New Survey: 99 Percent of Executives Expect AI Layoffs Within 2 Years—What It Means for the Workforce

Why It Matters

AI‑driven layoffs signal a fundamental reshaping of the talent landscape, forcing companies to rethink workforce strategy and investors to reassess exposure to automation risk.

Key Takeaways

• 99% of executives anticipate AI‑driven layoffs in next two years
• 63% say AI work redesign will deliver highest value
• 98% plan organizational design changes by 2026
• 2026 tech layoffs hit 144,205 workers; projection 361,000 total
• Oracle cut ~30,000 jobs; Meta slashed 7,000 for AI spending

Pulse Analysis

The Mercer Global Talent Trends survey paints a stark picture: executives are overwhelmingly convinced that artificial intelligence will compress headcount across industries. While AI promises efficiency gains, the survey shows a paradox—leaders see the greatest value in redesigning work around automation, yet they remain skeptical about the workforce’s ability to blend human and machine capabilities. This disconnect fuels a wave of preemptive cuts as firms scramble to align cost structures with ambitious AI roadmaps, especially as AI hardware demand outstrips supply.

For talent leaders, the numbers translate into an urgent need to upskill and redeploy existing staff. With 98% of executives planning organizational redesigns, traditional roles are being re‑engineered or eliminated. The projected 361,000 layoffs by the end of 2026 suggest a talent market that will favor hybrid skill sets—data fluency, prompt engineering, and AI governance—over purely functional expertise. Companies that invest in reskilling pipelines may mitigate the shock, while those that rely solely on attrition risk losing critical institutional knowledge.

Corporate examples illustrate the scale of the shift. Oracle’s abrupt reduction of roughly 30,000 positions follows its push to meet soaring demand for AI infrastructure, backed by $553 billion in remaining performance obligations. Meta’s 10% workforce trim, about 7,000 jobs, funds an estimated $115‑$135 billion AI capex plan aimed at training next‑generation models. These moves signal that AI is no longer a peripheral experiment but a core cost driver, reshaping balance sheets and strategic priorities. Investors and boardrooms must now weigh AI adoption against the human capital implications, balancing short‑term savings with long‑term innovation capacity.