About this episode

Dr Andree Bates discusses the importance of AI capability in pharma teams and the need for proper training to use AI effectively.

In this solo episode of AI For Pharma Growth, Dr Andree Bates explores why many pharma teams do not have an AI problem at all. They have a capability problem. Dr Andree starts with a simple question: when was your team last properly trained on AI for their specific role? Not when they were given access to tools, licences or a generic use policy, but when they were trained to use AI effectively, safely and compliantly in their actual workflow. The episode challenges the usual explanations for disappointing AI results: the model was not good enough, the vendor was wrong, the data was not ready, or the organisation resisted change. In many cases, the tools work, the pilots are useful and the training lands. But the working knowledge needed to use AI well is uneven, fragile and decays over time. Dr Andree explains why this matters so much in pharma. High-value AI work is often judgement-led: medical information responses, payer materials, safety narratives, regulatory documents and MLR-compatible content. AI can support these tasks, but only when users can tell the difference between a strong draft and a merely plausible one. She also discusses the research behind skill decay…

People in this episode

Host: Dr Andree Bates

Topics covered

• AI in pharma
• capability problem
• training
• judgement-led tasks
• skill decay
• compliance
• patient safety

Keywords

• AI
• pharma
• training
• capability
• skill decay
• compliance
• judgement-led tasks

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