If Output Isn’t Evidence of Performance, What Is?

Performance reviews are often still be based on output, even though output no longer tells you much about the person who produces.

Only 7% of CHROs are piloting performance metrics built around judgment rather than task completion, according to the 2026 CHRO Association survey. Nearly half say a performance management redesign is on the roadmap and hasn’t been implemented.

In our first AI Signal event, we take on one question: if output isn’t evidence of capability, what is? We’ll discuss how performance management criteria are changing because of AI-driven workflows, what a review still tells us about performance when AI does part of the work, how to rate people fairly when some have better AI tools than others, and what talent leaders who’ve attempted a redesign say they have learned. 

You’ll learn how to:

1. Create a current performance management criteria that accounts for AI-assisted work.
2. Learn what organizations attempting judgment-based criteria have learned.
3. Know why hours saved is an incomplete measure, and what it looks like to account for correction time alongside it.
4. Audit whether your recent talent decisions reflected capability or tooling. 
5. Implement practical guidance on what to tell managers ahead of this performance review cycle, even if your organization may not have changed anything before reviews open.

Who this is for: CHROs, CPOs, heads of talent, and people analytics leaders heading into a review cycle that needs to be redesigned.