From the 2026 Summer Journal of the Colorado Dental Association
By: David Geck, D.D.S., M.S.; Steven Michalek, Esq.; and Corinne Jozwick, Esq.
Dr. David Geck
Corinne Jozwick, Esq.
Steven Michalek, Esq.
While algorithm‑driven automation and machine learning have quietly supported dental practices for years, the integration of artificial intelligence into dental practice management, patient communications, patient charting, diagnosis, and treatment is now at the center of innovation and professional debate. This article explores the rapid adoption and use of AI in clinical practice balanced against privacy concerns, current technological limitations, and legal and ethical considerations.
Dental practitioners are feeling more pressure than ever before to integrate artificial intelligence (AI) tools into their practices. “AI” is a broad term that includes aspects of machine learning, software integration, summary tools and other automation. What started as predictive text models, billing/coding software integration, and automatic template preparation in charting and patient communications has evolved to automated preparation of high-level clinical summaries, diagnostic tools, imaging analysis, research tools, and more. Most of these AI tools “learn” from you the more you engage – adopting your preferences, style and language – and have proven tremendously efficient in both practice management and clinical care.
When used appropriately and with thorough understanding of the data an AI tool reads, stores, shares and manipulates, the potential benefits are limitless. On the other hand, as a healthcare provider with legal and ethical obligations regarding patient data and clinical documentation/retention, the need to understand and vet these tools before incorporating them into your practice cannot be understated.
AI in Practice Management
Regardless of where you are in the process of adopting new AI efficiencies, the reality is you are probably already using more AI than you realize. Most basic dental software already uses some form of AI, particularly as it relates to practice management. Examples include scheduling, automated appointment reminders, payment portals, auto-generated invoicing and other communications. These have become so commonplace you may not even consider their function as AI. Such efficiencies allow providers to focus more on patient care and less on administrative obligations, providing a time-savings benefit in clinical settings.[i]
The more technology you incorporate, though, the greater the risk and need for consideration. One issue facing providers is lack of integration with existing software. If an AI application is separate from your primary electronic health record, consider how data from that tool will make its way into the patient’s chart and be stored in compliance with recordkeeping and privacy requirements.
For example, you may use a software platform for your clinical notes but use a different application for appointment reminders and patient communications. You might have an entirely separate billing, invoicing and insurance program. When tools you rely on are separate, you need to have a plan for saving, storing and incorporating that information into your patient’s record. You may be accustomed to directing staff to copy/paste practice emails into the patient’s chart. This inconvenience is magnified when you use third-party text/email-based communication platforms that don’t integrate into the patient chart. Many have not considered how these communications will be preserved as part of the patient’s record. You may have patient communications saved in three places with no system to ensure those communications are saved and available in the event of a release of records or legal inquiry. You may forget to archive the data regularly or direct it into individual patient records, potentially leaving you out of compliance with document retention requirements.
Even if the communication tools you use integrate with existing software, consider what data is being shared between those applications. While a communications application may need basic information like patient names, emails, and phone numbers, billing software may store or maintain insurance and payment information. Additionally, the patient notes contain confidential medical information. The more data that is shared, stored, or read by an AI tool, the greater the risk of a data breach, sale or distribution of you/your patient’s data or proprietary systems, and unwanted access or dissemination.
AI, Patient Charting and Patient-Facing Efficiencies
AI tools have utility far beyond practice management. Speech-to-text recording and dictation software are AI tools that have been used for decades. These capabilities have now evolved to allow summarization of patient appointments, diagnostic tools from examinations and associated imaging, and advanced referrals, treatment plans, and clinical options with patient cost and care longevity analysis.[ii]
Integrating advanced clinical AI tools with patient audio and video recording now raises more than the obvious HIPAA protection concerns. With growing risks of “voice cloning” (using AI to create artificial voices that sound like a specific person) and other hacks including facial recognition tools, which may lead to the adoption of the likeness of minors or third parties entering your waiting room, understanding what happens to the data you are allowing third-party companies to access is more critical than ever. Additionally concerning, the accuracy of these applications is still in question, leading to concerns about the integrity of the data it is producing that you (and others) may be relying upon.[iii]
Consider a tool that audio records your clinical examination and summarizes a note for you. In addition to ensuring the note will be included in the patient’s chart, you must consider the accuracy of the note. What if the automation misheard you and you need to make robust edits? What if the automated system places the note in the incorrect patient file? Do your drafts become a part of the patient’s chart? As a Colorado practitioner, your obligation is to ensure essential entries are included in the dental chart (C.R.S. § 12-220-201(z)). Essential entries are broadly recognized as those that support your clinical decision making and clinical findings. If you relied upon the AI-generated summary to formulate your treatment plan, or if you used any portion of the summary that you did not author, you should take a hard look at how you are documenting and maintaining it in the patient record.
In the event you include notations about use of AI in practice, how, if at all, are you notifying your patients that you are using this technology? Many practices are considering implementation of consents, but without a true understanding of the software these disclosures may raise questions you and your staff are not equipped to answer. In the event you have patient-facing AI-supported tools, you need to be prepared to balance patients who embrace transparency and efficiency with those who express reservations about your reliance on AI or use of their data in these tools.[iv]
At present, there is no formal guidance or answers to these important considerations. Best practices mandate transparency, meaning at a minimum, you should identify that the final note in the chart incorporates the substance of an AI-generated summary. Whether you include prior versions of the AI note, including but not limited to the original note, is, as it stands today, a judgment call. If you are recording entire examinations, consider how maintaining those recordings may be helpful or harmful in the event of future inquiry in terms of consent, price transparency and other legal issues. The answers to these issues will come as patients and practitioners adjust to the reality that AI is here to stay and will inevitably become a large part of clinical dental care.
The Future of AI Integration
As it stands, few dental organizations or state licensing boards have issued formal guidance relating to the scope or necessity of additional patient consents, disclosures or other communications about the use of AI in practice or research.[v] Several states, including Colorado, have begun considering mandating affirmative consent of patients when healthcare providers utilize certain AI integrations, though thus far many have largely been limited to specific areas outside of dentistry.[vi] As AI implementation continues to grow, disclosures — not only to patients but potentially to professional liability insurance carriers and third-party patient insurance payors — may become routine practice. Disclosures as to how AI is used in research, education and training may also become necessary as technology advances and creates efficiencies at the expense of data privacy considerations.
Practitioners across all healthcare industries are facing the unenviable position of weighing their own comfort level with use of AI against patient demand and seemingly equal patient apprehension. On a busy day, it might be tempting to download the latest application without thorough vetting, copy/paste the whole AI summation into the patient’s chart or rely on a complex diagnosis and treatment plan which you relay to the patient. As incredible as AI developments are, they remain a mere supplemental tool and not a replacement for clinical examination, review, analysis and verification. Whether you are a practitioner excited and invigorated by the availability of these revolutionary machine learning tools or more cautiously beginning to accept the reality that AI is here to stay, now is the time to understand what AI truly is and what it means for you, your business, your patients and the future of dental practice.
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[i] Meredith A. Bailey, D.M.D., M.B.A., Ethical Considerations for the Integration of Artificial and Augmented Intelligence in Dentistry, The Journal of the American Dental Association, Vol. 155:8 (August 2024).
[ii] American Dental Association SCDI White Paper No. 1106—Dentistry—Overview of Artificial and Augmented Intelligence Uses in Dentistry (Dec. 30, 2022), available at https://www.ada.org/-/media/project/ada-organization/ada/ada-org/files/resources/practice/dental-standards/ada_1106_2022.pdf.
[iii] Sohaib Shujaat, et al., FDA Approved AI Solutions in Dental Imaging: A Narrative Review of Applications, Evidence, and Outlook, International Dental Journal (Dec. 2025), available at https://pmc.ncbi.nlm.nih.gov/articles/PMC12775797/.
[iv] Laura Ramsey, Artificial Intelligence in Patient Care, Education and Treatment, Metro Denver Dental Society, available at https://mddsdentist.com/practice-management/ai-in-dentistry/.
[v] J. Cunha-Cruz, N., et al. IADR and AADOCR Policy Statement on Ethics in Artificial Intelligence (AI) in Dental, Oral, and Craniofacial Research, April 3, 2026, International Association for Dental, Oral, and Craniofacial Research, available at https://www.iadr.org/science-policy/policy-statement-ethics-artificial-intelligence-ai-dental-oral-and-craniofacial.
[vi] See HB26-1139, Use of Artificial Intelligence in Health Care, available at https://leg.colorado.gov/bills/HB26-1139; Scott Driggs & Bill Ojile, Preparing for the Convergence of SB 24-205, HB26-1139, and HB 26-1195—Three new Colorado Laws Targeting AI in Healthcare, Snell & Wilmer (April 23, 20260, available at https://www.swlaw.com/publication/preparing-for-the-convergence-of-sb-24-205-hb-26-1139-and-hb-26-1195-three-new-colorado-laws-targeting-ai-in-healthcare/
