Redesigning Talent Strategies for AI

I hope you're doing well.  For this weekend, we worked on creating a detailed paper reflecting on the various panels and presentations from our user conference in NYC

Four interlocking shifts that surfaced repeatedly:

1. Work must be deliberately decomposed
   Break roles into tasks → classify them (routine cognitive, non-routine judgment, etc.) → redesign workflows with AI embedded by design (not bolted on). Administrative & coordination friction is the highest-confidence, lowest-regret starting point.
2. Talent Acquisition is becoming a trust & judgment layer
   AI accelerates screening/sourcing, but human-in-the-loop validation (especially final decisions) is now viewed as a competitive differentiator rather than a legacy step. Candidate experience and authenticity checks are non-negotiable; many organizations are already pulling back from fully automated video interviews.
3. Workforce planning must move from headcount → capability modeling
   Job categories are becoming unreliable planning units. Skills + task portfolios are the new “balance sheet.” Early macro signals: denser JDs, rising IC: manager ratios in some functions, hiring slowdown in highly automatable areas.
4. Skills architecture is a continuous infrastructure — not a project
   One-time mapping quickly becomes stale. Future baseline capabilities now include:
   • Critical thinking (interrogating AI outputs)
   • Learning agility
   • AI output review & override judgment

Please read the paper and share your reflections