The Avatar Advantage: AI-Powered Faculty Development to Enhance Feedback Delivery Skills

Background: Feedback is fundamental to health professions education and essential for workplace-based assessment. Unfortunately, most educators lack formal training and access to evidence-based programs that incorporate experiential learning and real-time interactions. Objective: This study investigates the extent to which feedback delivery ratings provided by artificial intelligence (AI)-powered avatars are considered acceptable and reliable in comparison with feedback delivery ratings created by faculty participants and peer observers. Methods: After an interactive lecture on high-quality feedback, participants worked in small, facilitated four-person groups to deliver feedback in structured scenarios using AI-powered avatars. After each scenario, participants, peers, and the avatar independently rated feedback delivery using the DOCS-FBS scale (1–3; 1 = not done, 3 = successfully done). Scenario complexity was assessed with a nine-item scale (1–4; 4 = most complex). Multisource feedback ratings, postsession surveys, and group debrief data were analyzed with descriptive statistics, paired-sample t tests, and analysis of variance. Results: Participants rated session quality as very good (38%) or excellent (62%). Most found avatar-based feedback practice very or extremely effective (82%) and expressed strong interest in future avatar training (80%) and postworkshop access (74%). Participants reported high engagement and valued detailed rationales from the avatar. Peer observer ratings (2.82 ± 0.08) were significantly higher than both self-ratings (2.53 ± 0.39, P < .001) and avatar ratings (2.62 ± 0.32, P < .001). No differences emerged between self and avatar feedback delivery ratings. Conclusions: Using AI-powered avatars in feedback training sessions provide reliable feedback delivery ratings, are well received by participants, and can serve as a pragmatic solution for those leading professional development efforts.