{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T23:47:53Z","timestamp":1782517673959,"version":"3.54.5"},"reference-count":38,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["The American Surgeon\u2122"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The surgical workforce in the United States is aging while artificial intelligence (AI) tools are increasingly integrated into clinical practice. These developments raise questions about cognitive aging, professional longevity, and patient safety within the cognitive domains of surgical performance. This review situates these issues within the broader context of surgeon competency, cognitive aging, and the integration of emerging technologies into clinical practice.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This narrative review synthesizes literature published between 2000 and 2026 addressing cognitive reserve, cognitive offloading, automation bias, surgeon aging, fatigue, and contemporary AI applications relevant to surgical decision-making. Emphasis was placed on human studies, clinically applicable cognitive science, and AI tools currently used in perioperative care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Cognitive aging is associated more consistently with reduced processing speed and endurance than with deterioration in clinical judgment. Sustained engagement in complex surgical practice may contribute to cognitive reserve. Current AI systems primarily offload documentation, information retrieval, and organizational tasks, thereby reducing extraneous cognitive load without replacing clinical reasoning. Overreliance on automated systems introduces risk of automation bias and diminished vigilance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI does not restore technical dexterity and does not substitute for surgical judgment. When implemented deliberately, it may reduce peripheral cognitive burden and support reliable decision-making. For late-career surgeons, AI functions as augmentation rather than replacement.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00031348261465684","type":"journal-article","created":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T06:43:48Z","timestamp":1782369828000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence, Cognitive Aging, and the Late-Career Surgeon: A Narrative Review"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2561-0550","authenticated-orcid":false,"given":"Kimberly","family":"McElveen","sequence":"first","affiliation":[{"name":"Mercer University School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9324-9031","authenticated-orcid":false,"given":"Don K.","family":"Nakayama","sequence":"additional","affiliation":[{"name":"Mercer University School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"issue":"3","key":"e_1_3_3_2_2","first-page":"512","article-title":"Geographic disparities in the supply and adequacy of the general surgeon workforce: a national projection study","volume":"178","author":"Darnell B","year":"2025","unstructured":"Darnell B, Clancy T, Zaydfudim V, et al. 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