The global health workforce is approaching a breaking point, driven by administrative overload, inefficient workflows, burnout, and accelerating retirements, with a projected global shortfall of 11 million health professionals by 2030. This urgency coincides with the rapid emergence of clinical artificial intelligence (AI) tools, especially generative systems now embedded in documentation, triage, and workflow support. Therefore, AI should be framed less as a substitute for clinicians than as a retention strategy that preserves careers, expertise, and the human core of care. High-impact uses include ambient documentation, coding support, scheduling and demand prediction, claims and billing support, and inbox triage-tools that can reduce clerical burden and return time to caring, teaching, and leadership. Workforce shortages also create an ethical and geopolitical dilemma; reliance on international recruitment can deepen global inequities, whereas responsible AI deployment might ease competition for scarce talent and expand capacity in lower-resource settings. Yet, AI will not fix dysfunctional systems by default; poorly designed implementation can shift burdens, erode confidence, and widen gaps in health-care quality, access, and clinician wellbeing. Practice must remain clinician-led, patient-centred, and grounded in shared decision making. The policy priority is expertise amplification, not workforce replacement.
Dai et al. (Mon,) studied this question.
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