About this episode

Dr Andree Bates discusses the AI capability problem in pharma, emphasizing the need for role-specific training to maintain AI effectiveness within organizations.

In this solo episode of AI For Pharma Growth, Dr Andree Bates explores the AI capability problem pharma has not properly named: training that works in the room, but fails to hold inside the organisation. Dr Andree explains why one-off workshops, generic AI fluency programmes and broad learning platforms are not enough. They may teach people what AI is, what it can do and where it can fail, but they rarely teach the exact workflows, judgement calls and regulatory context people need for their own roles. The episode looks at why AI capability fades over time. Some people leave training and build valuable new workflows, while others forget how to apply what they learned within weeks or months. In pharma, that matters because many AI use cases depend on cognitive, accuracy-based judgement: deciding whether a generated summary faithfully represents a source, whether a claim is substantiated, or whether an output can safely enter a regulated workflow. Dr Andree also explains why generic training can create risk. If usage rises faster than judgement, teams may become more confident with AI without becoming more capable in the workflows where mistakes carry regulatory, compliance or…

People in this episode

Host: Dr Andree Bates

Topics covered

• AI capability in pharma
• training effectiveness
• regulatory context
• workflow application
• judgement in AI use
• role-specific training

Keywords

• AI training
• pharma
• capability problem
• workflows
• regulatory compliance
• judgement calls
• generic training

More episodes of AI For Pharma Growth

• E234: The contrarian case for physics over data: can deterministic, training-free models beat ML in lead optimization? · September 8, 2026 · 44 min
• E232: The Early Readout: Upgrading the Interim Analysis to Catch Futility and Success Years Sooner · August 25, 2026 · 28 min
• E231: The Diagnostic Room: You didn't have an AI problem. You had a capability problem. · August 18, 2026 · 37 min
• E230: The Last Untouched Dataset · August 11, 2026 · 24 min
• E229: From Reactive to Proactive: What a QP's Job Should Actually Look Like in 2026 · August 4, 2026 · 33 min
• E228: The Diagnostic Room: "We're Doing AI" Is Not a Board Answer · July 28, 2026 · 40 min

Explore listener stats, chart rankings, contacts and more on the AI For Pharma Growth podcast page.