Using AI to prep managers before performance reviews. What are you doing?

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We're seeing the same challenge in many organisations. Summarising Teams chats and emails can provide useful context, but it rarely gives managers the full picture because performance conversations should be grounded in goals, outcomes, feedback, development progress, and documented achievements, not just activity.

The most effective approach I've seen is using AI to aggregate information from multiple sources rather than relying on communications alone. This might include performance goals, manager and peer feedback, one-on-one notes, project contributions, learning records, recognition, action items, and relevant collaboration data. AI can then help managers identify themes, accomplishments, challenges, and growth areas while keeping the employee's actual objectives at the centre of the review.

One lesson we've learned is that managers should not wait until review season to gather evidence. Encouraging employees and managers to capture wins, feedback, and key outcomes throughout the year creates much better inputs for AI-generated summaries and leads to fairer, more balanced reviews.

I'm curious what others are using. Are you relying on your performance management platform, a dedicated AI HR solution, or building something with Microsoft 365 Copilot and your existing systems?