Death of expertise in the dawn of AI has been vastly overreported with no sign of its ability to displace creative and disciplined drug discovery teams. Citing Bernstein Research, the Financial Times notes: “from 2012 to 2022, adjusting for inflation, spending on pharmaceutical research and development increased by almost half to roughly $250bn, yet the number of novel drug approvals remained broadly flat.” AI holds the promise in shaping and hastening scientific discovery by winnowing therapeutic targets, sorting through large datasets, and flagging areas where assumptions need to be challenged. This panel will explore how AI and ML serve as force multipliers, especially for biotech’s with big ideas and small dedicated teams. The discussion will be a deep dive into how to position AI within a drug discovery team and create guidelines and guardrails for its adoption for maximum effect. Built on a working familiarity with what AI excels at now, this session will challenge assumptions about where it can go next – exploring a theoretical ceiling and practical utility in drug discovery.