Author ORCID Identifier

https://orcid.org/0000-0003-3080-4379

Semester

Spring

Date of Graduation

2026

Document Type

Dissertation

Degree Type

DBA

College

Chambers College of Business and Economics

Department

Management

Committee Chair

Ryan Angus

Committee Member

Jeffery Houghton

Committee Member

Hyeonsuh Lee

Committee Member

Richard Oxarart

Abstract

The purpose of this single-case qualitative project is to uncover how self-leadership’s behavioral and cognitive strategies influence perceptions of Artificial Intelligence (AI) and AI adoption. While existing literature acknowledges that there is an association between self-leadership, technology’s perceived usefulness and ease of use, as well as comfort with AI preparedness and its professional impact, there is limited research on how self-leadership shapes perceptions of AI and AI adoption in real-life contexts. To fill this gap in contemporary literature, this project analyzes qualitative semi-structured interviews with 25 healthcare professionals involved in the implementation of ‘AI Model 1’ at their mid-sized United States healthcare system. Interview data was analyzed inductively using Qualitative Content Analysis and followed grounded-theory coding best practices. Results indicated that participants high in self-leadership described more concerns about AI and expressed more benefits of augmented AI use, when compared to low self-leaders. Perceived ease of using AI also emerged as a mediator between self-leadership and AI use. Finally, this project’s most profound contribution to self-leadership and technology adoption theory is the Theory of Self-Leadership-AI Reciprocity (SLAIR), which explains that a reciprocal relationship exists where AI use strengthens the very psychological resource (i.e. self-leadership) that predicts its own adoption. This project extends our theoretical understanding by identifying self-leadership as a key antecedent driving perceptions of AI and AI adoption, while AI use, in turn, drives self-leadership development. In terms of practical implications, this project highlights the importance of implementing AI tools that enhance self-leadership, support autonomy, and facilitate augmented decision-making, rather than replacing humans with AI.

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