Abstract: This analysis examines the concept of pro-worker artificial intelligence, defined as technologies that increase the value of human skills and expertise by expanding worker capabilities rather than merely replacing them. Drawing on recent scholarship and workplace examples, the paper distinguishes among five categories of technological change—labor-augmenting, capital-augmenting, automating, expertise-leveling, and new task-creating—and argues that only new task-creating technologies unambiguously enhance worker value. The essay presents evidence from multiple sectors demonstrating AI's collaborative potential in electrical services, custodial work, education, patent examination, and accessibility accommodations. Market failures including misaligned incentives, path dependence, and pro-automation ideology currently constrain pro-worker AI development. Nine policy interventions are proposed to redirect AI investment toward worker-enhancing applications, with particular emphasis on healthcare and education sectors where public leverage is substantial. The analysis concludes that while automation receives disproportionate attention and investment, AI's capacity to collaborate with workers represents an equally transformative yet underexploited opportunity for expanding employment and elevating the value of human expertise.
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