The Adoption and Implementation of Artificial Intelligence Chatbots in Public Organizations: Evidence from U.S. State Governments

Tzuhao Chen, Mila Gascó-Hernandez, Marc Esteve

Research output: Indexed journal article Articlepeer-review

10 Citations (Scopus)

Abstract

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.

Original languageEnglish
Number of pages16
JournalAmerican Review of Public Administration
Early online dateSept 2023
DOIs
Publication statusE-pub ahead of print - Sept 2023

Keywords

  • AI adoption
  • AI implementation
  • artificial intelligence
  • Chatbot
  • innovation adoption
  • innovation implementation

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