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Ford, IBM and Commonwealth Bank Reverse AI-Driven Layoffs
Companies that laid off workers banking on artificial intelligence are starting to hire them back. Robert Half estimates that roughly one in three American hiring managers has already done exactly that.
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Ford has brought back hundreds of quality engineers, Commonwealth Bank of Australia has reversed layoffs in customer service, and IBM is preparing to triple entry-level hiring in the US. All three companies previously cut staff citing the capabilities of artificial intelligence, and now admit that automation couldn't handle the tasks it was meant to take over.
What went wrong
The story follows a pattern that's been typical of the last two years: companies announced staff cuts, pointing to advances in generative AI as justification. Large language models were supposed to take over the work of analysts, customer service consultants, or quality control engineers. In practice, as TVN24 Biznes reports, some of these tasks turned out to be too complex or too risky to leave to unsupervised algorithms.
Ford is the most striking example. The automaker relied for a time on automated systems to detect quality defects in production, scaling back the engineering teams responsible for design reviews. But those systems missed problems that experienced staff routinely caught. The company restored hundreds of positions, and engineers went back to conducting design reviews before production even started.
The bank that couldn't keep up with the calls
A similar mechanism played out at Commonwealth Bank of Australia, one of the continent's largest banks. The institution eliminated more than 40 customer service positions, replacing people with an AI-based voice bot. Instead of lower costs and fewer inquiries, the bank saw call volumes rise, because the bot couldn't handle customers' more complicated issues. The layoffs were reversed.
IBM took a different route but arrived at a similar conclusion. The AI system deployed in its HR department handles, according to the company, 94 percent of routine employee requests. The problem lies in the remaining cases, which often require ethical judgment or interpretation of ambiguous situations where the system falls short. In response, IBM announced it would triple entry-level hiring across the organization in the United States in 2026.
The scale of the trend
These aren't isolated cases. Research firm Orgvue found that 39 percent of business leaders carried out layoffs linked to AI adoption, and more than half of them later admitted that at least some of those decisions were wrong. Robert Half went a step further and asked US hiring managers directly: nearly one in three admitted to eliminating positions mainly because of AI, then rehiring people into the same or very similar roles.
Analytics firm Gartner goes even further in its forecasts, estimating that about half of companies that attributed staff cuts to AI will hire people into comparable positions by 2027. That suggests the wave of layoffs justified by automation will largely prove reversible rather than a lasting shift in workforce structure.
It's hard to draw a correlation between the huge growth in Claude Code usage and spending on it, and innovations that actually serve consumers - Andrew Macdonald, Uber's chief operating officer
Hopes versus the bill
The reversal of layoffs coincides with growing doubts about the return on AI investment even among tech companies themselves. Uber burned through, as COO Andrew Macdonald revealed, its entire annual budget for AI coding tools in four months, with no clear link between the spending and benefits for customers. The Financial Times, meanwhile, estimated widely varying returns on AI investment among big tech firms, ranging from positive at Amazon to clearly negative at Oracle and Meta.
Experts cited by the media stress that the mistake was treating AI as a one-to-one replacement for a worker. Language models handle repetitive, simple tasks well, but complex decisions requiring context, risk assessment, or interpretation of ambiguous situations still need a human. Companies that ignored this during the first wave of cuts are now paying twice to correct course: the cost of the layoffs and the cost of rehiring.
What it means for Poland
For the Polish labor market, the signal is significant, though it should be read cautiously. Polish companies, as earlier surveys have shown, still more often report seeking AI skills than actually laying people off because of automation. Still, the experiences of Ford, IBM, and Commonwealth Bank show that staffing decisions made under pressure from narratives about AI swiftly replacing humans can be costly to walk back, especially in roles requiring quality control, customer service, or judgment in unusual situations.
For HR departments and executives, that offers a practical takeaway: before a position disappears from the budget, it's worth checking whether an AI system actually closes out a process end to end, or only handles its simplest part while leaving the exceptions to a human. Ford, the bank, and IBM found that out after the fact.
