Background: Colorectal surgery continues to exhibit variability in outcomes despite advancements in minimally invasive and robotic techniques. Increasing evidence suggests that this inconsistency is driven less by technical proficiency than by unstructured, experience-dependent decision-making. Objective: This article presents a hybrid narrative review and perspective that examines the cognitive underpinnings of surgical strategy. It evaluates how cognitive augmentation—particularly through artificial intelligence (AI)-enabled decision support—can improve consistency, reproducibility, and equity in colorectal care. Methods: We conducted a structured synthesis of literature from surgical cognition, naturalistic decision-making, and augmented intelligence. The review integrates perspectives from behavioral science, digital health, and colorectal surgery. AI-assisted dialogue (ChatGPT-4o) was used under human supervision to support hypothesis generation, narrative framing, and linguistic refinement. Approximately 30% of the article was developed using AI-generated suggestions, which were critically reviewed and edited by the authors to ensure clinical and scientific accuracy. Practical examples from elective and emergency settings illustrate clinical relevance. Results: Experience-based heuristics and tacit knowledge, though valuable, are susceptible to bias and variability, particularly in complex scenarios. Cognitive augmentation tools demonstrate potential in improving decision-making reliability when carefully incorporated into clinical workflows. Nevertheless, their deployment encounters obstacles such as data heterogeneity, insufficient standardization, and barriers to clinician adoption. Robotic platforms provide enhanced technical execution but necessitate integration with cognitive tools to facilitate strategic reasoning. Conclusion: Strategic consistency in colorectal surgery requires more than technological refinement; it demands a shift toward cognitively structured decision-making. Augmenting surgeon judgment through intelligent, context-aware support systems represents a critical next step toward reproducible, high-quality surgical care.
Delrio et al. (Mon,) studied this question.