The digital scalpel: navigating the future of surgical innovation
BACKGROUND: Artificial intelligence is entering surgical practice not as an extension of the surgeon's hand, eyes, or dexterity, but of surgical judgment itself. This creates a growing informational asymmetry between well-resourced and under-resourced operative environments, with implications for training, competence, accountability, and equity. METHODS: This commentary, derived from the Karl Storz Lecture delivered at the SAGES 2026 Annual Meeting, proposes the Digital Scalpel: a five-layer conceptual architecture (data infrastructure, connected systems, computational vision, cognitive augmentation, and human judgment) for understanding AI-enabled surgical practice. The current evidence base for each layer is appraised, with particular reference to AI assessment of the Critical View of Safety in laparoscopic cholecystectomy. RESULTS: Computational vision is the most mature layer, with deep-learning systems demonstrating high concordance with expert assessment of the Critical View of Safety, though validation remains largely confined to elective, uninflamed, single-centre cases. Three risks are identified: automation complacency, an unresolved accountability gap, and a digital inverse care law under which AI-augmented capability tracks existing resource inequities. The most evidence-supported entry point for most institutions is routine operative video capture and structured review, not real-time guidance. CONCLUSIONS: The surgeon of 2035 will require four attributes: preserved technical excellence, data literacy as a core competency, ethical fluency, and institutionalised clinician-engineer collaboration. The Digital Scalpel demands active, critical, and equitable engagement rather than passive technological adoption.
Authors
- Derek T. O’Keeffe (ORCID: https://orcid.org/0000-0001-8501-2382)
Institutions
- Ollscoil na Gaillimhe – University of Galway (IE)
Publication Details
- Journal
- Surgical Endoscopy
- Published
- 2026-08-03
- DOI
- https://doi.org/10.1007/s00464-026-13131-7
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Irish Research eLibrary