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It is clear that AI has the potential to impact the entire continuum of musculoskeletal and orthopaedic care. The following areas may experience improvements from integrating AI into surgical applications: surgical trainees can learn more easily at lower costs in extended reality simulations; physicians can receive support in decision\u2010making and case planning; efficiencies can be driven with improved case management and hospital episodes; performing surgery, which until recently was the only element industry engaged with, can benefit from intraoperative AI\u2010derived inputs; and postoperative care can be tailored to the individual patient and their circumstances. AI delivers the potential for industry to offer valuable augments to patient experience and enhanced surgical insights along the digital episode of care. However, the true value is in considering not just how AI can be applied in each silo but also across the patient\u2019s entire continuum of care. This opportunity was first opened with the advent of robotics. The data derived from the robotic systems have added something akin to a black box flight recorder to the operation, which now offers 2 critical outcomes for industry. First, together we can now start to stitch preoperative elements like demographics, morphological phenotyping, and pathology that can be integrated with intraoperative elements to produce surgical plans and on\u2010the\u2010fly anatomic data like ligament tension. Second, postoperative elements such as recovery protocols and outcomes can be considered through the lens of the intraoperative experience. In forming this bridge, AI can accelerate the development of a truly integrated digital ecosystem, facilitating a shift from providing implants to providing patient experience pathways.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Level of Evidence<\/jats:title>\n                    <jats:p>Level V, expert opinion.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1016\/j.arthro.2025.01.064","type":"journal-article","created":{"date-parts":[[2025,2,17]],"date-time":"2025-02-17T02:28:45Z","timestamp":1739759325000},"page":"1683-1690","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Intelligence in Commercial Industry: Serving the End\u2010to\u2010End Patient Experience Across the Digital Ecosystem"],"prefix":"10.1002","volume":"41","author":[{"given":"Michael J.","family":"Ormond","sequence":"first","affiliation":[{"name":"Stryker 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