Leading AI in R&D: From Scientific Ambition to Accountable Innovation

How can R&D leaders turn AI’s potential into better science, stronger organisations and meaningful outcomes for patients? Drawing on experience leading global pharmaceutical R&D, Mikael Dolsten explores the leadership decisions needed to make this transformation work.

Connecting with the CLAIR Research Agenda’s focus on leadership, governance and organisational transformation, this keynote examines practical examples of setting priorities, bringing scientific and technical expertise together, and creating conditions for responsible experimentation. It considers how leaders can establish clear accountability, preserve critical scientific judgement and decide when AI applications are ready to move beyond pilots.

Examples and lessons would illustrate potential building blocks for a practical Leadership Framework for AI in R&D: explicit decision rights, evidence requirements, multidisciplinary ownership, and measures of scientific and organisational value. The keynote invites participants to consider which practices can transfer across organisations, what requires adaptation, and how leadership experience can inform a framework for evaluation and continuous improvement.