AI Talent Migration Into U.S. Healthtech
An analysis of 142 observed career transitions examining where U.S. healthtech businesses source AI talent and how those patterns differ across healthcare technology segments.
Research and observations about how talent markets work, where experience comes from, and how consequential hiring decisions get made.
Original research and perspectives on the markets, requirements, and decisions shaping leadership hiring.
An analysis of 142 observed career transitions examining where U.S. healthtech businesses source AI talent and how those patterns differ across healthcare technology segments.
AI has made candidates easier to identify, but more precise searches do not automatically produce faster hiring. A look at candidate availability, escalating requirements, and the continuing role of market judgment.
How imprecise role requirements and misaligned expectations can undermine leadership hiring in PE-backed businesses, and why agreement on success matters before a search starts.
Why leadership hiring increasingly involves tradeoffs among growth, financial exposure, and accountability, particularly for talent leaders working under tighter constraints.
How to define and assess a customer-facing data scientist through technical work, domain understanding, customer communication, and collaboration with internal teams.
Direct, experienced perspective on leadership priorities, the talent market, and the requirements that matter.