**The big picture:** A new survey reveals that nearly three-quarters of HR professionals regret AI-driven job cuts, finding that the costs associated with these reductions ultimately exceeded any savings. **Why it matters:** This trend highlights a significant miscalculation by organizations regarding AI's capabilities and the true cost of workforce disruption, impacting talent strategies and financial performance. **Between the lines:** - 91.6% of HR leaders regret their organization's approach to AI-driven restructuring. - 54.6% found new AI systems required more human oversight than anticipated. - Approximately one-third of organizations rehired more than half of the roles initially cut. **Staffing & HR impact:** The need to rehire and retrain after AI-related layoffs creates significant re-recruiting costs and impacts recruiter mobility, while the loss of institutional knowledge strains remaining HR resources. **The bottom line:** Companies must carefully assess the full financial and human capital implications before implementing AI-driven workforce reductions.

**The big picture:** Companies are increasingly attributing layoffs to AI investments, but a disconnect exists between the stated reasons and actual impact, often leading to critical skill loss. **Why it matters:** Excluding IT leaders from layoff decisions risks misjudging AI capabilities, leading to unnecessary job cuts and undermining the very productivity gains companies seek. **Between the lines:** - 99% of C-suite leaders anticipate headcount reductions in the next two years. - Nearly a third of HR professionals report critical skill loss due to AI-blamed layoffs. - Only 35% of IT and HR leaders collaborate on AI-related workforce decisions, despite 94% seeing it as a priority. **Staffing & HR impact:** Staffing firms and HR departments face challenges in backfilling lost expertise and ensuring compliance if AI-driven layoffs are based on flawed assessments, potentially impacting gross margins and recruiter mobility. **The bottom line:** Involving IT leaders in layoff decisions is essential to ensure accurate AI assessments and prevent