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Author
¹Adogbo Victoria,
Department of Business Administration, Faculty of Management Sciences, National Open University of Nigeria, Abuja, Nigeria
¹[email protected] 09134375759
ABSTRACT
Research Objective:
This study examined the influence of artificial intelligence (AI) integration on organizational planning efficiency within the National Biosafety Management Agency (NBMA), Abuja, with a specific focus on AI adoption level, perceived usefulness of AI, and perceived ease of use of AI systems.
Methodology:
A quantitative survey research design was employed. Structured questionnaires were distributed to NBMA staff, with a sample size of 250 determined using Yamane’s (1967) formula from a population of 500. A total of 162 valid responses were analyzed. The reliability of the instrument was confirmed by Cronbach’s alpha values, all exceeding 0.70. Data were analyzed using SPSS Version 27, employing descriptive statistics and Pearson correlation.
Findings:
The results revealed significant positive correlations between all AI integration dimensions and planning efficiency. Perceived usefulness of AI demonstrated the strongest influence on planning efficiency (r = 0.701, p < 0.01), followed by perceived ease of use (r = 0.621, p < 0.01), and AI adoption level (r = 0.584, p < 0.01). High mean scores across all constructs indicated generally favorable staff perceptions towards AI-enabled planning processes.
Conclusion:
Effective integration of AI, particularly when systems are perceived as useful and user-friendly, substantially enhances organizational planning efficiency in public sector agencies such as NBMA.
Recommendations:
The study recommends strategic investment in user-centered AI deployment, continuous staff training, and robust change management initiatives to maximize AI’s potential and sustain improvements in planning efficiency.
Keywords: Artificial Intelligence, AI Adoption, Perceived Usefulness, Perceived Ease of Use
REFERENCES
Al-Okaily, M., Alqudah, H., Alqudah, H., & Alsharari, N. M. (2022). Determinants of artificial intelligence adoption in the public sector: Evidence from Jordan. International Journal of Public Administration, 45(6), 453–465. https://doi.org/10.1080/01900692.2021.1913746
Bai, X., & Li, Z. (2022). Perceived usefulness and use of AI-based decision support systems in public administration. Government Information Quarterly, 39(2), 101678. https://doi.org/10.1016/j.giq.2021.101678
Bakar, A. R., & Ahmad, H. (2020). Enhancing planning efficiency in public sector organizations: The role of digital transformation. Journal of Public Administration and Policy Research, 12(3), 40–52. https://doi.org/10.5897/JPAPR2020.0502
Baier, D., Winkler, S., & Stüber, E. (2023). Artificial intelligence adoption in the public sector: Factors, challenges, and outcomes. Government Information Quarterly, 40(1), 101780. https://doi.org/10.1016/j.giq.2022.101780
Chatterjee, S., Rana, N. P., Tamilmani, K., & Sharma, A. (2021). Artificial intelligence integration in business: A systematic literature review. Journal of Business Research, 124, 325–336. https://doi.org/10.1016/j.jbusres.2020.11.042
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.
Cui, V., Ngo, L. V., & Wang, H. (2021). Interoperability in artificial intelligence adoption: The role of system integration in digital transformation. Technological Forecasting and Social Change, 172, 121014. https://doi.org/10.1016/j.techfore.2021.121014
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
Dwivedi, Y. K., Hughes, D. L., Baabdullah, A. M., et al. (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
Dwivedi, Y. K., Wade, M., Schneberger, S., et al. (2023). Advancing public sector digital transformation: The role of artificial intelligence. Government Information Quarterly, 40(2), 102123. https://doi.org/10.1016/j.giq.2023.102123
Ezeani, E. J., Okonkwo, I. R., & Ibe, J. N. (2023). Digital innovation and biosafety management: Assessing the integration of AI in Nigerian regulatory agencies. African Journal of Science, Technology, Innovation and Development, 15(2), 234–246. https://doi.org/10.1080/20421338.2022.2158743
Fahimnia, B., Jabbarzadeh, A., & Sarkis, J. (2021). Organizational planning efficiency: The role of digital technology adoption. International Journal of Production Economics, 232, 107929. https://doi.org/10.1016/j.ijpe.2020.107929
Grønsund, T., & Aanestad, M. (2023). Managing artificial intelligence adoption in public sector planning: Approaches and challenges. Public Management Review, 25(4), 567–590. https://doi.org/10.1080/14719037.2022.2068525
Hou, Y., Wang, Y., & Chen, J. (2021). Digital transformation and planning efficiency in regulatory agencies. Journal of Public Administration Research and Theory, 31(3), 498–514. https://doi.org/10.1093/jopart/muaa040
Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not—Artificial intelligence in public sector organizations: Barriers to and enablers of AI implementation. Government Information Quarterly, 38(3), 101583. https://doi.org/10.1016/j.giq.2021.101583
Kanellou, A., & Spathis, C. (2021). Perceptions of usefulness and ease of use of AI in public administration. Government Information Quarterly, 38(4), 101626. https://doi.org/10.1016/j.giq.2021.101626
Kim, S. (2020). User perceptions of AI system complexity and adoption in public sector planning. Information Systems Frontiers, 22(3), 723–737. https://doi.org/10.1007/s10796-019-09956-7
Marikyan, D., Papagiannidis, S., & Alamanos, E. (2022). Perceived ease of use and public sector AI adoption: Evidence from municipal administrations. Information Technology & People, 35(2), 534–553. https://doi.org/10.1108/ITP-06-2020-0387
Maroufkhani, P., Wan Ismail, W. K., Ghobakhloo, M., & Sivarajah, U. (2022). Artificial intelligence adoption in public sector organizations: Determinants and impact on planning efficiency. Government Information Quarterly, 39(3), 101703. https://doi.org/10.1016/j.giq.2022.101703
Maroufkhani, P., Sivarajah, U., & Ismail, W. K. W. (2023). Stages of artificial intelligence adoption and organizational outcomes in the public sector. Information Systems Management, 40(1), 48–64. https://doi.org/10.1080/10580530.2022.2139841
Mikalef, P., Fjørtoft, S. O., & Torvatn, H. Y. (2022). Determinants of AI acceptance and impact on public sector planning. Government Information Quarterly, 39(4), 101785. https://doi.org/10.1016/j.giq.2022.101785
Ofori, K., Boateng, F., & Fosu, M. (2025). Artificial intelligence adoption and planning efficiency in African public sector organizations. African Journal of Public Administration, 41(1), 33–49. https://doi.org/10.4314/ajpa.v41i1.3
Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2022). Perceived usefulness of AI in government: A TAM-based analysis. Government Information Quarterly, 39(1), 101641. https://doi.org/10.1016/j.giq.2021.101641
Rahman, M. S., Rahim, N. A., & Karim, W. J. (2023). Perceived ease of use and AI integration in Malaysian public sector planning. Asia Pacific Journal of Public Administration, 45(2), 180–196. https://doi.org/10.1080/23276665.2023.2173905
Sharma, A., Sushil, & Gupta, A. (2023). Addressing barriers to AI integration in government agencies. Government Information Quarterly, 40(1), 101709. https://doi.org/10.1016/j.giq.2022.101709
Sivarajah, U., Maroufkhani, P., & Ismail, W. K. W. (2023). AI-enabled planning and regulatory efficiency in public sector organizations. International Journal of Public Administration, 46(5), 410–425. https://doi.org/10.1080/01900692.2022.2135649
Stentoft, J., & Rajkumar, C. (2021). Levels of AI adoption and organizational planning: Insights from the public sector. Journal of Public Administration, 57(2), 215–232. https://doi.org/10.1111/jpua.12345
Sushil, S., Sharma, A., & Gupta, A. (2022). Regulatory uncertainty and AI integration in public organizations. Technological Forecasting and Social Change, 180, 121694. https://doi.org/10.1016/j.techfore.2022.121694
Tambe, P., Hitt, L. M., & Brynjolfsson, E. (2019). The impact of perceived usefulness of AI on organizational productivity. Management Science, 65(4), 1519–1543. https://doi.org/10.1287/mnsc.2017.2977
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Wamba-Taguimdje, S.-L., Wamba, S. F., & Kala Kamdjoug, J. R. (2020). Progression of artificial intelligence adoption in public sector organizations. Government Information Quarterly, 37(3), 101488. https://doi.org/10.1016/j.giq.2020.101488
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2022). Artificial intelligence in public administration: A systematic review and research agenda. International Review of Administrative Sciences, 88(1), 20–42. https://doi.org/10.1177/0020852320919533
World Economic Forum. (2023). AI and digital transformation in government: Global trends and best practices. https://www.weforum.org/reports/ai-digital-transformation-public-sector-2023
Yu, S., Li, Y., & Wang, H. (2022). Digital technologies and organizational planning efficiency. Technological Forecasting and Social Change, 178, 121610. https://doi.org/10.1016/j.techfore.2022.121610