AI in dentistry: what the research says so far

This post summarizes published research for general education by Copeland Consulting Services. It is not clinical, legal or purchasing advice.

What does AI mean in dentistry?

It means software that learns patterns from data and applies them to new cases. A 2023 review in Frontiers in Dental Medicine defines AI as “the ability of machines to perform tasks that normally require human intelligence.” Dental tools usually rely on machine learning, which learns from examples that people have labeled. The term artificial intelligence in dentistry covers those tools.

The ADA draws one more line. In ADA News, artificial intelligence refers to intelligence shown by machines. Augmented intelligence “retains elements of human intelligence” and acts as a tool that assists the clinician. The ADA white paper uses both terms.

Where is AI used in dentistry?

Mostly in image analysis. The 2023 review says most dental AI applications are for diagnosis from radiographic or optical images. Other tasks are harder because of limits in data availability, data uniformity and computing power for 3D data.

The 2025 review in Medical Science Monitor covers more ground. It examines endodontic disease, periodontal disease, implantology, orthodontics, prosthodontics, and oral and maxillofacial surgery. It reports uses across prevention, screening, diagnosis, treatment planning, follow-up and prognosis.

The ADA lists further areas. They include treatment planning software, robotics, virtual and augmented reality, predictive analytics, and administrative support such as scheduling and billing help. The ADA frames these as areas being developed and used, not as settled practice.

How well does it work?

Results look promising in studies, and the reviews are careful about what that means. The 2025 review says AI in dentistry “remains in its nascent stages, characterized by high precision in experimental settings,” while it “faces challenges in terms of clinical accuracy and reliability.” The 2023 review says some studies show AI with “the same accuracy or even better compared with dentists” in early lesion detection. It ties that result to close work between clinicians and computer scientists, who label the images and then check the output together.

Read both statements together. Accuracy in a study does not guarantee the same accuracy in your office. The table lists the limits that the reviews name.

Sources for the table are the 2025 review and the 2023 review.

Will AI replace dentists?

Neither review nor the ADA describes that outcome. The 2025 review says AI systems should “complement” and “enhance clinical decision-making without supplanting the nuanced judgment of experienced clinicians.” The ADA quotes the chair of its Council on Dental Practice: “human expertise and clinical judgment remain essential.”

The 2023 review calls AI “a supplemental tool” that may reduce workload and improve precision, if training data is unbiased and the algorithm is properly trained. The condition matters. It is a reason to ask any vendor how a tool was trained and tested.

What do the reviews say about specific clinical areas?

The 2025 review tells the story area by area. For caries, it says detection from images depends heavily on clinician experience, and that AI is increasingly used to improve detection and diagnosis from captured images. For periapical disease, it reports deep learning studies of lesion detection on radiographs. For periodontal disease, it reports models that measure bone levels and interpret panoramic images.

In implant dentistry, the review reports that AI helps with identifying implant types from radiographs and with presurgical digital planning. It calls AI algorithms “potent diagnostic tools” in this field.

The 2023 review sorts the evidence by discipline: operative dentistry, periodontics, orthodontics, oral and maxillofacial surgery and prosthodontics. In each, the studies it describes focus on images. Both reviews are narrative reviews. A narrative review summarizes the field but does not pool study results the way a meta-analysis does. Read their numbers as examples, not as a scorecard.

For detail on one area, see the post on AI and dental X-rays.

What role do standards play?

They set shared rules for safety, privacy and ethics. In 2023 the ADA said it was developing a technical report and standard for image analysis systems that use AI, and the U.S. position for an international standard. It listed reasons standards matter: patient safety, data privacy and security, ethical considerations such as transparency and bias, interoperability, and training.

Standards are still developing, so a team has to judge tools without a full rulebook. The ADA digital dentistry page lists its AI resources and white paper for that purpose.

Questions a practice can ask before adopting any AI tool

1. What data was the tool trained on, and does it resemble the practice’s patients?
2. Was it tested outside the group that built it?
3. Who reviews its output, and who decides what to do with it?
4. Where does patient data go, and does the vendor sign a business associate agreement?
5. How would a wrong result be caught?

See HIPAA for the privacy rules behind question 4. For a deeper look at tool types, see the post on AI scribes and the post on AI and dental X-rays.

Next step

The AI in the dental practice guide covers uses, evidence and risks in more depth. To discuss a related project, contact Dr. Copeland about consulting.