E217: The Diagnostic Room: Pilot purgatory: why pharma AI stalls after the first wins
About this episode
Dr Andree Bates discusses the challenges of AI execution in the pharma industry, focusing on the issue of pilot purgatory and the structural constraints that hinder AI adoption.
Pharma doesn’t have an AI experimentation problem. It has an AI execution, scaling, and ROI justification problem. In this solo episode, Dr Andree Bates names one of the most expensive failure patterns in the industry: pilot purgatory. A key theme is misdiagnosis. When AI stalls, organisations often blame platforms, data science capability, training, vendor selection, or “resistance to change”. Dr Andree argues these explanations are usually incomplete because they ignore the structural constraints that determine whether AI gets trusted, governed, adopted, and tied to real decisions at scale. She outlines the core blockers she sees repeatedly: governance ambiguity, unresolved decision rights between global and local teams, data ownership disputes, incentive misalignment across functions, and adoption friction caused by tools that were never designed around real workflows. Treating adoption as a comms issue or solving with yet another pilot simply keeps the constraint untouched. Finally, Dr Andree explains what breaking out of pilot purgatory actually takes: clear executive ownership of business outcomes (not just technical delivery), defined decision points where AI changes…
People in this episode
Host: Dr Andree Bates
Topics covered
- AI execution
- pilot purgatory
- pharma industry
- governance
- adoption friction
- decision rights
Keywords
- AI
- pharma
- pilot purgatory
- governance
- adoption
- decision rights
- ROI
- data ownership
- incentive alignment
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