Poster #3 - AI-Driven Productivity, Workforce Transformation, and Equity in Healthcare and the Public Sector

• In Event: Saturday Poster Luncheon

Abstract

Artificial intelligence (AI) is increasingly reshaping how institutions operate, how services are delivered, and how value is generated across sectors. Healthcare has emerged as a critical domain for examining these transformations, as AI applications are used to automate diagnostics, streamline administrative processes, and enhance care coordination. While these developments are associated with measurable productivity gains, they also raise important questions regarding workforce restructuring, access disparities, and the governance of technological change.This paper examines how AI adoption in U.S. healthcare can inform broader public sector innovation, with a focus on implications for workforce dynamics and policy design. Specifically, the study assesses three interrelated questions: How does AI influence productivity and cost structures in healthcare relative to prior technological shifts? How does AI reshape workforce composition, task allocation, and skill requirements? And how can these dynamics inform equitable and sustainable public sector transformation?Using a mixed-methods approach, the analysis combines secondary data on healthcare productivity and AI adoption with case-based evidence from healthcare systems. It further incorporates institutional and policy analysis to examine how public agencies regulate, fund, and shape the implementation of AI technologies. This approach allows for a systematic assessment of both measurable outcomes and underlying institutional mechanisms.Preliminary findings suggest that AI adoption is associated with increased operational efficiency and task reallocation, particularly in administrative functions and routine clinical processes. However, these gains are unevenly distributed across institutions and occupations. The analysis indicates that workforce impacts are differentiated by skill level and role, with potential displacement risks for routine tasks alongside opportunities for augmentation and role transformation. In addition, variation in institutional capacity appears to influence the extent to which productivity gains translate into improved service delivery and equitable access.The paper develops an evaluative framework for AI integration in the public sector that emphasizes workforce resilience, institutional capacity, and equity. It contributes to policy discussions by identifying governance and implementation mechanisms that can align productivity gains with inclusive and sustainable public value creation.

Author

• Imen Ameur, Hult International Business School
  Presenting Author