Studies in Public Service Administration

Infrastructural Requirements for Artificial Intelligence Adoption in Public Organizations

Document Type : Original Article

Authors

Hadi Khanmohammadi 1
Niloufar Mozafari 2

1 Faculty of Public Administration, Faculty of Management and Accounting, Allameh Tabatabaei University, Tehran, Iran.

2 Faculty of Management and Accounting, Allameh Tabatabai University, Tehran, Iran

https://doi.org/10.22054/spsa.2026.90287.1102
Abstract
Despite the transformative role of AI in modernizing governance systems, many government organizations face challenges in successfully implementing this technology due to the lack of an appropriate platform. The main objective of this study is to identify and classify critical infrastructures for improving the level of readiness and successful deployment of AI in the public sector. The present study adopts a qualitative approach, utilizing McNabb’s process model and the thematic analysis method. For this purpose, scientific articles published in the period 2019 to 2025 in reputable databases (including Google Scholar and Web of Science) were screened, and finally 30 selected articles were analyzed. Data analysis showed that the ecosystem of AI readiness in the public sector is multidimensional in nature and requires balanced development in seven areas: information technology, data, organizational and management, legal and policymaking, cultural and social, economic and investment, and human resources.
While these infrastructures operate independently, they also interact and synergize with each other, forming the overall ecosystem required for the adoption, localization, and effective use of AI in public institutions. The findings show that creating interdisciplinary structures, data standardization, human resource training, flexible regulation, and sustainable financing are among the key requirements on the path to smart government.

Keywords

Big data
Public budgeting
Challenges and opportunities
Thematic analysis
Data-driven budgeting
Data-driven governance
  1. Adiguzel, Z., Sonmez Cakir, F., & Özbay, F. (2024). Examination of the effects of artificial intelligence readiness on lean sustainability and value creation in the mediation variable effect of organizational flexibility in technology-focused companies. Kybernetes. https://doi.org/10.1108/K-01-2024-0046
  2. Al-Alaq, A. (2025). The Oxford Insights Government AI Readiness Index (GARI): An Analysis of its Data and Overcoming Obstacles, with a Case Study of Iraq. https://doi.org/10.48550/arXiv.2503.20833
  3. Andrews, L. (2019). Algorithms, regulation, and governance readiness. In Algorithmic Regulation (pp. 245–270). Oxford University Press. https://doi.org/10.1093/oso/9780198838494.003.0009
  4. Androniceanu, A. (2024). Generative artificial intelligence, present and perspectives in public administration. Administration & Public Management Review, (43). https://doi.org/10.24818/amp/2024.43-06
  5. Chopra, D., & Sharma, A. (2025). Artificial Intelligence in E-governance-Enhancing efficiency and transparency.  https://dx.doi.org/10.2139/ssrn.5101270
  6. Dei, H. (2025). Artificial intelligence in public administration: benefits and risks. Management (Montevideo), 3, 137-137. https://doi.org/10.62486/agma2025137
  7. Eggers, W. D., Schatsky, D., & Viechnicki, P. (2017). AI-augmented government: Using cognitive technologies to redesign public sector work. Deloitte Insights.
  8. Glaser, B. G. (1992). Basics of grounded theory analysis: Emergence vs. forcing. Sociology Press.
  9. Grigalashvili, G. (2025). Artificial intelligence in public administration: An ethical dilemma. International Journal of Innovative Technologies in Social Science, 2(46). https://doi.org/10.31435/ijitss.2(46).2025.3436
  10. Kurhayadi, K. (2025). Evaluating the readiness of public institutions for AI-Driven decision making: A framework for adaptive governance. Edelweiss Applied Science and Technology, 9(4), 1569-1580. https://doi.org/10.55214/25768484.v9i4.6335
  11. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage Publications.
  12. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage.
  13. Madanchian, M., & Taherdoost, H. (2025). Barriers and Enablers of AI Adoption in Human Resource Management: A Critical Analysis of Organizational and Technological Factors. Information, 16(1), 51. https://doi.org/10.3390/info16010051
  14. McNabb, D. E. (2017). Research methods in public administration and nonprofit management. Routledge.
  15. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed). Sage.
  16. Neumann, O., Guirguis, K., & Steiner, R. (2024). Exploring artificial intelligence adoption in public organizations: a comparative case study. Public Management Review, 26(1), 114-141. http://dx.doi.org/10.1080/14719037.2024.2356444
  17. Poduval, M., Ghose, A., Manchanda, S., Bagaria, V., & Sinha, A. (2020). Artificial intelligence and machine learning: a new disruptive force in orthopaedics. Indian journal of orthopaedics, 54(2), 109-122. https://doi.org/10.1007/s43465-019-00023-3
  18. Pаламарчук, I. (2024). Artificial intelligence governance regulation in public administration. Наукові інновації та передові технології, 3(31), 73–81. https://doi.org/10.52058/2786-5274-2024-3(31)-73-81
  19. Sandeep, M.M., Lavanya, V. and Balakrishnan, J. (2025), "Leveraging AI in recruitment: enhancing intellectual capital through resource-based view and dynamic capability framework", Journal of Intellectual Capital, 26)2), 404-425. https://doi.org/10.1108/JIC-05-2024-0155
  20. Shah, S. I. H., Peristeras, V., & Magnisalis, I. (2021). Government big data ecosystem: definitions, types of data, actors, and roles and the impact in public administrations. ACM Journal of Data and Information Quality, 13(2), 1-25. https://doi.org/10.1108/JIC-05-2024-0155
  21. Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed). Sage.
  22. Stupin, R. S. (2024). AI Readiness Level in Public Administration: Case of the Russian Federation. RUDN Journal of Public Administration, 11(1), 157-172. https://doi.org/10.22363/2312-8313-2024-11-1-157-172
  23. Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.09.008
  24. Ulaşan, F. (2023). The Dark Side of Artificial Intelligence on the Basis of Public Administration. Toplum Ekonomi ve Yönetim Dergisi, 4(Özel), 301-323. https://doi.org/10.58702/teyd.1345570
  25. Ulnicane, I., Knight, W., Leach, T., Stahl, B. C., & Wanjiku, W. G. (2022). Governance of Artificial Intelligence: Emerging international trends and policy frames. In The global politics of Artificial Intelligence. Taylor & Francis. https://doi.org/10.1201/9780429446726-2?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle
  26. Van Noordt, C., & Medaglia, R. (2025). Policy initiatives for Artificial Intelligence-enabled government: An analysis of national strategies in Europe. Public Policy and Administration. https://doi.org/10.1177/09520767231198411
  27. Vatamanu, A. F., & Tofan, M. (2025). Integrating artificial intelligence into public administration: Challenges and vulnerabilities. Administrative Sciences, 15(4), 149. https://doi.org/10.3390/admsci15040149
  28. Walter, Y. (2024). Managing the race to the moon: Global policy and governance in Artificial Intelligence regulation—A contemporary overview and an analysis of socioeconomic consequences. Discov Artif Intell, 4(14). https://doi.org/10.1007/s44163-024-00109-4
  29. Weiner, B. J. (2009). A theory of organizational readiness for change. Implementation Science, 4(1), 67. https://doi.org/10.4337/9781788975995.00015
  30. Wirtz, B. W., & Müller, W. M. (2019). An integrated artificial intelligence framework for public management. Public Management Review, 21(7), 1076–1100. https://doi.org/10.1080/14719037.2018.1549268
  31. Wirtz, B. W., Langer, P. F., & Fenner, C. (2021). Artificial intelligence in the public sector-a research agenda. International Journal of Public Administration, 44(13), 1103-1128. https://doi.org/10.1080/01900692.2021.1947319
  32. Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector—applications and challenges. International Journal of Public Administration, 42(7), 596-615. https://doi.org/10.1080/01900692.2018.1498103
  33. Akbari, A. (2024). Artificial Intelligence Governance (3): Artificial Intelligence Capacities in Improving the Country's Administrative System. Monthly Expert Reports of the Islamic Consultative Assembly Research Center, 32(10), doi: 22034/report.mrc.2025.1403.32.10.20342[In Persian]
  34. Jafari, Z., Kheradmandnia, S., Malai, M., Rajabi, A., & Tavana, P. (2024). Artificial Intelligence Development and Regulation (2): Government Artificial Intelligence Readiness Index. Monthly Expert Reports of the Islamic Consultative Assembly Research Center, 32(8), doi: 22034/report.mrc.2024.1403.32.8.20142[In Persian]
  35. Roshen, S. A., Yaghoubi, N., & Momeni, A. (2021). Application of Artificial Intelligence in the Government Sector (A Meta-Synthesis Study). Quarterly Journal of the Iranian Management Sciences Association, 16(61), 117-145. [In Persian]
  36. Alemi Pasand, S., & Farahani, A. (2025). Capacity Building for Implementing Artificial Intelligence in Government Organizations. Tehran Municipality. [In Persian]
  37. Fartash, K., Khairy, A., & Baramki, T. (2024). Providing a Framework for Developing Artificial Intelligence Infrastructures in Iran with a Focus on Service Providers and AI Service Aggregators. Science and Technology Policy, 17(3), 9-25. doi: 22034/jstp.2025.11771.1815. [In Persian]
  38. McNabb, D. E. (2018). Research methods for political science: Quantitative and qualitative methods, (Vol. 2), (R. Vaezi & M. S. Azmandian, Trans.). Saffar Publications. (Original work published 2013). [In Persian]
Studies in Public Service Administration
Volume 3, Issue 10
Spring 2026
Pages 1-44

  • Receive Date 10 December 2025
  • Revise Date 05 February 2026
  • Accept Date 10 February 2026

Home

Editorial Boards

Submit Manuscript

Contact Us

Article Processing Charges