Artificial intelligence and robotic surgery in clinical medicine: progress, challenges, and future directions

Abstract

Technological innovations in medicine are increasingly expected to replicate the diagnostic, decision-making, and procedural skills of experienced physicians. This review explores the evolution, current status, and limitations of artificial intelligence (AI) and robotic surgery in clinical practice. Radiology and pathology have led the way in digital transformation, enabling AI applications through standardized datasets and electronic health records. However, limitations such as algorithmic opacity, legal-ethical uncertainties, and fragmented digital infrastructures continue to hinder broader implementation. In robotic surgery, soft tissue procedures have not yet demonstrated significant advantages over conventional laparoscopy in terms of cost or operative efficiency. Orthopedic applications, particularly in arthroplasty, are promising but still lack long-term validation. Importantly, for any technology to create true value in healthcare, its benefits must clearly outweigh its costs. As healthcare systems face mounting pressure from aging populations and rising procedural demand, particularly for cholecystectomy, prostatectomy, and arthroplasty, the development of efficient and scalable technologies becomes inevitable. While neither AI nor robotic surgery has yet fulfilled its transformative promise, historical trends suggest that innovation will persist toward overcoming these barriers.