Artificial intelligence (AI) is poised to revolutionize surgical care by leveraging the vast and complex “data lake” of healthcare information. This perspective piece outlines how AI may harness structured and unstructured data to improve patient outcomes. Advances in deep learning and foundational models have enabled the development of predictive analytics, automated clinical documentation, personalized patient chatbots, remote monitoring, and enhanced medical imaging. Examples include the ACS NSQIP risk calculator, Sepsis ImmunoScore, startups in ambient transcription, and cutting-edge AI applications in intraoperative imaging and real-time diagnostics. However, the adoption of AI in healthcare requires overcoming challenges, including data privacy, bias, integration into clinical workflows, interoperability, cost, ethical concerns, and regulatory hurdles. As AI technologies evolve, collaboration between surgeons and scientists will be critical to ensure ethical, patient-centered designs. This manuscript calls for surgeons to lead AI applications role in surgery, bridging technology with meaningful use cases to positively align with clinical practice.
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