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

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.

Keywords

Chatbot artificial intelligence AI adoption AI implementation innovation adoption innovation implementation

Get full access to this article

View all access options for this article.

References

Alford

R. R.

(1998). The craft of inquiry: Theories, methods, evidence. Oxford University Press.

Androutsopoulou

Karacapilidis

Loukis

Charalabidis

(2019). Transforming the communication between citizens and government through AI-guided chatbots. Government Information Quarterly, 36(2), 358–367. https://doi.org/10.1016/j.giq.2018.10.001

Anthopoulos

Reddick

C. G.

Giannakidou

Mavridis

(2016). Why e-government projects fail? An analysis of the Healthcare.gov website. Government Information Quarterly, 33(1), 161–173. https://doi.org/10.1016/j.giq.2015.07.003

Aoki

(2020). An experimental study of public trust in AI chatbots in the public sector. Government Information Quarterly, 37(4), 101490. https://doi.org/10.1016/j.giq.2020.101490

Baldauf

Zimmermann

H.-D.

(2020). Towards conversational E-government: An experts’ perspective on requirements and opportunities of voice-based citizen services. In Nah

F. F.-H.

Siau

(Eds.), HCI in business, government and organizations (Vol. 12204, pp. 3–14). Springer International Publishing.

Baumgartner

F. R.

Jones

B. D.

(1991). Agenda dynamics and policy subsystems. The Journal of Politics, 53(4), 1044. al of Politicsicy Subsystems. 1). ed Le. https://doi.org/10.2307/2131866

Baumgartner

F. R.

Jones

B. D.

(1993). Agendas and instability in American politics. University of Chicago Press.

Blank

J. D.

Osofsky

(2020). Automated legal guidance. Cornell Law Review, 106(1), 179–245.

Borins

(2001). Encouraging innovation in the public sector. Journal of Intellectual Capital, 2(3), 310–319. https://doi.org/10.1108/14691930110400128

10.

Boushey

(2012). Punctuated equilibrium theory and the diffusion of innovations. Policy Studies Journal, 40(1), 127–146. https://doi.org/10.1111/j.1541-0072.2011.00437.x

11.

Campion

Gasco-Hernandez

Mikhaylov

S. J.

Esteve

(2020). Managing artificial intelligence deployment in the public sector. Computer, 53(10), 28–37. https://doi.org/10.1109/MC.2020.2995644

12.

Campion

Gasco-Hernandez

Mikhaylov

S. J.

Esteve

(2022). Overcoming the challenges of collaboratively adopting artificial intelligence in the public sector. Social Science Computer Review, 40(2), 462–477. https://doi.org/10.1177/0894439320979953

13.

Cantador

Viejo-Tardío

Cortés-Cediel

M. E.

Rodríguez Bolívar

M. P.

(2021). A chatbot for searching and exploring open data: Implementation and evaluation in E-government. In DG.O 2021: The 22nd annual international conference on digital government research (pp. 168–179).

14.

Carvalho

N. R.

Barbosa

L. S.

(2019). Deep learning powered question-answering framework for organizations digital transformation. In Proceedings of the 12th international conference on theory and practice of electronic governance (pp. 76–79).

15.

Chan

C. M. L.

Lau

Pan

S. L.

(2008). E-government implementation: A macro analysis of Singapore’s e-government initiatives. Government Information Quarterly, 25(2), 239–255. https://doi.org/10.1016/j.giq.2006.04.011

16.

Dale

(2016). The return of the chatbots. Natural Language Engineering, 22(5), 811–817. https://doi.org/10.1017/S1351324916000243

17.

Davis

F. D.

(1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008

18.

De Vries

Bekkers

Tummers

(2016). Innovation in the public sector: A systematic review and future research agenda. Public Administration, 94(1), 146–166. https://doi.org/10.1111/padm.12209

19.

de Vries

Tummers

Bekkers

(2018). The diffusion and adoption of public sector innovations: A meta-synthesis of the literature. Perspectives on Public Management and Governance, 1(3), 159–176. https://doi.org/10.1093/ppmgov/gvy001

20.

DiMaggio

P. J.

Powell

W. W.

(1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147. https://doi.org/10.2307/2095101

21.

Eom

S.-J.

Lee

(2022). Digital government transformation in turbulent times: Responses, challenges, and future direction. Government Information Quarterly, 39(2), 101690. https://doi.org/10.1016/j.giq.2022.101690

22.

Fischer

Siegel

Proeller

Drathschmidt

(2023). Resilience through digitalisation: How individual and organisational resources affect public employees working from home during the COVID-19 pandemic. Public Management Review, 25(4), 808–835. https://doi.org/10.1080/14719037.2022.2037014

23.

Frumkin

Galaskiewicz

(2004). Institutional isomorphism and public sector organizations. Journal of Public Administration Research and Theory, 14(3), 283–307. https://doi.org/10.1093/jopart/muh028

24.

Gartner (2021). Gartner Says Government Organizations Are Increasing Investment in AI, But Their Workforce Remains Apprehensive . https://www.gartner.com/en/newsroom/press-releases/2021-10-05-gartner-says-government-organizations-are-increasing-

25.

Gascó Hernández

Ysa Figueras

Longo Martínez

Fernández Ple

(2013). La gestió de la interoperabilitat en govern electrònic a les administraciones publiques catalanes (Electronic government interoperability in Catalan public organizations). Escola d’Administració Pública de Catalunya.

26.

Gichoya

(2005). Factors affecting the successful implementation of ICT projects in government. The Electronic Journal of E-Government, 3(4), 175–184.

27.

Gil-Garcia

J. R.

(2012). Electronic government success: Definition, measures, and factors. In Gil-Garcia

J. R.

(Ed.), Enacting electronic government success (pp. 1–32). Springer US.

28.

Gkeredakis

Lifshitz-Assaf

Barrett

(2021). Crisis as opportunity, disruption and exposure: Exploring emergent responses to crisis through digital technology. Information and Organization, 31(1), 100344. https://doi.org/10.1016/j.infoandorg.2021.100344

29.

Glyptis

Christofi

Vrontis

Giudice

M. D.

Dimitriou

Michael

(2020). E-government implementation challenges in small countries: The project manager’s perspective. Technological Forecasting and Social Change, 152, 119880. https://doi.org/10.1016/j.techfore.2019.119880

30.

Heeks

(2006). Understanding and Measuring eGovernment: International Benchmarking Studies. UNDESA Workshop “E-Participation and E-Government: Understanding the Present and Creating the Future,” Budapest, Hungary.

31.

(2018). Preparing public managers for the digital era: Incorporating information management, use, and technology into public affairs graduate curricula. Public Management Review, 20(5), 766–787. https://doi.org/10.1080/14719037.2017.1327180

32.

Jun

K.-N.

Weare

(2011). Institutional motivations in the adoption of innovations: The case of E-government. Journal of Public Administration Research and Theory, 21(3), 495–519. https://doi.org/10.1093/jopart/muq020

33.

Keyner

Savenkov

Vakulenko

(2019). Open data chatbot. In Hitzler

Kirrane

Hartig

de Boer

Vidal

M.-E.

Maleshkova

Schlobach

Hammar

Lasierra

Stadtmüller

Hose

Verborgh

(Eds.), The semantic web: ESWC 2019 satellite events (Vol. 11762, pp. 111–115). Springer International Publishing.

34.

Kumar

Best

M. L.

(2006). Impact and sustainability of E-government services in developing countries: Lessons learned from Tamil Nadu, India. The Information Society, 22(1), 1–12. https://doi.org/10.1080/01972240500388149

35.

Lommatzsch

(2018). A next generation chatbot-framework for the public administration. In Hodoň

Eichler

Erfurth

Fahrnberger

(Eds.), Innovations for community services (Vol. 863, pp. 127–141). Springer International Publishing.

36.

Makasi

Nili

Desouza

Tate

(2020). Chatbot-mediated public service delivery. First Monday, 25(12). https://doi.org/10.5210/fm.v25i12.10598

37.

Makasi

Nili

Desouza

K. C.

Tate

(2022). A typology of chatbots in public service delivery. IEEE Software, 39(3), 58–66. https://doi.org/10.1109/MS.2021.3073674

38.

Maxwell

J. A.

Chmiel

(2014). Generalization in and from qualitative analysis. In Flick

(Ed.), The SAGE handbook of qualitative data analysis (pp. 540–553). Sage Publications, Inc.

39.

Mehr

(2017). Artificial intelligence for citizen services and government. Harvard Kennedy School, Ash Center for Democratic Governance And Innovation. https://ash.harvard.edu/files/ash/files/artificial_intelligence_for_citizen_services.pdf

40.

Miller

(2020). Government Chatbots Now a Necessity for States, Cities, Counties. GovTech. https://www.govtech.com/products/Government-Chatbots-Now-a-Necessity-for-States-Cities-Counties.html

41.

Moore

(2019). Top Trends From Gartner Hype Cycle For Digital Government Technology 2019. Gartner. https://www.gartner.com/smarterwithgartner/top-trends-from-gartner-hype-cycle-for-digital-government-technology-2019

42.

NASCIO (2020). Chat with us: How states are using chatbots to respond to the demands of COVID-19 (pp. 1–8). National Association of State Chief Information Officers (NASCIO).

43.

Neumann

Guirguis

Steiner

(2022). Exploring artificial intelligence adoption in public organizations: A comparative case study. Public Management Review, 1–27. https://doi.org/10.1080/14719037.2022.2048685

44.

Nurdin

Stockdale

Scheepers

(2014). The role of social actors in the sustainability of E-government implementation and use: Experience from Indonesian regencies. In 2014 47th hawaii international conference on system sciences (pp. 2263–2272).

45.

Patton

M. Q.

(2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). Sage Publishing.

46.

Petriv

Erlenheim

Tsap

Pappel

Draheim

(2020). Designing effective chatbot solutions for the public sector: A case study from Ukraine. In Chugunov

Khodachek

Misnikov

Trutnev

(Eds.), 6th International conference on electronic governance and open society: Challenges in Eurasia (EGOSE 2019) (pp. 320–335). Springer International Publishing.

47.

Phillips

Roehrich

J. K.

Kapletia

(2021). Responding to information asymmetry in crisis situations: Innovation in the time of the COVID-19 pandemic. Public Management Review, 1–24. https://doi.org/10.1080/14719037.2021.1960737

48.

Picazo-Vela

Gutiérrez-Martínez

Duhamel

Luna

D. E.

Luna-Reyes

L. F.

(2018). Value of inter-organizational collaboration in digital government projects. Public Management Review, 20(5), 691–708. https://doi.org/10.1080/14719037.2017.1305702

49.

Powell

W. W.

DiMaggio

(Eds.). (1991). The new institutionalism in organizational analysis. University of Chicago Press.

50.

Quaintance

(2017). Rise of the Government Chatbot. GovTech. https://www.govtech.com/civic/Rise-of-the-Government-Chatbot.html

51.

Saldaña

(2015). The coding manual for qualitative researchers (3rd ed.). Sage Publishing

52.

Schramm

(1974). Notes on Case Studies of Instructional Media Projects. Working Paper for the Academy of Educational Development, Washington, DC.

53.

Shawar

B. A.

Atwell

(2007). Chatbots: Are they really useful? Journal for Language Technology and Computational Linguistics, 22(1), 29–49. https://doi.org/10.21248/jlcl.22.2007.88

54.

Stromback

Kiousis

(Eds.). (2011). Political public relations: Principles and applications (1st ed.). Routledge.

55.

The Government Digital Service (2020). A guide to using artificial intelligence in the public sector.

56.

van Noordt

Misuraca

(2019). New wine in old bottles: Chatbots in government: Exploring the transformative impact of chatbots in public service delivery. In Panagiotopoulos

Edelmann

Glassey

Misuraca

Parycek

Lampoltshammer

(Eds.), Electronic participation (Vol. 11686, pp. 49–59). Springer International Publishing.

57.

Wang

Lin

Shao

(2022). How does artificial intelligence create business agility? Evidence from chatbots. International Journal of Information Management, 66, 102535. https://doi.org/10.1016/j.ijinfomgt.2022.102535

58.

Wang

Zhang

Zhao

(2022). Understanding the determinants in the different government AI adoption stages: Evidence of local government chatbots in China. Social Science Computer Review, 40(2), 534–554. https://doi.org/10.1177/0894439320980132

59.

Wright

(2021). The Alexafication of adult social care: Virtual assistants and the changing role of local government in England. International Journal of Environmental Research and Public Health, 18(2), 812. https://doi.org/10.3390/ijerph18020812

60.

Yin

R. K.

(2013). Case study research: Design and methods (Rev.). Sage Publishing.

61.

Yuan

Gasco-Hernandez

Gil-Garcia

Cook

Pardo

(2023). Continuity of operations and organisational resilience during the COVID-19 pandemic: Lessons from city governments in the US Northeast region. Public Management Review, 1–21. https://doi.org/10.1080/14719037.2023.2222763

62.

Zhang

J. J. Y.

Følstad

Bjørkli

C. A.

(2023). Organizational factors affecting successful implementation of chatbots for customer service. Journal of Internet Commerce, 22(1), 122–156. https://doi.org/10.1080/15332861.2021.1966723