The Talent You Already Have: A Design Thinking Fix for the AI Skills Gap
About this session
Every leadership team facing the AI talent crisis reaches for the same lever: hire more AI talent. But the market for "AI-fluent" hires is thin, expensive, and getting thinner, while the workforce you already have sits on the sidelines, quietly resisting the tools you rolled out last quarter. That resistance isn't a skills gap. It's what happens when someone is handed a tool that makes them feel like they're writing with their non-dominant hand: clumsy, exposed, and one mistake away from looking incompetent. No hiring plan fixes that feeling. No mandate does either. This talk makes the case that the fastest, cheapest path through the AI talent crisis is not external hiring. It's redesigning how you reskill and redeploy the people you already have. Using Stanford d.school's Design Thinking model I will share a concrete, repeatable model for turning reluctant employees into your fastest internal AI talent pipeline.
Speaker
Key takeaways
- The AI talent crisis is a design problem wearing a hiring problem's clothes. Most organizations already have the raw talent; what's missing is a deliberate design for how that talent builds AI fluency, not a bigger recruiting budget.
- A leadership framework for workforce transformation. A practical adaptation of the 5-stage Design Thinking model (Empathize, Define, Ideate, Prototype, Test), applied specifically to reskilling and internal mobility, not classroom training.
- A reskilling pilot leaders can greenlight this quarter. Attendees leave with a concrete first move (a small pilot cohort, a reframed HMW problem statement, or a manager-coaching layer) that de-risks reskilling before it's rolled out org-wide.