Informed Consent in AI-Augmented Dentistry and Dental Research: A Scoping Review

Background/Objectives: Artificial intelligence (AI) is increasingly used in dental diagnostics, treatment planning, documentation, and research. However, there is limited synthesis of how informed consent should be understood and operationalized in AI-augmented dentistry. This scoping review aimed to map the existing literature on informed consent in AI-assisted dental care and dental research, identify conceptual and practical gaps, and synthesize key domains relevant to ethically robust implementation. Methods: This review was conducted in accordance with PRISMA-ScR and the review question was developed using the Population-Concept-Context framework. Searches were performed in PubMed, Web of Science, and ClinicalKey, supplemented by Google Scholar and reference list screening. English-language sources published between January 2015 and January 2026 were considered if they addressed informed consent, patient information, autonomy, transparency, accountability, or governance in relation to AI use in dentistry or dental research. Results: Of 2624 records identified, 30 sources were included. The reviewed literature consistently emphasized the importance of disclosing AI involvement, clarifying clinician accountability, communicating uncertainty and bias, distinguishing clinical care from research-related consent, and addressing secondary data use. Most included sources were conceptual, ethical, regulatory, or narrative in nature, with limited empirical evidence on implementation or patient outcomes. Conclusions: The available literature suggests that informed consent in AI-augmented dentistry should extend beyond traditional clinician-patient models to explicitly address AI involvement, human oversight, and data governance. Based on recurring themes across the included sources, we propose the ACCOUNT-AI framework as a conceptual synthesis to support future research, policy development, and implementation efforts.