Artificial Intelligence Integration and Project Manager Efficiency in Public Sector Projects: The Moderating Role of Organizational Readiness in Pakistan
DOI:
https://doi.org/10.70670/sra.v4i1.1937Keywords:
Artificial Intelligence Integration, Project Manager Efficiency, Organizational Readiness, Public Sector Projects, Technology Adoption, Technology Acceptance ModelAbstract
Artificial intelligence (AI) has emerged as a transformative technology capable of improving managerial decision-making, coordination, and operational efficiency in project-based organizations. However, empirical research examining the influence of AI on managerial efficiency, particularly within public sector projects in developing economies, remains limited. This study investigates the relationship between artificial intelligence integration and project manager efficiency in Pakistani public sector projects while examining the moderating role of organizational readiness. The research is grounded in an integrated theoretical framework combining the Technology Acceptance Model (TAM), the Technology–Organization–Environment (TOE) framework, and Diffusion of Innovation (DOI) theory to explain how technological and organizational factors influence AI-enabled managerial outcomes. A quantitative research design was employed using a structured questionnaire distributed to project managers and senior project officials working in public sector project-based organizations in Pakistan. Data were analyzed using regression and moderation analysis to examine the direct effect of artificial intelligence integration on project manager efficiency and the moderating influence of organizational readiness. The results indicate that artificial intelligence integration significantly improves project manager efficiency by enhancing managers’ ability to process information, make timely decisions, coordinate project activities, and respond effectively to project uncertainties. Furthermore, the findings reveal that organizational readiness strengthens this relationship, as organizations with stronger leadership support, technological infrastructure, and skilled personnel are better able to translate AI-enabled systems into tangible managerial efficiency gains. These results highlight the importance of both technological capability and organizational preparedness in achieving successful digital transformation. The study contributes to the literature by examining managerial efficiency as a distinct outcome of AI integration and by providing empirical evidence from the public sector context of a developing economy. The findings also offer practical insights for policymakers and public sector managers seeking to enhance project management effectiveness through artificial intelligence initiatives.
References
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. (2023). How to improve firm performance using big data analytics capability and artificial intelligence. International Journal of Information Management, 71, 102478.
Almansour, A., Müller, R. M., & Nilsson, J. (2025). Impact of artificial intelligence on project management: Multi-expert perspectives on innovation and decision-making. Journal of Innovation & Knowledge, 10(5), 100772. https://doi.org/10.1016/j.jik.2025.100772
Almansour, A., Müller, R., & Nilsson, J. (2025). Impact of artificial intelligence on project management: Multi-expert perspectives on innovation and decision-making. Journal of Innovation & Knowledge, 10(5), 100772.
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, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P., Janssen, M., Jones, P., Kar, A., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. (2023). 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., Hughes, L., Ismagilova, E., et al. (2023). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
Flyvbjerg, B. (2017). The Oxford handbook of megaproject management. Oxford University Press.
Hossain, M., Akter, S., Uddin, M., & Dwivedi, Y. (2024). Artificial intelligence in project management: Opportunities, challenges, and research agenda. Technological Forecasting and Social Change, 196, 122870. https://doi.org/10.1016/j.techfore.2023.122870
Hossain, M., Akter, S., Uddin, M., & Dwivedi, Y. (2024). Artificial intelligence in project management: Opportunities, challenges and research agenda. Technological Forecasting and Social Change, 196, 122870.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human–AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/j.bushor.2018.03.007
Khan, A., & Ullah, R. (2021). Meticulous Inquest of Interplay Among Work Engagement, Emotional Exhaustion and Turnover Intentions. Pakistan Journal of Society, Education & Language, 7(1).
Khan, G. F., Moon, J., Swar, B., Zo, H., & Rho, J. J. (2023). E-government development in Pakistan: Opportunities and challenges. Electronic Government, an International Journal, 19(2), 129–148.
Marnewick, C. (2023). Artificial intelligence in project management: A systematic literature review and future research agenda. Project Leadership and Society, 4, 100072. https://doi.org/10.1016/j.plas.2023.100072
Mergel, I., Edelmann, N., & Haug, N. (2023). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 40(2), 101795. https://doi.org/10.1016/j.giq.2022.101795
Mergel, I., Edelmann, N., & Haug, N. (2023). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 40(2), 101795.
Mikalef, P., Gupta, M., & Boura, M. (2024). Artificial intelligence capability and firm performance: The role of organizational readiness. Information & Management, 61(1), 103739. https://doi.org/10.1016/j.im.2023.103739
Mikalef, P., Gupta, M., & Boura, M. (2024). Artificial intelligence capability and firm performance: The role of organizational readiness. Information & Management, 61(1), 103739.
Müller, R., & Lecoeuvre, L. (2014). Operationalizing governance categories of projects. International Journal of Project Management, 32(8), 1346–1357.
Müller, R., Nilsson, J., & Almansour, A. (2025). Impact of artificial intelligence on project management: Multi-expert perspectives on innovation and decision making. Journal of Innovation & Knowledge, 10(5), 100772.
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
Salaheldin, S., & Hussein, G. (2025). Artificial intelligence adoption and organizational performance: Evidence from digital transformation initiatives. Journal of Business Research, 178, 114234.
Salaheldin, S., & Hussein, G. (2025). Artificial intelligence adoption and organizational performance: Evidence from digital transformation initiatives. Journal of Business Research, 178, 114234.
Siddiqui, U. A., & Mehmood, W. (2021). E-government in Pakistan: Implementation and challenges. International Journal of Education and Management Engineering, 11(6), 10–19. https://doi.org/10.5815/ijeme.2021.06.02
Too, E., & Weaver, P. (2014). The management of project management: A conceptual framework for project governance. International Journal of Project Management, 32(8), 1382–1394.
Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
Turner, J. R. (2014). Handbook of project-based management (4th ed.). McGraw-Hill.
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2023). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901.
Verhoef, P. C., Broekhuizen, T., Bart, Y., et al. (2023). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901.
Vial, G. (2024). Understanding digital transformation: A review and research agenda. Journal of Strategic Information Systems, 33(1), 101770.
Vial, G. (2024). Understanding digital transformation: A review and research agenda. Journal of Strategic Information Systems, 33(1), 101770.
Wamba, S. F., Queiroz, M. M., & Trinchera, L. (2024). Dynamics between artificial intelligence capability and firm performance: The role of data-driven culture. International Journal of Information Management, 74, 102737.
Weiner, B. J. (2009). A theory of organizational readiness for change. Implementation Science, 4(67), 1–9. https://doi.org/10.1186/1748-5908-4-67
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
Zuiderwijk, A., Chen, Y. C., & Salem, F. (2021). Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda. Government Information Quarterly, 38(3), 101577. https://doi.org/10.1016/j.giq.2021.101577
Wamba, S. F., Queiroz, M. M., & Trinchera, L. (2024). Dynamics between artificial intelligence capability and firm performance. International Journal of Information Management, 74, 102737.
