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Leveraging AI for Enhanced eGovernment: Optimizing the Use of Open Governmental Data

Author

Listed:
  • Maro Androutsopoulou

    (National Technical University of Athens (NTUA))

  • Dimitrios Askounis

    (National Technical University of Athens (NTUA))

  • Elias G. Carayannis

    (George Washington University)

  • Nikos Zotas

    (University of the Aegean (UNI AEGEAN))

Abstract

Artificial intelligence (AI) is rapidly transforming various sectors and holds significant potential for improving government operations, specifically in the realm of eGovernment. This paper explores how AI can pave the way for Gov4 by optimizing the use of open governmental data. Despite AI’s limited adoption in the public sector, it presents a disruptive technology that can drive transparency, innovation, and economic growth. This study examines pioneering governments that have successfully integrated AI to handle and open governmental data, assesses the challenges they faced, and provides recommendations to achieve the desired outcomes.

Suggested Citation

  • Maro Androutsopoulou & Dimitrios Askounis & Elias G. Carayannis & Nikos Zotas, 2025. "Leveraging AI for Enhanced eGovernment: Optimizing the Use of Open Governmental Data," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(3), pages 12998-13033, September.
  • Handle: RePEc:spr:jknowl:v:16:y:2025:i:3:d:10.1007_s13132-024-02317-w
    DOI: 10.1007/s13132-024-02317-w
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    References listed on IDEAS

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    1. Elias G. Carayannis & Dirk Meissner & Anastasia Edelkina, 2017. "Targeted innovation policy and practice intelligence (TIP2E): concepts and implications for theory, policy and practice," The Journal of Technology Transfer, Springer, vol. 42(3), pages 460-484, June.
    2. Elpida Samara & Pavlos Kilintzis & Efthymios Katsoras & George Martnidis & Paraskevi Kosti, 2024. "A system dynamics approach for the development of a Regional Innovation System," Journal of Innovation and Entrepreneurship, Springer, vol. 13(1), pages 1-22, December.
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