Tabriz University of Medical Sciences Research and Development in Medical Education 2322-2719 14 1 2025 01 01 Blending human and AI-powered feedback models in medical education: A practical overview 33353 33353 10.34172/rdme.025.33353 EN Ehsan Toofaninejad https://orcid.org/0000-0001-6440-0992 Mahdieh Zangiabadizadeh Masomeh Kalantarion https://orcid.org/0000-0003-4778-3973 Saeed Latifi https://orcid.org/0000-0003-0420-7474 Journal Article 10.34172/rdme.025.33353 2025 07 01 2025 08 19 Effective feedback plays a pivotal role in medical education, bridging the gap between current and desired learner performance. This short communication outlines common types and models of feedback in clinical teaching and explores how artificial intelligence (AI) tools, such as ChatGPT, can complement traditional methods. While AI can offer immediate, data-driven insights, the irreplaceable human element brings contextual awareness and emotional intelligence to feedback processes. We present a practical categorization of feedback types and a comparative overview of ten well-established models. By integrating human expertise with AI-supported systems, educators can enhance formative assessment and foster autonomous, reflective learning. Practical implications are discussed for implementing feedback models in both in-person and digital learning environments.