Perceptions and Experiences of Local Administrative Officials Regarding the Integration of Artificial Intelligence in Public Service Delivery
Article Sidebar
Main Article Content
Abstract
This research aims to investigate the perceptions and experiences of Local Administrative Organization (LAO) officials regarding the integration of Artificial Intelligence (AI) into public service delivery. Employing a qualitative research methodology, data were collected through in-depth interviews with 18 key informants from LAOs in Chonburi Province. Thematic analysis was utilized for data interpretation. The findings reveal that officials’ perceptions of AI are dichotomous: while there are high expectations regarding AI’s potential to enhance efficiency and transparency, there is significant anxiety concerning job security and technological displacement. Furthermore, officials’ direct experience with AI remains very limited, highlighting a substantial gap between policy and practice. The primary structural barriers to AI integration include budget constraints, a shortage of technical experts, and insufficient support from the central government. The study suggests that future success hinges on two critical factors: strong executive commitment and systematic workforce skill development. This research recommends that the central government develop specialized AI strategies and platforms for local authorities, while LAO executives must lead the transformation through small-scale pilot projects to foster organizational acceptance and collective learning.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Views and opinions appearing in articles in the Journal of Arts of Management It is the responsibility of the author of the article. and does not constitute the view and responsibility of the editorial team I agree that the article is copyright of the Arts and Management Journal.
References
Ahmed, S. K., Mohammed, R. A., Nashwan A. J., Ibrahim, R. H., Abdalla, A. Q., Ameen, M. M., & Khdhir, R. M. (2025). Using thematic analysis in qualitative research. Journal of Medicine, Surgery, and Public Health, 6, 100198. https://doi.org/10.1016/j.glmedi.2025.100198
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: choosing among five approaches (4th ed.). Sage.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Digital Government Development Agency (Public Organization). (2021, January 15). Thailand’s digital government development plan 2020-2022. Digital Government Development Agency. https://www.dga.or.th/policy-standard/policy-regulation/dga-019/dga-024/
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., Medaglia, R., Le Meunier-FitzHugh, K., Le Meunier-FitzHugh, L. C., Misra, S., Mogaji, E., Sharma, S. K., Singh, J. B., Raghavan, V., Raman, R., Rana, N. P., Samothrakis, S., Spencer, J., Tamilmani, K., Tubadji, A., Walton, P., & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Lertsukekasem, T. (2022) The digital transformation of the Thai governmental agency: study the case of the ministry of foreign affairs under the framework of Thailand's masterplan on digital government B.E. 2563 - 2565[Independent Study, Chulalongkorn University].
https://digital.car.chula.ac.th/chulaetd/8352
Medaglia, R., Gil-Garcia, J. R., & Pardo, T. A. (2023). Artificial intelligence in government: Taking stock and moving forward. Social Science Computer Review, 41(1), 123–140. https://doi.org/10.1177/08944393211034087
Piwkham, G., Wanghmuklang, W., & Phothisai, C. (2024). Adapting local administrative organizations to bureaucracy 4.0 based on innovation. Journal of Administration Management and Sustainable Development, 2(3), 689-701. https://so15.tci-thaijo.org/index.php/jamsd/article/view/1134
Pulijala, S. (2024). Artificial intelligence in governance: opportunities, challenges, and ethical implications for public administration. International Journal for Multidisciplinary Research, 6(6), 1-10. https://doi.org/10.36948/ijfmr.2024.v06i06.29990
Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Sutthajitto (Sukhampha), P., Dangpron S., Kulee, K., & Chutinthawong, S. (2023). Guidelines for developing the administration of local government organizations. Journal of Administration Management and Sustainable Development, 1(3), 279–289.
https://so15.tci-thaijo.org/index.php/jamsd/article/view/288
Tamilmani, K. & Rana, N. P., & Dwivedi, Y. K. (2020). Consumer acceptance and use of information technology: A meta-analytic evaluation of UTAUT2. Information Systems Frontiers, 23, 987–1005. https://doi.org/10.1007/s10796-020-10007-6
Tveita, L. J., & Hustad, E. (2025). Benefits and challenges of artificial intelligence in public sector: A literature review. Procedia Computer Science, 256, 222-229. https://doi.org/10.1016/j.procs.2025.02.115
