The case for surgeons to embrace <scp>AI</scp> as a disruptive technology

Abstract

People won't be replaced by AI. They'll be replaced by people who know how to use AI. In the years ahead, technological disruption in surgery will probably not arise from artificial intelligence (AI) itself, but from the growing divide between those who can harness its potential and those who cannot. It is not AI that will replace surgeons—it is AI-literate surgeons who will. AI represents a new kind of disruption—one that transcends technical refinement and reshapes the very nature of surgical work. Traditional surgical innovations, such as the introduction of laparoscopic or robotic surgery, revolutionized access and dexterity but left the surgeon's cognitive role largely untouched. Surgeons remained the interpreters, the decision-makers, and the ultimate executors of each manoeuvre. AI, however, disrupts this paradigm by extending into the cognitive domain. It enables algorithms to interpret radiologic scans, stratify operative risks, suggest procedural plans, and even predict post-operative outcomes. While laparoscopic surgery demanded new psychomotor skills, the use of AI demands new cognitive and ethical competencies. This shift challenges surgeons to move beyond the identity of being ‘skilful technicians’ who perform operations, towards becoming empathetic interpreters of data and curators of AI-augmented care. The surgeon's role will increasingly involve integrating computational insights with human empathy—ensuring that AI-driven recommendations are aligned with each patient's values, goals, and context. The surgeon's professional identity is entering a profound transformation. The rise of AI-driven systems capable of perception, reasoning, and autonomous execution compels us to redefine what it means to ‘perform’ an operation. The milestone demonstration of autonomous cholecystectomy using a hierarchical, language-conditioned framework (SRT-H) marked a turning point.1 The system performed the clipping and cutting steps entirely independently, achieving a 100% success rate in ex vivo models. While the procedure was simple compared to complex oncologic or reconstructive operations, it symbolized a threshold moment: AI could now observe, plan, act, and recover from its own errors. The logical next step is the progression towards fully autonomous operations for selected pathologies, where structured, repetitive procedures such as appendectomy, hernia repair, or specific stages of hepatectomy become amenable to automation. Each iteration of AI learns from vast surgical datasets, improving exponentially. The surgeons of the future will therefore not disappear but ascend to a new supervisory role—overseeing autonomous systems, ensuring safety, and contextualizing AI outputs within humanistic care. Beyond the operating room, AI has already begun reshaping decision-making and precision in oncologic and peri-operative care. In the field of surgical oncology, the emergence of the augmented oncologist illustrates how AI is redefining complex therapeutic decision-making.2 AI-powered decision-support systems can dynamically integrate guidelines, genomic data, and real-world outcomes to provide personalized, context-aware recommendations. Rather than replacing oncologic judgment, such systems serve as choice architects, helping surgeons and oncologists weigh competing regimens and tailor therapy to each patient's profile. Similarly, AI-powered spatial analysis in pancreatic cancer has redefined tumour biology.3 AI-based mapping of tumour-infiltrating lymphocytes can identify immune phenotypes predictive of survival, transforming histopathology into a field of quantitative immune spatial analytics. In critical care, AI integration guided by human-centric governance emphasizes ethical, transparent, and equitable decision-making—ensuring that AI supports, not supplants, the human connection at the heart of medicine.4 Despite these advances, adoption of AI in surgical practice faces psychological and logistical barriers. Among these, resistance to change remains perhaps the most powerful, particularly among established surgeons who feel that AI is ‘for future generations.’ Such attitudes reflect pride and a fear of obsolescence, but risk excluding experienced surgeons from shaping future systems. Developing AI literacy demands epistemic humility—the recognition that traditional expertise is incomplete in the face of complex algorithms. Humility here does not mean surrendering authority, but acknowledging that knowledge could be co-constructed between human and machine. It allows the surgeon to critically question AI recommendations and integrate them with clinical intuition. Institutional inertia, lack of data integration, and absence of structured AI education further constrain progress. Embedding ethical AI governance principles such as transparency, accountability, and human oversight into surgical training will be essential to bridge craftsmanship and digital mastery.5 This transformation demands leadership, not adaptation alone. A key framework is double-loop learning—distinguishing between single-loop learning (correcting errors within existing assumptions) and double-loop learning (questioning and revising the assumptions themselves). Applied to AI in surgery, single-loop learning might involve improving an algorithm's accuracy, whereas double-loop learning asks: Should this task be automated? What values does this system reinforce? How does it reshape the surgeon–patient relationship? By fostering double-loop learning, surgical leaders can ensure that AI innovation aligns not only with technical excellence but with ethical purposes. Responsible governance requires adaptive frameworks balancing innovation and accountability. Surgeons, as both clinicians and leaders, must commit to ongoing reflection, inclusive dialogue, and structures that safeguard human dignity while embracing technological progress. AI will not replace the surgeons' hands or hearts, but it may redefine the mind of surgery. The surgeons who thrive in this new era will be those who engage with AI as collaborators, not competitors—combining surgical wisdom with digital fluency and leadership with foresight. The question, therefore, is no longer whether AI will disrupt surgery (because it already has), but who among us will shape that disruption into progress.

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