Dental schools are adding artificial intelligence to teaching, but the evidence base is thin: a 2025 scoping review found only 17 studies of AI in dental education, and four of them were randomized. The FDI World Dental Federation, which represents national dental associations worldwide, asks dental professionals to acquire basic AI literacy, to appraise the evidence behind each tool, and to keep responsibility for every diagnosis with the human user.
Key takeaways
- A 2025 scoping review in Dentistry Journal included 17 studies published from 2022 to 2025, and only four used a randomized design.
- The FDI policy statement on AI in dentistry places responsibility for any AI-assisted diagnosis or treatment decision with the human user.
- The FDI policy on basic dental education, revised in 2026, lists AI literacy and data privacy as graduate competencies.
- The American Dental Association publishes a white paper, a technical report, and a standard on AI, aimed at image analysis systems and their validation.
- No study in the scoping review tested real-time AI feedback on operative procedures such as cavity preparation.
What the research on AI in dental teaching covers
A scoping review in Dentistry Journal (2025, volume 13, article 384) screened 497 records and kept 17 studies on AI in dental education. Ten of them dealt with clinical, diagnostic, and radiographic training, such as chatbots and image-analysis tools that help students spot patterns on radiographs. Three examined assessment and feedback, two covered preclinical practice, and two covered AI-generated cases, quizzes, and modules.
Results were mixed. In one trial students trained with AI improved at caries detection, while another found no significant gain. A comparison of feedback found ChatGPT-4 comments rated clearer than a human tutor's, and a comparison of cases found that expert-written cases still scored significantly higher on an OSCE quality measure. The review rated the risk of bias as low in three studies, moderate in 13, and high in one.
Evidence quality: what the numbers allow
| Feature of the 17 studies | Reported count | What it limits |
|---|---|---|
| Randomized design | 4 of 17 | Most findings come from observation or small pilots |
| Largest sample | 194 students | Several trials had 13 to 74 participants |
| Single-institution studies | At least 6 | Results may not transfer to other schools or curricula |
| Risk of bias (reviewers' rating) | 3 low, 13 moderate, 1 high | Confidence in any single result is moderate at best |
| Real-time AI feedback on operative work | None found | Hands-on skills remain untested |
The authors also point to inconsistent definitions of AI, since some studies counted virtual reality as AI, and to tools built mostly by computer scientists rather than dental educators. These are the reasons the findings read as early signals rather than settled results. The full text is open access at the the free archive of the US National Library of Medicine record.
What professional bodies ask of dental schools and dentists
The FDI policy statement on artificial intelligence in dentistry, prepared for adoption at its General Assembly in Istanbul in September 2024, names the risk that educators have to address: automation bias, meaning over-reliance on a tool's output. It also notes that options to measure an AI tool's performance on standardized datasets with comparable metrics are currently lacking. For educators, it recommends using a core curriculum on AI for dental professionals to shape undergraduate and postgraduate programs. That curriculum was published by Schwendicke and colleagues in the Journal of Dentistry in 2023.
A second FDI document, the revised policy statement on basic dental education adopted in Prague in 2026, names the rapid development of AI as one reason for updating the approach. It expects graduates to demonstrate digital and AI literacy, to assess emerging technologies critically, and to treat data privacy and cybersecurity as a core digital competency. The AI policy statement is available as a PDF from FDI.
Standards that dental AI tools are measured against
In the United States, the American Dental Association's standards program lists three AI documents. White Paper No. 1106 gives an overview of AI and augmented intelligence uses in dentistry. Technical Report No. 1109 covers image analysis systems that use AI. Standard No. 1110-1 sets guidance for validation datasets, specifically image annotation and data collection. These documents concern how tools are built and tested. They do not set learning outcomes for dental students.
Whether the accreditation standards that US and Canadian dental programs must meet contain AI-specific requirements could not be confirmed from the sources reviewed, so this article makes no claim either way.
Questions a dental program can ask about an AI teaching tool
- Was the tool tested on students in a comparison group, and how many took part?
- Does the evidence cover the skill being taught, such as diagnosis, case design, or hand skills?
- Who is accountable if the tool gives a wrong answer, and does the course say so?
- Where do patient images and student data go, and who can see them?
- Does the course still assess unaided performance?
This is general information about education and research. It is not dental, medical, or legal advice, and it says nothing about care for any individual patient.
FAQ
Is AI already part of the dental curriculum?
Some schools use it in specific courses, and the scoping review found studies from several institutions. The same review states that systematic integration into curricula remains underdeveloped, so practice varies from school to school.
Can AI replace faculty feedback in preclinical training?
The evidence does not show that. The review found that AI struggles to assess dexterity and clinical judgment, and no study tested real-time AI feedback on operative procedures. Reported gains are mostly in narrow tasks such as written feedback or radiograph pattern recognition.
Who is responsible when an AI tool is wrong?
The FDI policy statement says the responsibility for any diagnosis or treatment deduced from AI assistance remains with the human user. Students are therefore taught to treat output as a second opinion, not as an answer.
Do the ADA documents tell schools how to teach AI?
No. The white paper, technical report, and standard on the ADA standards page concern AI tools, their image data, and validation. Teaching content is addressed in FDI policy and in the published core curriculum.
Related reading
- Impact and potential of AI in education
- Challenges and limitations of AI in education
- A review of current trends in AI in education
- AI in orthodontics and dental care
More in AI in health.
Last verified: October 2026
Sources
- Artificial Intelligence in Dental Education: A Scoping Review of Applications, Challenges, and Gaps, Dentistry Journal 13(9), 384, 2025
- FDI Policy Statement: Artificial intelligence in dentistry, FDI World Dental Federation, prepared for the General Assembly of September 2024
- FDI Policy Statement: Basic Dental Education, revised version, FDI World Dental Federation, 2026
- Artificial intelligence for oral and dental healthcare: Core education curriculum, Schwendicke F et al., Journal of Dentistry 128:104363, 2023
- Artificial and Augmented Intelligence, ADA Standards (White Paper 1106, Technical Report 1109, Standard 1110-1), American Dental Association