PUBLIC ADMINISTRATION AND STRATEGIC DECISION-MAKING SUPPORT BASED ON ARTIFICIAL INTELLIGENCE: CONSTRAINING FACTORS

Authors

  • Edgars Cīrulis Vidzeme University of Applied Sciences, Valmiera, Latvia (LV)
  • Kaspars Osis Vidzeme University of Applied Sciences, Valmiera, Latvia (LV)

DOI:

https://doi.org/10.35363/ViA.sts.2025.144

Keywords:

public administration, decision-making support, artificial intelligence, constraining factors

Abstract

The importance of artificial intelligence is growing. The adoption of it in public administration has the potential to enhance transparency, efficiency, and responsiveness, ultimately creating greater public value (Babšek et al. 2025). Using artificial intelligence technologies in government improves policy-making processes, public service delivery, and the internal management of public administrations (van Noordt and Misuraca 2022). This study aims to analyse constraining factors that influence the strategic decision-making support within public administration based on artificial intelligence.

References

Babšek, M., Ravšelj, D., Umek, L., & Aristovnik, A. (2025). Artificial Intelligence Adoption in Public Administration: An Overview of Top-Cited Articles and Practical Applications. AI, 6(3), 44. https://doi.org/10.3390/ai6030044

Noordt, van, C., & Misuraca, G. (2022). Artificial Intelligence for the Public Sector: Results of Landscaping the Use of AI in Government across the European Union. Government Information Quarterly 39 (3), 101714. https://doi.org/10.1016/j.giq.2022.101714

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Published

04.11.2025

Issue

Vol. 3 (2025): SOCIETY. TECHNOLOGY. SOLUTIONS. Abstract Proceedings of the 5th International Scientific Conference.16.10.2025.

Section

Simulation and Prediction

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Cīrulis, E., & Osis, K. (2025). PUBLIC ADMINISTRATION AND STRATEGIC DECISION-MAKING SUPPORT BASED ON ARTIFICIAL INTELLIGENCE: CONSTRAINING FACTORS. SOCIETY. TECHNOLOGY. SOLUTIONS. Proceedings of the International Scientific Conference, 3, 72-73. https://doi.org/10.35363/ViA.sts.2025.144