ORCID
https://orcid.org/0000-0001-5570-7626
Date of Award
Summer 2025
Language
English
Embargo Period
6-12-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
College/School/Department
Department of Public Administration and Policy
Program
Public Administration and Policy
First Advisor
Mila Gasco-Hernandez
Second Advisor
J. Ramon Gil-Garcia
Committee Members
Hongseok Lee, Marc Esteve
Keywords
Artificial Intelligence, Chatbots, Accountable AI, Explainable AI, Innovation, Digital Transformation
Subject Categories
Public Administration
Abstract
With the rapid advancement of artificial intelligence (AI), governments around the world are increasingly exploring how AI can enhance decision-making and improve public service delivery. A growing body of research has examined governmental use of AI, offering insights into several key areas: (1) domains of application, (2) potential benefits and risks of AI initiatives, and (3) adoption and implementation processes, including critical determinants and results. However, two significant gaps remain in the literature. First, there is limited understanding of how the unique characteristics of AI may transform government service delivery and internal operations. Second, while many studies on AI-related managerial processes emphasize data and technological aspects, few adopt a multi-dimensional approach — resulting in a fragmented understanding of AI’s role and influence in the public sector. Addressing these gaps, this dissertation aims to contribute to the literature by exploring the following overarching question: How do AI adoption, implementation, and result evaluation occur in the public sector?
Drawing on the literature on innovation adoption, technology implementation, and digital transformation, this dissertation develops a holistic framework to assess the processes of AI adoption, implementation, and result evaluation. Two lines of inquiry, comprising four empirical studies and employing both quantitative and qualitative methods, structure the research. The first line of inquiry focuses on practice-level dynamics of AI by examining the real-world use of AI chatbots. Based on semi-structured interviews, the two chapters in this line of inquiry explore the practical realities of AI adoption, implementation, and observed results within U.S. state agencies. The second line of inquiry takes a policy-level perspective, offering a broader view of AI use in government. The two chapters examine how public organizations should adopt, implement, and evaluate AI initiatives, based on a content analysis of state agency policies and a nationally representative survey of U.S. citizens.
Overall, this dissertation provides a comprehensive perspective on the use of AI in government, highlighting the various stakeholders and factors that influence the processes of adoption, implementation, and result evaluation. It demonstrates that, as an emerging technology, AI introduces distinct challenges at each phase, necessitating diverse strategies to ensure its deployment aligns with public values. It also identifies areas for further investigation to ensure that AI use remains accountable and responsive to citizens’ needs. Finally, the findings offer practical contributions by outlining key processes and strategies for the development of AI initiatives.
License
This work is licensed under the University at Albany Standard Author Agreement.
Recommended Citation
Chen, Tzuhao, "MANAGING ARTIFICIAL INTELLIGENCE IN THE PUBLIC SECTOR: ADOPTION, IMPLEMENTATION, AND RESULTS" (2025). Electronic Theses & Dissertations (2024 - present). 243.
https://scholarsarchive.library.albany.edu/etd/243
