Closing the Confidence-to-Action Gap: A Practical Path for AI in Medical Affairs

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New industry research reveals a striking gap: 86% of Medical Affairs professionals believe AI will improve their function’s efficiency in the next two to three years, but only 20% describe their organization as leading edge. This gap between belief and action is structural: most teams are using AI as chatbots opened on demand for individual tasks, while the more comprehensive workflows that define Medical Affairs operations remain largely untouched.

Drawing on industry research, roundtable discussions, and recent conversations with Medical Affairs leaders, this session explores the specific hurdles slowing AI adoption and what workflow-integrated AI requires to move from operational tasks toward higher-stakes Medical Affairs work.

Learning Objectives

1. Describe the current state of AI adoption in Medical Affairs functions based on the 2026 industry benchmark survey, including organizational posture, deployed use cases, and the leading barriers reported by senior practitioners.
2. Differentiate chatbot-style AI tools used for individual productivity from workflow-integrated AI that operates as a deeper collaborative partner and defined step inside governed Medical Affairs processes, and recognize the operational implications of each model.
3. Apply a use case prioritization framework that evaluates AI leverage against compliance friction to identify which Medical Affairs workflows are most viable for near-term AI deployment.
4. Evaluate their own organization’s validation, governance, and team readiness posture against industry benchmarks and identify two to three actions to advance AI maturity over the next 12 months, including review models, source-verification expectations, and capability-building for effective human oversight.

Speakers: