The role of artificial intelligence in clinical decision making for prosthodontic treatment planning, manufacturing, and complication management

Artificial intelligence is becoming an increasingly influential component of prosthodontics, reshaping digital workflows into intelligent clinical systems that may enhance diagnostic precision, treatment planning, and restorative outcomes. This narrative review aims to examine the role of artificial intelligence in prosthodontic clinical decision-making, with particular emphasis on treatment planning, restoration design, manufacturing processes, risk assessment within the clinical workflow, and the prediction of potential complications. Contemporary artificial intelligence approaches, including deep learning, generative modeling, and multimodal data integration, enable the simultaneous interpretation of heterogeneous clinical information derived from radiographic imaging, intraoral scans, facial scans, and occlusal records. Within this framework, artificial intelligence has demonstrated substantial potential in prosthetically driven implant planning, automated prosthesis design, and the generation of patient-specific restorations tailored to individual anatomical and occlusal characteristics. These capabilities may enhance marginal adaptation, occlusal harmony, esthetic outcomes, and manufacturing precision, while also promoting greater standardization and reproducibility across clinical workflows. In parallel, predictive artificial intelligence models have shown promising performance in identifying biological and mechanical risk profiles by integrating clinical, radiographic, and biomechanical variables, thereby supporting earlier intervention in prosthodontic care. Despite these advances, current artificial intelligence applications in prosthodontics remain constrained by limited training data, insufficient testing in real clinical environments, and uncertain performance across different patient groups. Overall, available evidence suggests that artificial intelligence may provide clinically relevant support in prosthodontics by assisting diagnostic interpretation, prosthetically driven treatment planning, restoration design, and complication risk assessment.