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Artificial Intelligence and the Public Sector—Applications and Challenges

Author

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  • Bernd W. Wirtz
  • Jan C. Weyerer
  • Carolin Geyer

Abstract

Advances in artificial intelligence (AI) have attracted great attention from researchers and practitioners and have opened up a broad range of beneficial opportunities for AI usage in the public sector. Against this background, there is an emerging need for a holistic understanding of the range and impact of AI-based applications and associated challenges. However, previous research considers AI applications and challenges only in isolation and fragmentarily. Given the lack of a comprehensive overview of AI-based applications and challenges for the public sector, our conceptual approach analyzes and compiles relevant insights from scientific literature to provide an integrative overview of AI applications and related challenges. Our results suggest 10 AI application areas, describing their value creation and functioning as well as specific public use cases. In addition, we identify four major dimensions of AI challenges. We finally discuss our findings, deriving implications for theory and practice and providing suggestions for future research.

Suggested Citation

  • Bernd W. Wirtz & Jan C. Weyerer & Carolin Geyer, 2019. "Artificial Intelligence and the Public Sector—Applications and Challenges," International Journal of Public Administration, Taylor & Francis Journals, vol. 42(7), pages 596-615, May.
    • Handle: RePEc:taf:lpadxx:v:42:y:2019:i:7:p:596-615
    DOI: 10.1080/01900692.2018.1498103
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    Cited by:

    1. Araz Taeihagh, 2021. "Governance of artificial intelligence [Application of artificial intelligence for development of intelligent transport system in smart cities]," Policy and Society, Darryl S. Jarvis and M. Ramesh, vol. 40(2), pages 137-157.
    2. El Bhilat, El Mehdi & El Jaouhari, Asmae & Hamidi, L. Saadia, 2024. "Assessing the influence of artificial intelligence on agri-food supply chain performance: the mediating effect of distribution network efficiency," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Nam, Jinyoung & Kim, Junghwan & Jung, Yoonhyuk, 2023. "Understandings of the AI business ecosystem in South Korea: AI startups' perspective," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 278005, International Telecommunications Society (ITS).
    4. Livia Sz. Oláh & Rudolf Richter & Irena Kotowska, 2023. "Introduction to the Special Collection on The new roles of women and men and implications for families and societies," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(29), pages 849-866.
    5. Liu, Min & Liu, Hong-Fei & Lee, Chien-Chiang, 2024. "An empirical study on the response of the energy market to the shock from the artificial intelligence industry," Energy, Elsevier, vol. 288(C).
    6. John, Laura, 2022. "Rethinking digital governance - How collaborative innovation strategies advance the development of digital innovations in public organisations," Junior Management Science (JUMS), Junior Management Science e. V., vol. 7(5), pages 1400-1418.
    7. Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.

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