Artificial intelligence (AI) is transitioning from a novelty to a chairside partner in dentistry, transforming routine images, scans, and clinical notes into decisions that are faster, more consistent, and traceable. This chapter traces the arc of that transformation, building on existing foundations of AI and its applications in dentistry, while addressing key issues such as data, consent, and trust, which are factors that further enable personalized dental treatment. We demonstrate how multimodal inputs can be integrated into AI and machine learning (ML) systems to create patient-specific digital dental twins. These digital twins can serve as predictive models, enabling clinicians to simulate and assess how hard and soft tissues respond to mechanical load, strain, and biological remodeling. We analyze how AI is transforming clinical workflows across stages of dental care, while aligning with outcomes traditionally measured by clinicians. The shift toward clinician enablement in AI moves the focus from algorithms to practitioners, emphasizing AI’s critical role in dental and continuing education to support real-world adoption. Importantly, the impact of AI extends beyond dentistry to governance, insurance payers, and patients. As autonomy in AI systems increases, the need for oversight becomes imperative. To support responsible implementation, we introduce a lightweight ML operations playbook for clinicians. AI and ML technologies will continue to reshape dental care. Their implementation must be guided by a collective effort to ensure AI remains a reversible decision-support layer that enhances clinical judgment and makes dental treatment safer, faster, and more predictable.