AI tools can help you produce performance reviews faster and make feedback sound more polished and consistent. But smoother language can also mask weak evidence, subjective judgments, and incomplete observations.
The bigger opportunity is to use AI to help you identify what your employee actually did—the decisions they made, the problems they solved, and the influence they had on others. Here’s how.
Focus on consequential moments. Instead of evaluating broad traits like leadership or strategic thinking, start by asking yourself which moments best revealed those capabilities in your employee. A difficult decision, a project pivot, or a key trade-off often says more than a page of unspecific evaluation language.
Set clear governance. Define which communication channels and document types are fair game for performance evidence and which are off-limits. AI should curate evidence, not make decisions or value judgments. Keep humans responsible for interpretation and ensure every example links back to a verifiable source.
Use AI to surface evidence. Direct AI tools toward finding examples of influence, problem-solving, and other performance criteria. Search for moments where your employee changed a project’s direction, resolved a conflict, or helped others succeed.
