TL;DR

I’ve discovered a couple highly practical uses for GenAI this week relative to performance reviews.

In one case, I collected various stakeholder feedback for an individual on my team (using these questions from the other day) and used AI to extract common themes (both strengths and growth areas) that I could share without revealing who wrote what (which I’d promised in the hopes of getting more honest responses). It was also useful for me as a manager to see what emerged so we could review together.

In another, I took all the self-evaluations across a team and asked AI to identify and then summarize specific portions that would be relevant to pass along to the broader leadership group (e.g. feedback they had about the organization, common challenges that might be indicators of systemic problems). It’s a lot to ask of an executive to read these docs in their entirety, but there’s valuable insights to be gleaned. Building this summary was the best of both worlds.

Something my years at Amazon taught me is the usefulness of discussing performance in light of shared values. Our evaluation forms this year broke down questions along those lines (at my suggestion), but I’m now seeing it may be a bit too structured and artificially constraining. So next year I might see if we can keep the reflection questions a bit more open-ended, and then use AI tooling to align people’s responses to our specific guiding principles. Will that be effective? Not sure! But worth a try.