AI is transforming diagnostics in dentistry, with over 97% accuracy in detecting caries from radiographs reported in a study.1 However, this progress comes with a critical dilemma: when AI and clinicians disagree, who is legally responsible? The absence of clear judicial guidelines creates a liability paradox, where both relying on and overriding AI can result in legal repercussions.

Hellyer highlights a future occupational hazard in dentistry and suggests solutions, including enforcing AI decisions, replacing jury trials with medical tribunals, and requiring a second blinded opinion before overriding AI.2 While these approaches address aspects of the problem, they do not fully resolve concerns about clinician autonomy, AI accountability, and legal clarity. Additional measures can ensure a balanced AI-clinician partnership.

AI should be recognised as a clinical support system, not an autonomous decision-maker. While AI can enhance diagnostic accuracy, clinicians must retain final authority over diagnoses to ensure patient safety and ethical practice. Legal protections should be in place to define AI as an advisory tool rather than a decisive authority, preventing blind reliance on AI-generated diagnoses. Without clear guidelines, the risk of misdiagnoses and liability concerns will continue to grow.

To strengthen clinical decision-making, AI-generated diagnoses should include confidence scores and explanatory reasoning. These indicators can help clinicians assess the reliability of AI predictions, allowing them to override low-confidence AI outputs with legal justification. A mandatory justification system for AI overrides would create a standardised, risk-based approach, reducing litigation risks when clinicians challenge AI-generated diagnoses.3

A major flaw in current legal frameworks is that full responsibility for AI-related errors falls on clinicians, discouraging AI adoption due to legal risks. Instead, a shared liability model can be introduced, making AI developers accountable for algorithmic errors alongside healthcare providers. Holding AI companies responsible for the safety and accuracy of their technology can incentivise better validation and protect clinicians from undue legal exposure.4

To address the growing legal uncertainty surrounding AI, standardised legal precedents must be established to define when clinicians are justified in accepting or rejecting AI recommendations. AI ethics review boards should evaluate disputed AI-driven decisions before legal action is taken. This can create a structured, transparent approach rather than leaving clinicians vulnerable to inconsistent and subjective legal interpretations.

AI is here to stay, but without urgent regulatory action, it risks becoming a liability trap rather than a diagnostic aid. Dentistry must proactively establish clinician-friendly guidelines that ensure AI remains an asset, not an obstacle, in patient care.