ADA highlights challenges in adoption of AI in dentistry

Dental Tribune International

Wed. 18. March 2026

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CHICAGO, US: Broad adoption of artificial intelligence-based (AI-based) tools by US dental clinics could significantly improve diagnostics, treatment planning and practice efficiency; however, substantial barriers exist. The American Dental Association (ADA) has outlined what it sees as the main challenges to AI adoption and innovation, as well as steps that could be taken to incentivise effective and wider use of the technology in clinical settings.

The ADA made the comments in a written response to a US Department of Health and Human Services (HHS) request for information on accelerating the adoption of AI in private sector care. The association stressed the need for validated datasets and independent evaluation frameworks to ensure that AI tools used in dentistry are safe, reliable and clinically effective. It explained that limited data standards and poor interoperability currently constrain the development and reliability of AI systems and identified the most significant barriers to adoption as:

the heterogeneity of electronic dental records in training datasets;
the inaccessibility and interoperability of dental data;
the limitations presented by dental claims data; and
the challenges related to data governance at scale.

Regarding the last point, the association explained that inconsistent data governance policies can create confusion over responsibility for clinician and patient consent, transparency, and privacy protections, thereby blurring liability and malpractice accountability. This has resulted in operational barriers for dental clinics, including high costs, workforce development constraints, and increased legal and operational risk.

According to the ADA, measures to incentivise the use of AI in dental clinics include strengthening the capture and reporting of dental data in federally funded programmes, boosting funding for technology infrastructure and establishing independent external validation of dental AI technologies. The association said that it is “committed to developing foundational standards for validating interoperability and AI tools”. This would include terminology standards to define the vocabulary used in dentistry, data structure and exchange standards to define how information is organised and shared, and content standards to define the data needed to support administrative functions and clinical care. Such measures, it added, would be essential for the generation of consistent, structured, high-quality datasets for reliable AI test data.

Furthermore, the ADA called for a standardised regulatory definition of “non-medical devices” as a category of health technology to reduce uncertainty related to privacy, cybersecurity and liability. The organisation also recommended stronger accountability from third-party technology vendors, on whom many dental practices rely for critical services and systems, such as electronic dental record management, imaging software and practice management tools. Alluding to regulatory gaps, the ADA recommended that HHS establish standardised labelling requirements for AI-based tools so that dentists and patients can better understand them, thereby improving trust, supporting adoption and strengthening shared decision-making.

Additionally, the ADA stated that policymakers and healthcare organisations must support the needs of smaller and rural dental offices to broaden the adoption of AI in clinical care. It explained that these practices often face challenges such as limited training opportunities, unclear liability frameworks and regulatory uncertainties, making the coordination of AI technologies a burden. The association noted that “many AI technologies do not integrate seamlessly with existing electronic health records, imaging systems or practice management platforms”, compounding these difficulties. To support both adoption and clinical research, the ADA also recommended that HHS establish a practice network offering a federated, multi-site platform for research, development and implementation to enable rigorous evaluation and deployment of AI tools in real-world clinical settings.

The submission forms part of the ADA’s wider push to shape how AI is developed and deployed in dentistry. Alongside its policy work, the association is advancing AI-driven innovation through the ADA Forsyth Institute, spanning a wide range of areas, including smart materials and data-driven oral health research. Together, these efforts point to a more structured, standards-led approach to integrating AI into everyday dental practice.

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American Dental Association Artificial intelligence Dental data Digital dentistry Electronic health records

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