{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T15:19:05Z","timestamp":1785424745748,"version":"3.56.0"},"reference-count":32,"publisher":"AOSIS","issue":"1","license":[{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Artificial intelligence (AI) presents a timely opportunity to modernise postgraduate medical education, which has remained largely unchanged despite rapid technological advancements. AI can streamline administrative tasks, personalise learning and support critical thinking, allowing educators to refocus on mentorship and bedside teaching. However, if used uncritically or introduced too early as a substitute for clinical reasoning, AI may contribute to the risk of \u2018never-skilling\u2019, where students fail to develop the foundational clinical skills and independent judgement needed for safe practice. Integrating AI and other digital tools into clinical environments fosters authentic, technology-enabled learning while promoting digital professionalism. A collaborative, environmentally conscious approach across disciplines and institutions is essential to ensure equitable, sustainable adoption. The thoughtful use of AI can transform postgraduate medical education into a more efficient, student-centred system, aligned with the realities of modern healthcare.<\/jats:p>","DOI":"10.4102\/jcmsa.v4i1.413","type":"journal-article","created":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T08:13:37Z","timestamp":1782375217000},"update-policy":"https:\/\/doi.org\/10.4102\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Reflection: AI as a catalyst for change in postgraduate medical education"],"prefix":"10.4102","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8769-3273","authenticated-orcid":false,"given":"Sumaiya","family":"Adam","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00g0p6g84","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Pretoria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7304-4424","authenticated-orcid":false,"given":"Vanessa","family":"Burch","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/037gpje79","id-type":"ROR","asserted-by":"publisher"}],"name":"Colleges of Medicine of South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2580","published-online":{"date-parts":[[2026,6,25]]},"reference":[{"key":"ref0","doi-asserted-by":"crossref","unstructured":"Toku\u00e7 B, Varol G. Medical education in the era of advancing technology. Balkan Med J. 2023;40(6):395\u2013399. https:\/\/doi.org\/10.4274\/balkanmedj.galenos.2023.2023-7-79","DOI":"10.4274\/balkanmedj.galenos.2023.2023-7-79"},{"key":"ref1","unstructured":"Mir MM, Mir GM, Raina NT, et al. Application of artificial intelligence in medical education: Current scenario and future perspectives. J Adv Med Educ Prof. 2023;11(3):133\u2013140. https:\/\/doi.org\/10.30476\/JAMP.2023.98655.1803"},{"key":"ref2","doi-asserted-by":"crossref","unstructured":"Zarei M, Mamaghani HE, Abbasi A, Hosseini MS. Application of artificial intelligence in medical education: A review of benefits, challenges, and solutions. Med Cl\u00edn Pr\u00e1ct. 2024;7(2):100422. https:\/\/doi.org\/10.1016\/j.mcpsp.2023.100422","DOI":"10.1016\/j.mcpsp.2023.100422"},{"key":"ref3","unstructured":"Reyna J. The potential of Google NotebookLM for teaching and learning. Presented at: eLearn 2025; 2025 Oct 13\u201316 [cited 2026 May 15]; Bangkok, Thailand. Available from: https:\/\/www.academia.edu\/143048105\/2025_The_Potential_of_Google_NotebookLM_for_Teaching_and_Learning."},{"key":"ref4","doi-asserted-by":"crossref","unstructured":"Sikri D, Nuguri V. From notes to networks \u2013 A three-dimensional framework with integrated curation for using Google NotebookLM in health professions education. Med Teach. 2025;18:1\u20135. https:\/\/doi.org\/10.1080\/0142159X.2025.2533408","DOI":"10.1080\/0142159X.2025.2533408"},{"key":"ref5","doi-asserted-by":"crossref","unstructured":"Park PS, Goldstein S, O\u2019Gara A, Chen M, Hendrycks D. AI deception: A survey of examples, risks, and potential solutions. Patterns (NY). 2024;5(5):100988. https:\/\/doi.org\/10.1016\/j.patter.2024.100988","DOI":"10.1016\/j.patter.2024.100988"},{"key":"ref6","doi-asserted-by":"crossref","unstructured":"Cross JL, Choma MA, Onofrey JA. Bias in medical AI: Implications for clinical decision-making. PLoS Digit Health. 2024;3(11):e0000651. https:\/\/doi.org\/10.1371\/journal.pdig.0000651","DOI":"10.1371\/journal.pdig.0000651"},{"key":"ref7","doi-asserted-by":"crossref","unstructured":"Teng D, Tan L, Cao Q, et al. Impact of AI misinformation on diagnostic accuracy and confidence calibration in novice medical students. NPJ Digit Med. 2026;9:356. https:\/\/doi.org\/10.1038\/s41746-026-02547-z","DOI":"10.1038\/s41746-026-02547-z"},{"key":"ref8","doi-asserted-by":"crossref","unstructured":"Norori N, Hu Q, Aellen FM, Faraci FD, Tzovara A. Addressing bias in big data and AI for health care: A call for open science. Patterns (NY). 2021;2(10):100347. https:\/\/doi.org\/10.1016\/j.patter.2021.100347","DOI":"10.1016\/j.patter.2021.100347"},{"key":"ref9","doi-asserted-by":"crossref","unstructured":"Kharitonova YS, Savina VS, Pagnini F. Artificial intelligence\u2019s algorithmic bias: Ethical and legal issues. Bulletin of Perm University Herald. Juridical Sciences. 2021;(53):488\u2013515. https:\/\/doi.org\/10.17072\/1995-4190-2021-53-488-515","DOI":"10.17072\/1995-4190-2021-53-488-515"},{"key":"ref10","doi-asserted-by":"crossref","unstructured":"Turney J, Young TM, Chauhan DR, Beeharry R, Mahmud M. AI use for medical students: Impact on clinical skill acquisition and retention. A systematic review. Adv Med Educ Pract. 2026;17:583763. https:\/\/doi.org\/10.2147\/AMEP.S583763","DOI":"10.2147\/AMEP.S583763"},{"key":"ref11","doi-asserted-by":"crossref","unstructured":"Zheng C, Zhang H. Ethical issues in medical AI education: Challenges and prospects. Int J Ethics Educ. 2026. https:\/\/doi.org\/10.1007\/s40889-026-00241-y","DOI":"10.1007\/s40889-026-00241-y"},{"key":"ref12","doi-asserted-by":"crossref","unstructured":"Garibaldi BT, Russell SW. Strategies to reinvigorate the bedside clinical encounter. N Engl J Med. 2025;393(21):2142\u20132150. https:\/\/doi.org\/10.1056\/NEJMra2500226","DOI":"10.1056\/NEJMra2500226"},{"key":"ref13","doi-asserted-by":"crossref","unstructured":"Ke Y, Jin L, Ong JCL, et al. AI-induced never-skilling in medical education. Nat Med. 2026. https:\/\/doi.org\/10.1038\/s41591-026-04438-y","DOI":"10.1038\/s41591-026-04438-y"},{"key":"ref14","doi-asserted-by":"crossref","unstructured":"Wosny M, Strasser LM, Hastings J. Experience of health care professionals using digital tools in the hospital: Qualitative systematic review. JMIR Hum Factors. 2023;10:e50357. https:\/\/doi.org\/10.2196\/50357","DOI":"10.2196\/50357"},{"key":"ref15","doi-asserted-by":"crossref","unstructured":"Fernandes Prabhu D, Gurupur V, Stone A, Trader E. Integrating artificial intelligence, electronic health records, and wearables for predictive, patient-centered decision support in healthcare. Healthcare. 2025;13(21):2753. https:\/\/doi.org\/10.3390\/healthcare13212753","DOI":"10.3390\/healthcare13212753"},{"key":"ref16","doi-asserted-by":"crossref","unstructured":"Patocka C, Pandya A, Brennan E, et al. The impact of just-in-time simulation training for healthcare professionals on learning and performance outcomes: A systematic review. Simul Healthc. 2024;19(1S):S32\u2013S40. https:\/\/doi.org\/10.1097\/SIH.0000000000000764","DOI":"10.1097\/SIH.0000000000000764"},{"key":"ref17","unstructured":"Riel M. Education in the 21st century: just-in-time learning or learning communities. Paper presented at the Fourth Annual Conference of the Emirates Center for Strategic Studies and Research; 1998 May 24\u201326. Abu Dhabi: Emirates Center for Strategic Studies and Research, 2000; p. 137\u2013160."},{"key":"ref18","doi-asserted-by":"crossref","unstructured":"Hennus MP, Ramani S, Van Dam M. Giving the patient a leading role in bedside teaching; a truly collaborative and inclusive effort. Med Teach. 2025;47(3):375\u2013376. https:\/\/doi.org\/10.1080\/0142159X.2024.2398761","DOI":"10.1080\/0142159X.2024.2398761"},{"key":"ref19","doi-asserted-by":"crossref","unstructured":"Parmar R, Eldawud D, Sharma N, Issa R, Budzikowski A. Preserving bedside teaching: An AI-supported system for capturing spontaneous clinical teaching. Med Teach. 2026:1\u20134. https:\/\/doi.org\/10.1080\/0142159X.2025.2604243","DOI":"10.1080\/0142159X.2025.2604243"},{"key":"ref20","doi-asserted-by":"crossref","unstructured":"Ravichandran L, Saravanan S. Revitalizing the bedside teaching: The enduring value of clinical teaching at the patient\u2019s side. Sri Ramachandra J Health Sci. 2025;5:1\u20132. https:\/\/doi.org\/10.25259\/SRJHS_9_2025","DOI":"10.25259\/SRJHS_9_2025"},{"key":"ref21","unstructured":"Wu CJ, Raghavendra R, Gupta U, Acun B, Ardalani N, Maeng K, et al. Sustainable AI: environmental implications, challenges and opportunities. arXiv [Preprint]. 2022 [cited 2026 May 15]. Available from: https:\/\/arxiv.org\/pdf\/2111.00364."},{"key":"ref22","doi-asserted-by":"crossref","unstructured":"Franco D\u2019Souza R, Mathew M, Mishra V, Surapaneni KM. Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education. Med Educ Online. 2024;29(1):2330250. https:\/\/doi.org\/10.1080\/10872981.2024.2330250","DOI":"10.1080\/10872981.2024.2330250"},{"key":"ref23","doi-asserted-by":"crossref","unstructured":"Hu L, Argus G, Pineda RC, MacAskill W, Martin P. The role of artificial intelligence in enhancing interprofessional education and collaborative practice: A mixed methods scoping review. J Interprof Care. 2026;40(2):390\u2013399. https:\/\/doi.org\/10.1080\/13561820.2025.2576241","DOI":"10.1080\/13561820.2025.2576241"},{"key":"ref24","doi-asserted-by":"crossref","unstructured":"Blumenthal D, Bennett K, McDonough J. Overcoming the digital divide in health care AI. N Engl J Med. 2026;394; 1876\u20131877. https:\/\/doi.org\/10.1056\/NEJMp2600816","DOI":"10.1056\/NEJMp2600816"},{"key":"ref25","doi-asserted-by":"crossref","unstructured":"Ajalo E, Mukunya D, Nantale R, et al. Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study. PLoS One. 2025;20(1):e0313776. https:\/\/doi.org\/10.1371\/journal.pone.0313776","DOI":"10.1371\/journal.pone.0313776"},{"key":"ref26","doi-asserted-by":"crossref","unstructured":"Nantale R, Kayemba F, Paungholi K, et al. Experiences of nursing and medical students with the use of Artificial Intelligence tools such as ChatGPT in Uganda. PLoS Glob Public Health. 2025;5(12):e0005715. https:\/\/doi.org\/10.1371\/journal.pgph.0005715","DOI":"10.1371\/journal.pgph.0005715"},{"key":"ref27","doi-asserted-by":"crossref","unstructured":"Mukunya D, Nantale R, Kayemba F, et al. Utilisation of ChatGPT and other Artificial Intelligence tools among medical faculty in Uganda: A cross-sectional study. MedEdPublish (2016). 2026;14:245. https:\/\/doi.org\/10.12688\/mep.20554.3","DOI":"10.12688\/mep.20554.3"},{"key":"ref28","doi-asserted-by":"crossref","unstructured":"Titus S. Implementing extended reality (XR) and artificial intelligence (AI) in health professions education in southern Africa. Afr J Health Prof Educ. 2024;16(2):e1101. https:\/\/doi.org\/10.7196\/AJHPE.2024.v16i2.1101","DOI":"10.7196\/AJHPE.2024.v16i2.1101"},{"key":"ref29","unstructured":"Grand Challenges. Transforming healthcare education: AI-powered access to clinical guidelines and standard operating procedures (SOPs) for health practitioners in Francophone Africa [homepage on the Internet]. Dakar, Senegal: Tech Care For All - Africa; 2024 [cited 2026 May 15]. Available from: https:\/\/gcgh.grandchallenges.org\/grant\/transforming-healthcare-education-ai-powered-access-clinical-guidelines-and-standard"},{"key":"ref30","doi-asserted-by":"crossref","unstructured":"Smith SM, Tate M, Freeman K, Walsh A, Ballsun-Stanton B, Lane M. A university framework for the responsible use of generative AI in research. J High Educ Policy Manag. 2026;48(1):17\u201336. https:\/\/doi.org\/10.1080\/1360080X.2025.2509187","DOI":"10.1080\/1360080X.2025.2509187"},{"key":"ref31","doi-asserted-by":"crossref","unstructured":"Funa AA, Gabay RAE. Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study. Soc Sci Humanit Open. 2025;11:101221. https:\/\/doi.org\/10.1016\/j.ssaho.2024.101221","DOI":"10.1016\/j.ssaho.2024.101221"}],"container-title":["Journal of the Colleges of Medicine of South Africa"],"original-title":[],"link":[{"URL":"https:\/\/jcmsa.org.za\/index.php\/jcmsa\/article\/view\/413\/1068","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T08:14:51Z","timestamp":1782375291000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcmsa.org.za\/index.php\/jcmsa\/article\/view\/413"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,25]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1,1]]}},"URL":"https:\/\/doi.org\/10.4102\/jcmsa.v4i1.413","relation":{},"ISSN":["3105-4331","2960-110X"],"issn-type":[{"value":"3105-4331","type":"print"},{"value":"2960-110X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,25]]},"article-number":"a413"}}