Using Performance Leader AI tools for feedback summaries

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

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

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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.

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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.

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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.

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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.

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

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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.

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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 (paul.lemon@performanceleader.com)

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