The aging population, burnout, and earlier retirement of physicians along with the static number of training positions are likely to worsen the current physician shortage. There is an urgent need to transform the process for selecting medical students. In this Invited Commentary, the authors suggest that to build the physician workforce that the United States needs for the future, academic medicine should focus on building capacity in 3 overarching areas. First, medical schools need to develop a more diverse pool of capable applicants that better matches the demographic characteristics of health care trainees with those of the population, and they need to nurture applicants with diverse career aspirations. Second, medical schools should recalibrate their student selection process, aligning criteria for admission with competencies expected of medical school graduates, whether they choose to become practicing clinicians, physician-scientists, members of the public health workforce, or policy makers. Selection criteria that overweight the results of standardized test scores should be replaced by assessments that value and predict academic capacity, adaptive learning skills, curiosity, compassion, empathy, emotional maturity, and superior communication skills. Finally, to improve the equity and effectiveness of the selection processes, medical schools should leverage innovations in data science and generative artificial intelligence platforms. The ability of ChatGPT to pass the United States Medical Licensing Examination (USMLE) demonstrates the decreasing importance of memorization in medicine in favor of critical thinking and problem-solving skills. The 2022 change in the USMLE Step 1 to pass/fail plus the exodus of several prominent medical schools from the U.S. News and World Report rankings have exposed limitations of the current selection processes. Newer approaches that use precision education systems to leverage data and technology can help address these limitations.