--- title: "AI in the Dental Practice: Uses, Evidence and Risks" description: "AI in dentistry for practice owners: common uses, what peer-reviewed studies show, FDA device categories and HIPAA questions to ask before you adopt it." url: https://joncopeland.multisites.ai/guides/ai-in-the-dental-practice publisher: Copeland Consulting Services email: drcopeland@joncopelanddds.com contact: https://joncopeland.multisites.ai/contact --- # AI in the dental practice: what it does, what studies show and what to check AI in dentistry mostly means software that reads images or handles office tasks. Studies of radiograph tools show promising accuracy but often rest on weak designs. Some image tools are regulated by the FDA as prescription devices. Any tool that touches patient data raises HIPAA questions you should settle before use. GuideUpdated October 26, 20269 min read 1. 1 ## Two broad uses Image analysis for diagnosis and office support such as notes, scheduling and billing. They carry different evidence and different rules. 2. 2 ## Evidence is promising, not settled A 2024 meta-analysis of caries detection on bitewing radiographs found that most included studies had unclear or high risk of bias. 3. 3 ## Some tools are devices Federal rules classify radiograph caries detection software as a prescription medical image analyzer. Ask any seller about its regulatory status. 4. 4 ## Patient data comes first If a vendor handles patient information for you, HIPAA treats it as a business associate. A written agreement is needed before you share data. Artificial intelligence is now part of the dental conversation, and many owners are asked about it before they have a way to judge it. This guide explains what the term covers, what peer-reviewed studies show, how federal rules treat some of the tools, and what privacy questions to settle first. It is general education from Copeland Consulting Services. It names no products and gives no clinical advice. It belongs to the wider [dental technology guide](https://joncopeland.multisites.ai/guides/dental-technology). ## What does AI mean in dentistry? In dentistry, [artificial intelligence](https://joncopeland.multisites.ai/glossary/artificial-intelligence-in-dentistry) usually means software that finds patterns in data and produces a result, such as a marked area on an image or a draft of a note. A 2023 review in _Frontiers in Dental Medicine_ defines AI as “the ability of machines to perform tasks that normally require human intelligence.” The same authors say the field became practical only in the past two decades, helped by more data, more computing power and better algorithms. The ADA draws one more line that is worth knowing. In its news report on a standards white paper, it separates artificial intelligence from augmented intelligence. Artificial intelligence refers to intelligence shown by machines rather than humans. Augmented intelligence keeps elements of human intelligence in the process and acts as a tool that helps the clinician do the task. Many dental products are described the second way: the software points, and the dentist decides. ## What are the main uses of AI in a dental practice? Uses fall into two groups with different evidence and different rules: clinical uses that look at images and data, and office uses that handle words and tasks. The ADA news report lists these uses, based on comments from the chair of its Council on Dental Practice: Use Plain description Type Imaging and diagnosis Software that analyzes radiographs and intraoral scans to help a dentist find and diagnose disease Clinical Treatment planning Software that reviews patient data and past outcomes to inform options Clinical Robotics and automation Systems being explored for repeated tasks Clinical Virtual and augmented reality Tools for patient education and for showing treatment Clinical and education Data analysis and prediction Software that looks for patterns in large sets of records Clinical and business Administrative support Virtual assistants for scheduling, patient messages and billing Office Another category that owners ask about is the [AI dental scribe](https://joncopeland.multisites.ai/glossary/ai-dental-scribe), software that listens to a visit and drafts a note. It fits the “administrative support” idea. This guide found no peer-reviewed summary of scribe accuracy among its sources, so it makes no accuracy claim about them. Ask the seller for independent evidence. A second review, in _Medical Science Monitor_ in 2025, adds that AI has been studied in endodontics, periodontics, implantology, orthodontics, prosthodontics and oral and maxillofacial surgery. Research is wide. Daily use in most offices is narrower. ## Where is the research strongest? Research is strongest for tasks that look at images. The _Frontiers_ review says “the majority of the AI applications in dentistry are for diagnosis based on radiographic or optical images.” It explains that other tasks are harder to study “mainly due to the constraints of data availability, data uniformity, and computational power for handling 3D data.” This matters for buyers. If a seller claims a result for a task outside image analysis, ask what study supports it, because far fewer studies exist. ## What does a meta-analysis of caries detection show? One of the most studied tasks is finding caries on bitewing radiographs. A 2024 systematic review and meta-analysis in the _Japanese Dental Science Review_ screened publications from after 2010. Fourteen of 935 references met its criteria. Its main findings, as reported in the abstract: - Dataset sizes ranged from 112 to 3,686 radiographs. - 86 percent of the studies reported a model with an accuracy of 80 percent or more. - Most studies had an unclear or high risk of bias. - Three studies compared the model with dentists, and the models showed higher average sensitivity. - Five studies were pooled. The summary sensitivity was 0.87 and the summary specificity was 0.89. - For lesions in dentin, sensitivity was 0.84. For lesions in enamel, it was 0.71. Sensitivity is the share of true cases the tool finds. Specificity is the share of healthy sites it correctly leaves alone. A tool with good numbers can still be wrong for a given patient. The authors conclude that, despite the promising results, “the lack of high-quality, adequately reported, and externally validated studies highlight current challenges and future research needs.” External validation means testing a model on images it did not learn from, often from different clinics and machines. Without it, you cannot assume the result will hold in your office. For a reader, the practical message has three parts. Results are encouraging. Study quality is uneven. The enamel result is weaker than the dentin result, which shows that performance changes with the task. ## What limits and risks do the reviews name? The 2025 narrative review in _Medical Science Monitor_ lists challenges in plain terms: “inaccurate data annotation, limited capability for fine-grained feature expression, a lack of universally applicable models, potential biases in learning algorithms, and legal risks pertaining to medical malpractice and data privacy breaches.” Put simply: - **Training data can be wrong.** If the labels used to teach a model are inaccurate, the model learns the errors. - **Models may not travel.** A model built in one setting may not fit patients, machines or image styles in another. - **Bias is possible.** If the training set under-represents some groups, the tool may do worse for them. - **Legal and privacy risk is real.** The authors name malpractice and data privacy breaches. The ADA’s commentary adds the human side. Its council chair is quoted: “While the integration of AI and augmented intelligence in dentistry is progressing, it’s important to note that human expertise and clinical judgment remain essential.” The report also lists patient safety, data privacy and ethics, including transparency, informed consent and bias, as reasons standards are needed. ## How does the FDA treat dental AI? Some AI products are regulated as medical devices, and some are not. The rule depends on what the software is for. Federal regulation 21 CFR 892.2070 addresses medical image analyzers. It says these devices, “including computer-assisted/aided detection (CADe) devices for mammography breast cancer, ultrasound breast lesions, radiograph lung nodules, and radiograph dental caries detection,” are “a prescription device.” They are meant to direct the clinician’s attention to parts of a radiology image that may show abnormalities. In plain terms, software that flags possible caries on dental radiographs is a named example in this regulation. The regulation describes the device as an aid to the clinician reading the image. The FDA also keeps a public list of AI-enabled medical devices, with links to its database entries. It warns that the list “is not a comprehensive resource of AI-enabled medical devices,” because it was built mainly from AI-related terms in the summary documents. So the absence of a product from the list is not proof that it lacks clearance, and the presence of a product tells you only what it was cleared to do. Use this table when a seller says a product is “FDA cleared.” Question Why it matters What exact use did the FDA clear? A clearance for one image type or age group does not extend to others. What is the submission or database number? You can look up the FDA record yourself. Is this the version I will use? Software changes. Ask how updates are handled and reviewed. What does the tool say it is not for? Read the labeling for limits and for how the dentist is expected to use the output. Is this an image tool or an office tool? A scheduling or note tool is not an image analyzer. Ask the seller to state its regulatory status in writing. A statement from a seller is not legal advice. Ask your attorney how the product’s status affects your duties. ## What are the HIPAA risks? Any AI tool that sees patient information raises privacy questions. The first is whether the vendor is a business associate. HHS explains that a covered entity may disclose protected health information to a business associate “if the covered entity obtains satisfactory assurances, in the form of a contract or other written arrangement” (a [business associate agreement](https://joncopeland.multisites.ai/glossary/business-associate-agreement)) that the associate will safeguard the information. For cloud-based tools, HHS says that when a covered entity uses a cloud provider to “create, receive, maintain, or transmit ePHI,” the provider “is a business associate under HIPAA,” and the parties must sign a HIPAA-compliant agreement. Many AI tools run in the cloud. The [HIPAA Security Rule](https://joncopeland.multisites.ai/glossary/hipaa-security-rule) and your own [cybersecurity](https://joncopeland.multisites.ai/glossary/cybersecurity) practices still apply. If a vendor will not sign an agreement, do not send it patient information. Questions to ask any AI vendor that touches patient data: 1. Will you sign a business associate agreement? 2. What patient data goes to your system, and what stays in our office? 3. Do you keep our data? For how long? Where? 4. Do you use our data to train or improve your models? Can we opt out? 5. Who at your company can see our patient information? 6. What is your process if there is a [data breach](https://joncopeland.multisites.ai/glossary/data-breach), and how fast will we hear about it? 7. Can we get our data back, and is it deleted when we leave? The last two matter more than they seem. Settle them before you sign, not after. Do not paste patient details into a general-purpose chat tool that has no agreement with your practice. If your team might do this on its own, put a clear written policy in your handbook. Your attorney or a compliance adviser should check the policy and the contract terms. ## How should a practice try an AI tool? A short, controlled trial is a safer first step than a full rollout. Try this plan: 1. **Pick one question.** For example, “Does this tool change how often our providers agree on bitewing findings?” or “Does it shorten the time to finish notes?” 2. **Take a “before” measure.** Time the current process or count the current disagreements. 3. **Keep the dentist in charge.** Every finding is reviewed, and every clinical decision belongs to a licensed dentist. 4. **Tell patients when it matters.** The ADA report names transparency and [informed consent](https://joncopeland.multisites.ai/glossary/informed-consent) among the ethical questions in AI. Ask your attorney how to describe AI use in your forms and in the room. 5. **Log what happens.** Note what the tool flagged and what the dentist decided. Write down the cases where the tool was wrong. 6. **Set a review date.** After the trial, compare the result with the “before” measure and decide whether to stop, adjust or widen use. The same cost and training questions that apply to any purchase apply here too. See the guide on [dental technology ROI](https://joncopeland.multisites.ai/guides/dental-technology-roi) for a way to count the costs. ## What should a dental team lead remember? Four points hold across the sources: - **AI is a support tool.** The ADA and the reviewed articles describe it as help for clinicians. - **Evidence is uneven.** Image tasks have the most research, and even those studies often carry a risk of bias. - **Regulation depends on use.** Some tools are prescription devices. Ask for the specific clearance. - **Privacy comes first.** Settle the agreement before you share any patient data. Standards are also changing. The ADA says it is working on a technical report and a standard for image analysis systems and on the U.S. position for an international standard. Check the ADA’s technology pages again before you decide. ## Next step For the wider topic, read the [dental technology pillar guide](https://joncopeland.multisites.ai/guides/dental-technology), and see the [technology page](https://joncopeland.multisites.ai/technology). To raise a question with Dr. Jon Copeland, DDS, a general dentist in Wildwood, Missouri, [contact Dr. Copeland about consulting](https://joncopeland.multisites.ai/contact?topic=consulting). ## Frequently asked questions ### Is AI going to take over dentistry? The sources reviewed here describe AI as a tool to assist clinicians, not replace them. The ADA quotes its council chair: "human expertise and clinical judgment remain essential." Published reviews also list real limits, such as data quality, bias and legal risk. Read AI as support for a dentist's decision, not a substitute for it. ### What are the main uses of AI in a dental office? The ADA lists imaging and diagnosis, treatment planning, robotics, virtual and augmented reality, data analysis and administrative support. Image-based diagnosis has the most published research. Administrative uses, such as scheduling, patient messages and notes, have less peer-reviewed evidence but raise the same privacy questions. ### Is AI for reading dental X-rays accurate? Results look promising but vary. One 2024 meta-analysis pooled five studies and reported a summary sensitivity of 0.87 and specificity of 0.89 for caries on bitewing radiographs. The same review found that most studies had unclear or high risk of bias and few were externally validated. Accuracy in your office may differ. ### Does the FDA regulate dental AI software? Some of it. Federal regulation 21 CFR 892.2070 covers medical image analyzers, including radiograph dental caries detection, as prescription devices. Not every AI tool is a device. Ask each seller whether its product is cleared by the FDA, what its cleared use is, and have your attorney confirm what that means for you. ### Is it a HIPAA problem to put patient information into an AI tool? It can be. HHS says a covered entity may disclose protected health information to a business associate only with satisfactory assurances, usually a written agreement. If an AI vendor handles patient data for you, ask for a business associate agreement first. Your attorney or compliance adviser should review the terms. ### How should a practice test an AI tool before adopting it? Use a limited trial with a clear question, such as whether the tool changes how often providers agree on a finding. Keep a dentist in charge of every clinical decision. Record what the tool flagged and what the dentist decided. Review the record after a set period before you expand use. ## Terms on this page - [Business associate agreement](https://joncopeland.multisites.ai/glossary/business-associate-agreement) - [HIPAA Security Rule](https://joncopeland.multisites.ai/glossary/hipaa-security-rule) - [AI dental scribe](https://joncopeland.multisites.ai/glossary/ai-dental-scribe) - [Informed consent](https://joncopeland.multisites.ai/glossary/informed-consent) - [Cybersecurity](https://joncopeland.multisites.ai/glossary/cybersecurity) - [Data breach](https://joncopeland.multisites.ai/glossary/data-breach) - [Dental team](https://joncopeland.multisites.ai/glossary/dental-team) - [ADA](https://joncopeland.multisites.ai/glossary/ada) ## Sources 1. [ADA News: Artificial intelligence and dentistry](https://adanews.ada.org/ada-news/2023/june/artificial-intelligence-and-dentistry/) 2. [Medical Science Monitor (via PMC): Artificial Intelligence in Dentistry: A Narrative Review of Diagnostic and Therapeutic Applications](https://pmc.ncbi.nlm.nih.gov/articles/PMC11992950/) 3. [Frontiers in Dental Medicine (via PMC): Artificial intelligence in dentistry, a review](https://pmc.ncbi.nlm.nih.gov/articles/PMC11811754/) 4. [Journal of Dental Sciences Review (via PMC): Diagnostic performance of artificial intelligence-aided caries detection on bitewing radiographs: a systematic review and meta-analysis](https://pmc.ncbi.nlm.nih.gov/articles/PMC10917640/) 5. [eCFR: 21 CFR 892.2070, Medical image analyzer](https://www.ecfr.gov/current/title-21/chapter-I/subchapter-H/part-892/subpart-B/section-892.2070) 6. [U.S. Food and Drug Administration: Artificial Intelligence-Enabled Medical Devices](https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices) 7. [HHS Office for Civil Rights: Business Associates Frequently Asked Questions (FAQs)](https://www.hhs.gov/hipaa/for-professionals/privacy/guidance/business-associates/index.html) 8. [HHS Office for Civil Rights: Guidance on HIPAA & Cloud Computing](https://www.hhs.gov/hipaa/for-professionals/special-topics/health-information-technology/cloud-computing/index.html) Written by Copeland Consulting Services and checked against the sources above on October 26, 2026. Rules, data and guidance change, so check the linked page before you act on it. ## Keep reading - [Dental technology: digital dentistry, AI, how to judge a purchase and what the implant literature showsDental technology covers digital impressions, imaging, CAD/CAM, 3D printing, practice software and AI. Sound decisions rest on published evidence, not brochures. Review the study design, ask what the tool changes in daily work, count the full cost, and check patient data duties before you buy.](https://joncopeland.multisites.ai/guides/dental-technology) - [Dental technology ROI: how to evaluate a purchase before you signTo evaluate a dental technology purchase, name the problem it solves, list every cost beyond the price, check what independent studies say, plan training and workflow changes, then set a review date with measures chosen before you buy. A return figure is only as good as the inputs you can verify.](https://joncopeland.multisites.ai/guides/dental-technology-roi) - [AI and dental x-rays: what the evidence shows so farTwo peer-reviewed reviews report promising AI results for finding caries, periapical lesions and bone loss on dental radiographs. They also say most results come from experimental settings and note problems with data labeling, bias, and models that underperform on new data. The evidence supports AI as an aid to the clinician.](https://joncopeland.multisites.ai/blog/ai-dental-radiographs-evidence) - [AI in dentistry: what the research says so farTwo peer-reviewed reviews find that most dental AI work is image-based diagnosis, with promising results in experimental settings and open problems in data quality, bias, generalization, privacy and liability. The ADA describes AI as a tool that aids clinicians, and says human judgment stays essential. Standards are still being written.](https://joncopeland.multisites.ai/blog/ai-in-dentistry-research) - [Dental case acceptance: what the research, the ADA Code and vendors sayCase acceptance is the share of presented treatment plans that patients schedule or complete. Research on patient decisions points to cost, fear and communication. The ADA Code requires dentists to inform patients of proposed treatment and reasonable alternatives. A higher rate is not an ethical goal by itself, and vendor benchmarks use different formulas.](https://joncopeland.multisites.ai/guides/dental-case-acceptance-guide) - [Dental leadership: team skills, training programs and where to learn themDental leadership is the work of guiding a dental team, a practice or a part of the profession. Core skills include clear communication, delegation, feedback and hiring. Learn them through team routines, mentors, organized dentistry such as the ADA and state societies, and formal programs like the ADEA Leadership Institute.](https://joncopeland.multisites.ai/guides/dental-leadership) ## Talk with Dr. Copeland [Contact Dr. Copeland](https://joncopeland.multisites.ai/contact)[Email](mailto:drcopeland@joncopelanddds.com)