Date of Conferral

7-10-2026

Date of Award

July 2026

Degree

Doctor of Business Administration (D.B.A.)

School

Management

Advisor

Melvia Scott

Abstract

Health care leaders in the United States increasingly adopt artificial intelligence (AI) to improve operational efficiency, yet many organizations struggle to achieve sustained operational value from AI initiatives. This problem is important to health care leaders, patients, clinicians, staff, and communities because AI-supported decisions may affect workflow, access, safety, staffing, and trust. The purpose of this qualitative pragmatic inquiry project was to explore strategies U.S. health care leaders used to improve operational efficiency through AI in hospital settings. Eight U.S. health care leaders in hospital settings across the United States participated. The technology-organization-environment framework grounded the project. Data were collected through semistructured interviews and public health care and policy documents and were analyzed using Braun and Clarke’s thematic analysis. Five themes emerged: (a) governance structure and human decision rights; (b) data infrastructure and data quality; (c) stakeholder engagement and adoption; (d) workforce culture and staff trust; and (e) health equity and community accountability. A key recommendation is that health care leaders establish governance before deploying or scaling AI. The implications for positive social change include the potential to improve access, reduce delays, support staff, and strengthen trust.

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