Generative artificial intelligence in dentistry: A narrative review of current approaches and future challenges

Résumé fourni par la source

Artificial intelligence (AI) has become a commodity for laypeople and domain experts because of the advent of generative AI (GenAI) models that bridge the usability gap of AI by providing a natural language interface to interact with complex models. GenAI models perform tasks ranging from text generation, such as two-way chat systems, to image and video generation from user-provided textual descriptions. These advancements in AI have impacted Dentistry in multiple aspects. Dental education now benefits from GenAI models by enabling students to address numerous questions through intuitive prompts, receiving instant answers. Dental healthcare practitioners utilize GenAI to gather knowledge quickly and efficiently, improving patient care. In dental research, GenAI supports activities such as academic writing and the discovery of new drugs and therapies. In this narrative review, we summarize the current state of GenAI in dentistry as of 2025, define GenAI models, describe their multiple generation modalities, and discuss their current and potential applications in Dentistry. Finally, we describe the challenges these new technologies impose in our area. • Generative artificial intelligence (GenAI) models are a subset of models trained to provide answers that satisfy instructions given in natural language and not trained to solve a specific task. • GenAI enhances dental education by providing assessment, giving automated feedback, and reinforcing the overall student learning process. • GenAI improves clinical dental practice by supporting diagnostic, treatment, and patient communication processes. • GenAI accelerates dental research by assisting in academic writing and expediting the discovery of biomolecules and therapies for oral health conditions. • Integrating GenAI into dentistry presents challenges, including ethical concerns, data privacy, and the need for regulatory frameworks, which can be addressed through GenAI literacy and appropriate guidelines.

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