The Jefferies research report, based on analysis of 42 expert call transcripts from the past 90 days (identities kept anonymous), examines AI adoption across pharmaceutical services companies.
AI delivers efficiency gains that vary by development stage: early discovery and regulatory writing see cost savings of approximately 40%‑50%; preclinical workflows at contract research organizations (CROs) and contract development and manufacturing organizations (CDMOs) achieve time reductions of about 40%‑50%; later‑stage clinical trials realize more modest savings of roughly 10%‑20% due to continued human validation requirements.
Specific AI applications generate notable improvements: request‑for‑information (RFI) automation reduces turnaround from roughly three days to ten minutes; data management and biostatistics automation cuts programming hours by about 30% during trial setup; synthetic cohorts could potentially halve patient enrollment in certain trials and lower overall trial costs by more than 30%.
AI creates margin benefits for CROs by lowering labor costs, but competitive pressures cause companies to pass a portion of these savings to clients. Experts estimate that, on average, about 50% of AI‑driven savings are retained, with some competitors passing larger portions to secure business.
CROs are leveraging AI to expand capacity and pursue additional programs, especially with mid‑size and small‑cap clients.
Workforce impacts include expected reductions of 10%‑20% in junior positions and overall workforce reductions of 10%‑15% over time, while experienced employees remain essential to validate AI outputs.
Contracting dynamics are shifting: roughly 50% of contracts are moving toward milestone‑based or value‑based models, moving away from traditional fee‑per‑employee or hourly pricing structures toward outcome‑based frameworks with greater risk‑sharing.
