Nearly a third of workers terminated and replaced by artificial intelligence (AI) will be rehired by 2029 — often at higher salaries — as companies grapple with shortsighted talent strategies.
The findings, announced at Gartner Inc.’s annual HR Symposium/Xpo, underscores a growing crisis across corporate America: Businesses are rushing into AI-driven layoffs without understanding the operational mechanics required to sustain their businesses.
“Many organizations are making AI and workforce decisions in the wrong order,” said Caitlyn McDonough, vice president analyst in Gartner’s HR practice. “They decide how many people to let go before they understand what it will take to get work done. The goal should be to understand what work matters most to the strategy, how that work is changing, and the right mix of people and technology needed to deliver business outcomes.”
The forecast reflects findings from a July 2026 Gartner survey of nearly 300 chief human resources officers. Just 19% of respondents reported having workforce planning frameworks capable of handling AI’s impact and matching talent deployment with corporate objectives.
That deficit carries real financial consequences. Gartner’s data shows companies with effective strategic planning mechanisms are 1.4 times more likely to beat revenue targets and 1.5 times more likely to outperform cost goals.
Addressing the gap, Gartner unveiled a five-stage strategic workforce framework designed to replace conventional, bottom-up planning models.
Analysts noted that legacy approaches typically scrutinize existing headcounts and speculate on how software might automate individual roles. Gartner warned that this methodology is increasingly flawed, as rising deployment costs force companies to focus technology investments strictly on core strategic goals.
The new blueprint prioritizes high-level enterprise goals first, breaking operational needs into five distinct phases: identify critical capabilities, forecast future work demand, assess future workforce supply, quantify talent gaps, and establish formal governance.
A central innovation of the framework lies in forecasting work demand by deconstructing functions into measurable units. This granular visibility allows leaders to pinpoint the precise ratio of human labor versus automation needed to hit key milestones.
Rather than deploying the framework across entire enterprises immediately, Gartner recommends HR executives pilot the model within one or two critical business capabilities before rolling it out companywide.
“To prepare for an AI-driven future, leaders should stop planning for the workforce they have and start planning for the workforce their strategy requires,” McDonough said. “When organizations shift the focus from jobs to work and work demand, they avoid costly workforce missteps and allocate resources more effectively.”
