoping to restore lost expertise.

Why rehiring isn’t a simple fix

Ali Gohar, chief human resources officer at Software Finder, warned that “you’ll get their labor but not their loyalty.” He added that the most valuable former staff are those who continued to develop their careers elsewhere, and they are unlikely to forget how they were treated.

Joe Coletta, chief executive of 180 Engineering, echoed the sentiment, noting that workers who saw leadership present AI as a replacement for human expertise “will naturally question whether their job will last beyond the next round of automation.” Money alone cannot repair that breach of trust.

Rehiring aims to reclaim institutional knowledge that AI cannot replicate, yet the process carries hidden costs. Gohar explained that onboarding a returning employee can cost “roughly one to two times the old employee’s annual salary,” because contextual understanding does not transfer automatically.

Hiring brand‑new staff presents its own challenges. New hires lack the “invisible tasks” knowledge that long‑standing teams possess, meaning they require extensive training before reaching full productivity. Jack Mellor, chief executive of Personnel Checks, highlighted that the expense of replacing experienced workers can run into “many thousands of pounds” before the newcomer becomes effective.

Even senior or specialized roles often take three to six months to fill, and many firms have eroded their junior talent pipelines, leaving a gap for mid‑level positions.

In practice, the rehiring process can be slowed by AI‑driven screening. Candidates often must tailor resumes for keyword matching, submit applications to multiple roles, and endure AI interviews that may reject them within hours.

When a machine, rather than a person, delivers the rejection, it can deepen the perception that the employer values efficiency over human judgment.

Coletta pointed out that success hinges on leadership acknowledging past mistakes and offering clearly improved roles within a demonstrably changed environment.

From a broader view, the AI‑induced layoff‑rehire cycle mirrors earlier tech downturns, where companies that failed to address cultural wounds found it harder to attract talent later.

The current scenario differs mainly in the speed at which AI can replace routine tasks, amplifying the urgency for firms to rebuild trust quickly.

Companies weigh the costs of rehiring versus hiring anew, balancing financial considerations, the need for specialized knowledge, and the ability to demonstrate a genuine shift in how AI is deployed alongside human workers.