Watch this 27-minute on-demand session to see why AI-inferred, self-reported, and manager-assessed skills data is claimed, not proven — and what it actually takes to build defensible, decision-ready skills data.
Most workforce skills data falls into one of three buckets: AI-inferred from projects and performance data, self-reported by employees, or manager-assessed through reviews and endorsements. The problem? All three are claimed, not proven. Building a skills strategy on claimed data is a risky bet when the decisions on the line are promotions, hiring, and where you invest next.
What You'll Learn
| The real difference between claimed and demonstrated skill |
| When that difference actually matters (and when it's fine to rely on inference) |
| How to build demonstrated evidence at scale, in any program |
Who This Is For
CLOs, Heads of L&D, and Talent Development leaders ready to move beyond satisfaction scores.
Presented by Peerceptiv, built on 16+ years of peer learning research from the University of Pittsburgh.
| Watch On-Demand |