Skills-based talent management has been a major investment area for years, yet many organizations are still struggling to show clear value from heavy enterprise architectures, complex taxonomies, and rigid proficiency models.

With rapid advancements in AI, technology decisions made just two years ago are already ripe for reconsideration. Rather than overengineering systems, leaders must rethink their architecture, technology, and starting point to keep skills data precise enough to trust, but nimble enough to maintain.

Led by Shweta Srivastava, Matt Donovan, Katie McAllister, Craig Friedman, and Matt Sernaker, c

What we heard

Peers compared what's actually working in skills-based talent management: start narrow around one outcome, match validation to the stakes, and infer skills from the work itself.

"With 200,000 people, lack of visibility is a real strategic problem."
Shweta Srivastava

"When is the juice worth the squeeze? And it's not all the time, but it is some time."
Community voice