Data Warn Against Large-Scale Cuts to Middle Managers as AI Encourages Organizational Flattening

Surveys show companies are already trimming management layers and forecasts predict AI will accelerate flattening, but research tying managers to core outcomes warns broad removals could damage engagement, performance, and legal risk.

New data show companies are actively cutting management layers even as AI adoption is expected to encourage further flattening — and experts warn that sweeping removals of middle managers could have costly downstream effects. A Korn Ferry survey of 15,000 professionals found 41% of employees said their employers cut management layers last year, and middle managers accounted for more than 31% of layoffs in 2023, signaling both a current shift and a large population at risk.

Forecasters expect the trend to accelerate with AI. Gartner projects that through 2026, 20% of organizations will deploy artificial intelligence specifically to flatten structures and eliminate more than half of middle management roles. Proponents point to AI’s ability to handle routine managerial tasks — taking notes, drafting goals, scheduling one-on-ones, and highlighting underperformance in dashboards — as reasons those roles could be reduced or redesigned.

But the empirical case for wholesale cuts is complicated by research linking managers to measurable business outcomes. Gallup finds managers account for at least 70% of the variance in employee engagement scores across business units, and those engagement differences correlate with customer ratings, profitability, productivity, turnover, absenteeism, and safety incidents. Because engagement ties into these downstream metrics, removing manager capacity can affect product quality, operational risk, and financial performance.

The practical implication for leaders is clear: eliminating managers to save payroll may yield immediate cost reductions but also produce harder — to-measure losses in engagement and outcomes. The article’s author — drawing on years as an employment lawyer and HR practitioner — warns that removing human judgment and the capacity to clean up complex situations risks legal exposure, operational failures, and morale decline that current AI tools do not reliably resolve.

For product teams building HR and management tooling, the takeaway is concrete. Design AI to augment manager workflows rather than replace the role entirely; instrument engagement and performance metrics before and after pilots; and preserve functions that require contextual judgment, coaching, and human empathy. Pilots should include control groups, short feedback loops, and clear escalation paths for issues AI flags but cannot resolve.

Timeline and governance will matter as firms plan any flattening. With Gartner’s 2026 horizon and ongoing layoffs through 2023 — 2025, organizations should set explicit measurement goals for flattening efforts — engagement delta, turnover, customer metrics, and legal incidents — and invest in manager development where discrete tasks are automated. That approach lets organizations capture administrative efficiencies from AI while limiting damage to the relationship — driven work managers perform.