A growing number of companies are being forced to rehire workers after cutting jobs in anticipation of artificial intelligence savings that have yet to materialise, according to new research.
The study by Orgvue found that 32% of organisations that made layoffs linked to AI have since had to bring staff back, exposing a widening gap between ambition and execution.
The findings suggest that, for many businesses, the rush to adopt AI has led to costly miscalculations – and, in some cases, a “fire-and-rehire” cycle.
LACK OF AI UNDERSTANDING
At the core of the issue is a disconnect between technology adoption and operational reality, noted the study. Many organisations are deploying AI tools without a clear understanding of the specific tasks, roles and workflows they are trying to transform.
As a result, workforce reductions are being made based on broad assumptions rather than detailed analysis. The research found that:
- 23% of companies that made layoffs relied on general assumptions about AI capabilities.
- 42% of organisations are still only testing or researching AI deployment.
This reflects a wider trend across the labour market, where expectations around AI are moving faster than operational readiness.
DAMAGING FIRE & HIRE CYLCES
Even before results are proven, AI is already influencing hiring and redundancy strategies. Research shows that three in ten companies plan to replace employees with AI by 2026, while separate findings indicate that around one in three firms are planning layoffs as part of cost-cutting strategies.
Together, these trends highlight how anticipation of AI-driven efficiency – rather than proven outcomes – is driving workforce decisions. For some organisations, those decisions are now being reversed.
Rather than delivering immediate efficiency gains, AI deployment is in some cases creating operational gaps that require rapid rehiring to maintain productivity. This cycle introduces a range of hidden costs – from recruitment expenses to lost time – while undermining the original business case for workforce reduction.
Jessica Modrall, Chief Product Officer at Orgvue, said the issue lies in how organisations understand their workforce. “AI has genuine, transformative potential to reshape how organisations work, but that potential can only be unlocked when leaders have a clear, detailed picture of how work gets done today and who does it,” noted Modrall. “Right now, too many organisations are deploying AI without understanding the work in detail. That’s not an AI problem; it’s a workforce intelligence problem.”
ECONOMIC PRESSURES DRIVING LAYOFFS
Despite the focus on AI, the research suggests that traditional economic factors remain the primary driver of workforce reductions. For example:
- 43% of organisations cite economic conditions as the main reason for layoffs.
- 31% point to company restructuring.
Together, these account for 74% of workforce reductions, indicating that AI is often being used to justify broader organisational change rather than acting as the sole cause.
GUIDANCE FOR EMPLOYERS
The findings highlight a growing risk for organisations moving too quickly to cut roles in anticipation of AI-driven savings. Beyond missed expectations, the consequences can be financially and operationally damaging. Here are a few lessons for employers:
Redundancy is not a reversible cost
Letting employees go carries immediate expenses, including redundancy pay, notice periods and legal risk. Rehiring often comes at a premium, particularly in uncertain labour markets.
Rehiring costs can erase projected savings
Recruitment fees, onboarding and higher salaries for replacement hires can quickly outweigh any anticipated cost reductions from AI.
Lost time reduces productivity
When roles are cut prematurely, critical work slows or stops. Rebuilding teams takes time – delaying projects, reducing output and impacting customers.
Institutional knowledge disappears
Employees take with them expertise, relationships and operational insight that cannot be easily replaced, creating long-term inefficiencies.
Talent loss damages long-term performance
Layoffs followed by rehiring can weaken employer reputation and reduce trust. High-performing employees may leave – or avoid returning – increasing retention challenges.
Morale and engagement decline
Repeated workforce changes create uncertainty among remaining employees, affecting productivity and increasing turnover risk.
AI should augment, not replace
Without a clear understanding of how work actually gets done, organisations risk making reactive decisions based on hype rather than strategy.
THE COST OF MOVING TOO FAST
The promise of AI-driven efficiency is compelling, but the reality is proving more complex. For many organisations, the rush to reduce headcount has resulted in false economies. This includes short-term cost cutting followed by longer-term expense, disruption and lost capability.
Redundancy payouts, rehiring costs, lost productivity and weakened employee trust can quickly outweigh any anticipated savings. At the same time, broader workforce trends, including rising layoffs and growing reliance on automation, suggest that many companies are still navigating this transition without a clear roadmap. The result is a growing divide between expectation and execution.
As AI adoption accelerates, the organisations that succeed are likely to be those that move more deliberately, investing in understanding their workforce, building skills and aligning technology with how work actually gets done. Because ultimately, the cost of getting AI wrong is not just financial – it is measured in time, talent and trust.
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