Informed Consent in Artificial Intelligence-Augmented Dentistry: Clinical Care, Research, and the Dentist–Patient–AI Relationship: A Scoping Review

Artificial intelligence (AI) is increasingly integrated into dental diagnostics, treatment planning, documentation, and research. While ethical principles such as transparency and accountability are widely discussed, there is limited synthesis of how informed consent should be conceptualized and operationalized within the evolving dentist–patient–AI relationship. This scoping review aimed to map existing evidence on informed consent in AI-augmented dentistry and dental research, identify conceptual and practical gaps, and propose a structured framework to support ethically robust implementation; Methods: PRISMA-ScR guidelines was followed with review question formulated using the Population–Concept–Context (PCC) framework. A systematic search was conducted in PubMed, Web of Science, and ClinicalKey, complemented by grey literature screening; Results: From 2624 identified records, 30 studies were included after screening. The literature consistently emphasized disclosure of AI involvement, clarification of clinician accountability, communication of algorithmic limitations and bias, and separation between clinical and research consent. Based on thematic synthesis, we propose the ACCOUNT-AI framework, comprising structured domains addressing AI role clarification, clinician accountability, contextual differentiation, operational risks, secondary data governance, adaptive consent design, and transparency across the AI lifecycle. The framework integrates clinical use, research applications, and regulated data reuse as components of a unified accountability model; Conclusions: Informed consent in AI-augmented dentistry requires adaptation from traditional bilateral models to a triadic dentist–patient–AI framework grounded in human professional accountability. Standardized, context-sensitive consent structures are needed to ensure transparency, protect patient autonomy, and support ethically responsible AI integration in both clinical care and research.