Before AI layoffs, do companies seriously consider moving people to new roles — or cut first and figure it out later?

This explores whether firms look at moving people into other work before cutting jobs for AI. The short answer is that no source in the collection measures redeployment directly. What the collection does show is indirect, and it points one way: many companies cut first and assess later. The clearest case is Commonwealth Bank. It eliminated 45 roles, then reversed the decision and admitted its assessment "did not adequately consider all relevant business considerations." Klarna and IBM went through similar cycles of cutting and then rehiring Do banks accurately assess whether AI can replace customer service jobs?. A firm that had seriously weighed redeployment would probably not have needed to rehire the same roles within months.

The pattern is common enough to show up in aggregate numbers. One HR vendor survey found that 73% of companies rehired more than half of the roles they had cut within six months. Nearly a third spent more on rehiring than the layoffs saved Do AI layoffs actually save money for companies?. Forrester predicts that half of AI-attributed layoffs will be quietly reversed, often by rehiring offshore or at lower wages rather than bringing the original staff back Will companies quietly reverse their AI-driven layoffs?. Both point to the same cause: companies overestimated which tasks AI could take over. Part of the reason may be that "AI" is a convenient label for a layoff. Challenger's tracking makes AI the leading stated reason for 2026 job cuts, but it counts what employers announce, not displacement anyone has verified Is AI really driving job cuts in 2026?.

The more useful finding comes from economists, and it reframes redeployment as something that depends on how AI touches a job rather than on management goodwill. When AI affects only a few tasks within a role, workers can shift toward the tasks AI doesn't handle, and overall job losses stay modest. When it affects many tasks across a role, there is little left to shift to Does concentrated AI exposure enable workers to adapt and reallocate?. In other words, redeployment is easiest where AI changes part of a job rather than most of it. That is also where layoffs are hardest to justify, which may help explain why so many get reversed. Firms also differ in how quickly they swap human work for AI. Companies that already have strong internal AI capability make the switch faster and more cheaply, so the decision depends on the firm, not just on the technology Do firms substitute labor for AI at different rates?.

The surprising part is that the biggest workforce change may not be layoffs or redeployment at all, but hiring that never happens. Payroll data show no economy-wide job losses from AI so far. Instead, young workers in AI-exposed occupations are hired at sharply lower rates than their peers, while experienced workers show no such gap Is generative AI displacing workers at economy-wide scale? Is AI already shrinking the entry-level job market?. Companies can protect existing staff while quietly shrinking the entry-level pipeline, so the open question shifts from whether current workers get redeployed to whether new workers get hired at all. Executives and employees also disagree about the future. Executives expect AI to cut headcount slightly, while employees expect it to grow Do executives and employees agree on AI's job impact?. That gap suggests decisions about who stays and who moves are being made with little input from the people whose work is affected.