Recruitment is often the most time-consuming and expensive step of clinical trials. As such, it is the most common stage for AI implementation, due to its power to hasten timelines, reduce costs and workloads, and potentially increase the representativeness of study cohorts. Yet, formal regulatory guidance on the use and ethics of AI specifically for clinical trial recruitment is limited, and best practices have yet to be defined. Here, we discuss the use of AI in the trial recruitment process across five domains, synthesize the ethical elements that apply to AI recruitment, and advance a framework of considerations and recommendations across use cases and ethical elements. The ethical elements, tensions, and recommendations discussed here will help inform the practices of and oversight by investigators, commercial recruitment entities, contract research organizations, sponsors, regulators, and IRBs as they develop, test, use, and evaluate AI models for clinical trial recruitment.
Rentzepis et al. (2026) studied this question.