Using Performance Leader AI tools for feedback summaries

Ray D'Cruz
Performance Leader

Performance Leader is piloting AI tools to support more frequent, easier and better feedback interactions between people.

In our first pilot, reviewers are using Microsoft Azure Chat GPT in Performance Leader to summarise feedback from multiple sources.

The problem we’re solving is a simple and common one: reviewers spend significant time sifting through reviewee self-reflections, and multi-source (peer/360) feedback to generate their own feedback.

With Microsoft Azure Chat GPT in Performance Leader, a first cut of that reviewer summary can now be generated at the click of a button. Reviewers can then edit that summary, interspersed with their contribution.

Consider this simple ROI calculation: if every reviewer in a PSF of 1000 people saves 7 minutes on the first cut summary, then the application of AI will save 116 firm hours. That's more time for preparation and conversation, and time saved overall.

This is just the first step in our AI journey at Performance Leader. We know it's early days, and there’s much experimentation and validation to be done.

We’ve chosen Microsoft Azure Chat GPT as our AI partner because most of our clients are already using these products.

Performance Leader is guided by a philosophy that says that the role of technology is to facilitate more frequent, easier and better feedback interactions between people. The best technology recognises its place in solving problems.

If you’d like to learn more about our use of AI and how it could save time and facilitate better feedback, please get in touch with Paul Lemon (

Next week we’ll discuss another AI use case: identifying potential goals from feedback. Stay tuned!

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