As generative artificial intelligence tools such as chatbots and large language models become more common in healthcare and education, dental schools are beginning to explore how these technologies might support teaching and learning. At the same time, many educators are concerned about how to use such tools responsibly and how to protect academic integrity and patient privacy. A recent scoping review has taken stock of existing guidance from universities and international organisations and argues that dentistry‑specific frameworks are urgently needed.

The review analysed 31 guideline, policy or recommendation documents issued by 21 universities in 15 countries, as well as by several regional university associations and UNESCO. These documents described a range of possible uses for generative AI in education, including helping teachers design assignments, generating example questions or clinical scenarios, supporting students in summarising complex information and offering more personalised learning paths. Many guidelines emphasised that, when used thoughtfully, generative AI can promote critical thinking by giving students material to analyse and critique rather than to copy.

At the same time, the review underlined important limitations and risks. Generative AI systems produce text based on statistical patterns, not on clinical reasoning, and their answers may be convincing but factually incorrect. Over‑reliance on such tools can lead to “automation bias”, in which students accept AI output without sufficient critical appraisal. The documents also raised concerns about academic integrity, transparency about AI use in coursework, data privacy, intellectual property and the possibility that hidden biases in training data could be reflected in educational content. For dentistry in particular, questions arise about whether students should be allowed to submit patient radiographs or clinical data to external AI systems and how educators should incorporate AI‑generated cases into teaching.

The authors noted that, despite growing interest in AI, none of the guidelines they examined were specific to dental education. This confirms earlier surveys of dental educators who reported a lack of structured guidance on how to introduce AI into curricula. According to the review, dental schools will need to go beyond general university policies and define what is and is not acceptable in typical dental teaching situations. This may include setting clear rules on the use of generative AI for clinical simulations, case discussions and assessment tasks and clarifying how staff and students should handle sensitive patient information when using digital tools.

Looking ahead, the review suggests several steps for institutions that wish to integrate generative AI responsibly. These include developing explicit AI policies, offering training on AI literacy for both staff and students, investing in secure technical infrastructure and forming multidisciplinary committees to oversee AI‑related initiatives. Regular reviews of AI policies and open dialogue within faculties are seen as essential, since the technology and its applications are evolving quickly. The authors conclude that, if well regulated and paired with appropriate pedagogical changes, generative AI could become a useful complement to traditional teaching in dentistry, but only if students are trained to use such tools critically and in line with professional and ethical standards.