In the rapidly digitizing landscape of modern dentistry, artificial intelligence (AI) is becoming increasingly integrated into clinical workflows, patient engagement platforms, diagnostics, and practice management systems. Although AI promises remarkable improvements in efficiency and precision, it also introduces new cybersecurity and privacy vulnerabilities. Dental offices, which often operate with limited information technology (IT) infrastructure and cybersecurity expertise, are particularly susceptible to emerging cyber threats. On the flipside, AI can also be used defensively to safeguard sensitive patient data and ensure uninterrupted dental care. In order to properly protect themselves, it is important for dental practices to understand both the risks and benefits to cybersecurity that can come with the use of AI systems.
The Cybersecurity Risks of AI
Dental offices are not immune to the wave of cyberattacks that have recently targeted healthcare organizations. In fact, they may be more vulnerable due to a lack of robust security protocols, reliance on legacy systems, and limited cybersecurity budgets allocated for housing and using federally protected data. Examples of cybersecurity vulnerabilities that AI can create in a dental practice include the following:
1. Increased Attack Vectors
Many dental offices now use AI-powered platforms for appointment scheduling, diagnostic imaging, billing, and more. Oftentimes, these systems integrate with practice management software, electronic health record systems, and cloud-based storage solutions. If AI applications are not properly secured, they can introduce new points of entry for cybercriminals. If your patient data is stored off site in one of these new AI systems, it can create an additional point of entry for bad actors to access that data, and there are a whole host of third-party associates that are vulnerable. In addition, such systems can be vulnerable to adversarial attacks where bad actors manipulate input data to deceive AI algorithms and compromise diagnostic tools or image analysis software.1
2. Data Privacy and Cross Contamination
The AI models that are used in healthcare, including dentistry, are trained with vast quantities of sensitive data. If these models are improperly secured, attackers could exploit them to extract confidential patient information using a method known as model inversion.2 Furthermore, most of the AI assistants will ingest any data that they can access, so unless you have gone through all of your documents and folders and deemed the data private, it can show up in a model and become vulnerable through cross contamination. In the context of dental practice, this could include medical and treatment histories, radiographs, financial records, and insurance details-all of which are highly valuable on the dark web.
3. Enhanced Social Engineering
All of the dental industry cybersecurity incidents that have occurred over the years, including those involving Henry Schein, the American Dental Association, Delta Dental, and Change Healthcare, have given criminals a plethora of material to train AI tools to craft increasingly sophisticated phishing attacks. Generative AI tools can be used by hackers to craft highly convincing phishing emails and spoofed voice messages, which can be used to trick team members into divulging credentials or downloading malware. Because dental offices often lack formal cybersecurity training, they can be particularly vulnerable to such AI-enhanced social engineering attacks.3
4. Development of a False Sense of Security
As AI automates more and more functions, there's a risk that dental professionals may develop a false sense of security from the assumption that the technology is self-monitoring. However, AI systems themselves can be exploited or misconfigured. Without regular auditing and updates, even well-intentioned AI tools can be compromised and become liabilities.
AI as a Cybersecurity Ally
Although the incorporation of AI poses cybersecurity risks, it can also offer powerful tools to combat cyber threats when implemented thoughtfully and securely. For dental offices, AI-driven cybersecurity solutions can act as proactive sentinels, identifying and neutralizing threats in real time. Benefits to cybersecurity from the use of AI include the following:
1. Threat Detection and Anomaly Monitoring
Machine learning algorithms excel at identifying patterns and anomalies in large datasets. When appropriately implemented, AI-based intrusion detection systems can analyze network traffic in real time and flag suspicious activity, such as unauthorized access attempts or unusual data transfers.4 For dental practices, this can result in the prevention of breaches or faster identification of breaches before they escalate.
2. Behavioral Biometrics and Authentication
AI can enhance security through continuous authentication techniques, such as behavioral biometrics. These systems can analyze unique user behaviors, such as typing speed, mouse movement, or login patterns, to help detect imposters.5 For dental offices that rely on remote access or telehealth solutions, AI-enhanced authentication can provide an extra layer of verification without hindering practice workflow.
3. Phishing Detection and Email Security
AI can also be used to improve a practice's email security by scanning incoming messages for patterns associated with phishing or malware. Natural language processing tools can assess the tone and content of emails to detect attempts at impersonation or social engineering. Having this defensive capability is especially valuable for front-desk personnel and office managers who communicate via email far more often than clinical team members and, therefore, are frequent targets.
4. Automated Incident Response
When threats are detected, AI-powered platforms can be programmed to take automated actions, such as isolating affected devices, locking accounts, or alerting administrators. In resource-constrained dental offices, this immediate response can prevent breaches from spreading and buy valuable time for human intervention.
Best Practices for Safe AI Adoption
AI is rapidly changing the business and practice of dentistry. In order to balance innovation with protection, dental offices should adhere to guidelines for safe adoption, including the following:
• Conduct regular security audits. Periodic reviews of AI systems and their integrations can help uncover vulnerabilities.
• Implement data controls. Regularly review where your data lives and who has access to it.
• Implement zero trust architectures. Trust no one by default. Verify every device and user attempting to access data.
• Provide continuous staff education. Train employees to recognize AI-enhanced phishing attempts and follow secure protocols.
• Partner with reputable vendors. Choose AI solutions from vendors that prioritize data security and comply with regulations such as the Health Insurance Portability and Accountability Act (HIPAA) privacy and security rules and those from the National Institute of Standards and Technology.
• Implement encryption and access controls. Secure both stored and transmitted data with strong encryption and restrict access to it based on roles.
Conclusion
The incorporation of AI into dentistry has the potential to yield transformative benefits, from improved diagnostics to streamlined administrative workflows. However, the same technologies that can improve patient care and office efficiency can also introduce new cybersecurity risks. For dental practices, the key to successful adoption lies in embracing AI thoughtfully-safeguarding against its misuse while leveraging its power to defend against threats. By building resilient systems and staying vigilant, dental offices can ensure that the future of AI in oral healthcare is not only smart but also secure.
References
1. Biggio B, Roli F. Wild patterns: Ten years after the rise of adversarial machine learning. Pattern Recognition. 2018;84:317-331.
2. Fredrikson M, Jha S, Ristenpart T. Model inversion attacks that exploit confidence information and basic countermeasures. In: Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security. Association for Computing Machinery; 2015:1322-1333.
3. Buczak AL, Guven, E. A survey of data mining and machine learning methods for cyber security intrusion detection. IEEE Communications Surveys & Tutorials. 2015;18(2)1153-1176.
4. Sommer R, Paxson V. Outside the closed world: on using machine learning for network intrusion detection, IEEE Symposium on Security and Privacy, 2010. IEEE Xplore website. https://ieeexplore.ieee.org/abstract/document/5504793. Published July 8, 2010. Accessed May 28, 2025.
5. Pusara M, Brodley CE. User re-authentication via mouse movements. In: Proceedings of the 2004 ACM Workshop on Visualization and Data Mining for Computer Security. Association for Computing Machinery; 2004:1-8.
About the Author
Tasha Dickinson, MBA, is the founder and chief technologist of Siligent, a provider of cybersecurity and IT solutions for dental businesses.
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Tasha Dickinson, MBA
