The Adoption and Implementation of Artificial Intelligence Chatbots in Public Organizations

Evidence from U.S. State Governments

Bibliographic Data

ID11674279
AuthorsTzuhao Chen (0000-0001-5570-7626, University at Albany, State University of New York, corresponding author), Mila Gascó-Hernández (0000-0002-6308-8519, University at Albany, State University of New York), Marc Esteves (0000-0002-9732-8082, School of Public Policy, University College London, London, UK)
Year2023
Volume54
Issue3
Pages255-270
Publication date2023-09-11
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe American Review of Public Administration (JOURNAL)
Journal identifiersISSN: 0275-0740 • E-ISSN: 1552-3357
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/02750740231200522
OpenAlexW4386719165
LanguageEN
Citations received32
References cited44

Although the use of artificial intelligence (AI) chatbots in public organizations has increased in recent years, three crucial gaps remain unresolved. First, little empirical evidence has been produced to examine the deployment of chatbots in government contexts. Second, existing research does not distinguish clearly between the drivers of adoption and the determinants of success and, therefore, between the stages of adoption and implementation. Third, most current research does not use a multidimensional perspective to understand the adoption and implementation of AI in government organizations. Our study addresses these gaps by exploring the following question: what determinants facilitate or impede the adoption and implementation of chatbots in the public sector? We answer this question by analyzing 22 state agencies across the U.S.A. that use chatbots. Our analysis identifies ease of use and relative advantage of chatbots, leadership and innovative culture, external shock, and individual past experiences as the main drivers of the decisions to adopt chatbots. Further, it shows that different types of determinants (such as knowledge-base creation and maintenance, technology skills and system crashes, human and financial resources, cross-agency interaction and communication, confidentiality and safety rules and regulations, and citizens’ expectations, and the COVID-19 crisis) impact differently the adoption and implementation processes and, therefore, determine the success of chatbots in a different manner. Future research could focus on the interaction among different types of determinants for both adoption and implementation, as well as on the role of specific stakeholders, such as IT vendors

Agency (philosophy · Business · Chatbot · Economics · Empirical evidence · Empirical research · Government (linguistics · Knowledge management · Political science · Public relations · Public sector · Sociology · Software deployment · Computer Science · E-Government and Public Services · Privacy, Security, and Data Protection · Smart Cities and Technologies · Marketing