Perception and Challenges of Using Artificial Intelligence (AI) in Post Graduate Medical Education in Dar Es Salaam, Tanzania

Abstract Background Artificial intelligence (AI) is increasingly being integrated into healthcare and medical education, offering opportunities to enhance learning, teaching, and clinical decision-making. While AI has demonstrated considerable potential in medical training, evidence regarding its use in postgraduate medical education in low- and middle-income countries remains limited. This study explored the perceptions and challenges associated with AI use among postgraduate medical residents and faculty members in Tanzania and identified educational needs for its effective integration into training programs. Methods A descriptive qualitative study was conducted among postgraduate medical residents and faculty members from three universities offering postgraduate medical education in Dar es Salaam, Tanzania. Participants were purposively selected to ensure representation across specialties and levels of training. Data were collected through four focus group discussions with residents and thirteen key informant interviews with faculty members. Audio-recorded interviews were transcribed verbatim and analysed using conventional content analysis with the aid of MAXQDA version 24. The study was reported in accordance with the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines. Results A total of 40 participants (27 residents and 13 faculty members) were included. Five major themes emerged from the analysis: (1) AI as a supportive learning tool that enhances understanding and educational efficiency; (2) concerns that excessive reliance on AI may undermine clinical reasoning and academic integrity; (3) limitations in the accuracy, reliability, and contextual relevance of AI-generated information; (4) barriers to effective AI use within the local context; and (5) the need for structured institutional support to guide safe and effective AI use. Participants reported that AI improved learning efficiency, facilitated access to information, simplified complex concepts, and enhanced teaching productivity. However, concerns were raised regarding overdependence on AI, reduced critical thinking, fabricated references, inconsistent outputs, and limited applicability of AI-generated recommendations to the Tanzanian healthcare context. Financial constraints, limited local data, and lack of formal AI training were identified as important barriers to effective AI utilization. Conclusions AI is perceived as a valuable adjunct to postgraduate medical education in Tanzania, with the potential to enhance learning and teaching practices. However, concerns regarding overreliance, information reliability, contextual applicability, and inadequate institutional guidance remain significant barriers to its effective use. Structured training, institutional policies, and equitable access to reliable AI platforms are essential to support the responsible integration of AI into postgraduate medical education.