In the face of rising R&D costs and complexity, the pharmaceutical industry has turned to generative artificial intelligence (AI) to help increase efficiency. However, early adoption of AI has revealed a critical flaw in the prevailing strategy. Rather than embedding intelligence, organizations often apply an AI “overlay” to fundamentally unchanged processes. This may save time on some specific tasks, but it does not properly address the growing productivity gap.
This paper proposes a fundamental shift from the overlaid AI model to the “Agentic Biopharma” model. This new operating model posits that the true bottleneck is no longer technology, but the workforce structure and the operating model itself. By shifting from static functional silos to dynamic human-agent teams, and evolving scientists from “doers” to “orchestrators,” R&D organizations can shorten discovery timelines by up to 50% while also reducing costs. Companies must move quickly because the window to establish a competitive advantage is narrowing, estimated at just 12-18 months before these new capabilities become “table stakes.”
Download the paper to read more about how to make this necessary transformation.
