Don’t Use AI to Automate a Bad Process — Including Performance Reviews

Key Takeaways

• AI streamlines bad reviews, not better feedback
• 13% of firms claim AI‑driven reviews, likely underreported
• Top innovators have eliminated annual performance ratings
• Coaching conversations weekly outperform yearly rating systems
• Deming’s ‘substitute leadership’ still relevant in AI era

Pulse Analysis

Performance‑review fatigue is a long‑standing pain point for HR departments, and the rise of generative AI has tempted many leaders to outsource the writing and grading of these assessments. The promise—shorter drafts, polished language, and data‑driven insights—ignores the core flaw: the annual review itself rarely changes behavior and often damages employee trust. By automating a process that is already misaligned with modern talent development, AI can inadvertently cement a ritual that offers little strategic value, turning a costly administrative chore into a glossy but hollow document.

Industry leaders have already signaled that the traditional review model is obsolete. Companies such as Adobe, Microsoft, Netflix, and Accenture have either eliminated formal ratings or replaced them with continuous feedback loops. Their shift reflects a broader movement toward real‑time coaching, where managers and employees engage in brief, purpose‑driven conversations multiple times a year. This approach emphasizes growth, removes the anxiety of a high‑stakes annual judgment, and aligns more closely with lean principles that ask, "Should we be doing this work at all?" When the underlying process is sound, AI can be a useful assistant for data aggregation or insight generation, but it should never be the driver of a fundamentally broken system.

The lesson extends beyond performance reviews to any workflow where AI is considered a quick fix. Before deploying generative tools, organizations must ask whether the process creates genuine value or merely satisfies a compliance checkbox. If the answer is the latter, the focus should be on redesigning the workflow—introducing frequent coaching, clarifying expectations, and fostering a culture of continuous improvement—before layering AI on top. In doing so, firms can harness AI’s strengths without amplifying the inefficiencies of outdated practices, ultimately preserving trust and driving measurable performance gains.