5 Key Takeaways

• 1

  Clinical trial complexity and siloed systems can increase administrative burden for site staff and contribute to burnout, missed enrollment targets, and protocol deviations.

• 2

  Embedded AI agents can support trial workflows by tracking consent and protocol updates, managing documents, scheduling visits, and flagging documentation gaps.

• 3

  AI may help sponsors assess protocol feasibility using real-world patient populations, historical enrollment patterns, and site performance data.

• 4

  AI applications across trial operations include patient recruitment and retention, image analysis, real-time data validation, and signal detection.

• 5

  The article describes one trial in which AI-assisted patient prescreening and visit scheduling were associated with fewer protocol deviations, better evaluability, and faster time to data lock.