Dental surgery is undergoing a paradigm shift from manual, freehand techniques toward robotic-assisted and ultimately autonomous procedures. This review examines the convergence of artificial intelligence, computer vision, haptic feedback, and robotic actuation in dentistry, focusing on the current state of autonomous implant placement, osteotomy preparation, and soft tissue management. We analyze three tiers of autonomy: (1) robotic-assisted (surgeon-in-the-loop), (2) semi-autonomous (supervisory control), and (3) fully autonomous (no human intraoperative decision). Recent advances demonstrate that fully autonomous implant placement from preoperative planning to osteotomy execution and implant seating can achieve sub millimeter accuracy (entry point error <0.15 mm, angular deviation <1.0°) with zero cortical breaches in cadaver studies, exceeding human performed freehand accuracy by 3 5×. Key enabling technologies include: multi modal imaging (CBCT with intraoperative registration), 6 DOF force torque sensing (0.1 N resolution), and deep learning based anatomical segmentation (Dice >0.95). However, significant barriers remain: regulatory approval for autonomous surgical decision making, high capital costs ($350,000–500,000 per system), and surgeon acceptance in an inherently conservative field. We discuss the trajectory from the first fully autonomous implant procedure (2025) to anticipated regulatory clearance (2028–2030), concluding that while full autonomy in complex multi step procedures remains distant, targeted autonomous tasks will become clinically routine within the next decade.