Understanding Agentic AI in Clinical Development From Automation to Autonomy: Part 1

Clinical development organizations are moving beyond traditional automation and generative AI toward systems that can plan, make decisions and execute actions within defined governance boundaries. Described as agentic AI, these capabilities are beginning to reshape how clinical teams manage data-intensive processes, coordinate work across functions and respond to changing operational conditions.

This white paper examines what agentic AI means in practice for the pharmaceutical industry. It clarifies the differences between AI assistants, AI agents and agentic AI, and explores where autonomous capabilities are most effective across clinical development. Drawing on examples from medical writing, enrollment intelligence, site activation and clinical data surveillance, the paper highlights both the opportunities and the operational realities organizations must address.

Gain a practical understanding of the governance, data foundations and organizational structures required to support autonomous systems in regulated environments. The paper also outlines common implementation challenges, including isolated pilot programs, oversight requirements and the need for traceability, helping clinical leaders evaluate where and how agentic AI can be applied with confidence.