Will companies quietly reverse their AI-driven layoffs?

Forrester's 2026 workforce predictions state: "We expect half of AI-attributed layoffs to be quietly reversed, with jobs returning offshore or at lower wages." The framing is explicit that this is a forecast for the coming year, not a measurement of what has already happened — Forrester describes its annual exercise as stepping back from "the noise" to ask what leaders need to hear "not just what they want to hear."

The reasoning Forrester gives is that "the AI-washing and mirage of future AI collides with operational reality," and that "many firms are realizing that replacing humans with machines isn't always cheaper, or smarter, unless they have a complete approach that accounts for the people on whom all AI success will depend." In other words, the predicted reversal is not attributed to AI capability failing outright, but to layoff decisions having been made on inflated expectations of AI-driven savings that operational practice does not bear out — so firms rehire, often offshore or at lower wages, rather than reinstating the original roles.

This sits in tension with Is generative AI displacing workers at economy-wide scale?, which finds a hiring-driven shortfall for young workers in exposed occupations through mid-2026 rather than mass layoffs reversing — Forrester's claim is about a subset of layoffs specifically labeled "AI-attributed" being walked back, which is a narrower and more mechanism-specific claim than an economy-wide displacement or non-displacement finding. It also complements Does concentrated AI exposure enable workers to adapt and reallocate?: both describe employment effects that are less severe or more reversible in practice than headline AI-labor narratives suggest, though Forrester's mechanism is specifically the gap between AI-washing rhetoric and delivered savings, not task-level reallocation. It also stands apart from Does AI growth inevitably shift wealth away from workers?, which models aggregate wage and labor-share trajectories rather than the micro-level churn of specific layoff-then-rehire decisions Forrester describes.

The excerpt gives no sample, no methodology, and no data behind the "half" figure — it is a named consultancy's analyst judgment, presented as a prediction for the year ahead rather than a retrospective count of already-reversed layoffs. Forrester is itself a research and advisory firm that sells guidance to the same enterprise leaders it is forecasting about, so the prediction should be read as expert forecasting intended to shape client decisions, not as independently verified outcome data. Whether "half" proves accurate, and whether reversed roles return onshore or offshore, at comparable or lower wages, remains to be seen through 2026.