Building a Future-Ready Public Sector with AI: Enabling an Actionable AI Framework
Isi Artikel Utama
Abstrak
As ASEAN economies pursue inclusive and sustainable growth, Artificial Intelligence (AI) has emerged as a significant disruptive force in public sector transformation, reshaping decision-making and strategic planning. Despite its potential to streamline processes and enhance service delivery, AI adoption within the Malaysian public sector remains under-optimised. While the 2024 Government AI Readiness Index ranks Malaysia second in ASEAN and 23rd globally, the country has declined in the Chandler Good Government Index particularly in the innovation indicator, where it falls below the global average. In light of these trends, it is vital for the Malaysian government to understand the key factors influencing AI adoption among public sector managers, who act as pivotal change agents in implementing AI-related policies and navigating adoption challenges. This study addresses that need by employing the Unified Theory of Acceptance and Use of Technology (UTAUT), extended with AI literacy as a moderating variable. Drawing on survey data from 402 public sector managers in Putrajaya, Kuala Lumpur, and Selangor, the findings show that Performance Expectancy is the strongest predictor of AI adoption, followed by Effort Expectancy and Facilitating Conditions. Although Social Influence is statistically significant, its impact is weaker, reflecting the hierarchical and compliance-driven nature of Malaysia’s public sector. Notably, AI literacy moderates this relationship, with digitally literate managers exhibiting greater autonomy and confidence in AI-related decision-making. In response to these findings, the study proposes an actionable AI framework to support strategic and sustainable adoption. The framework offers a practical model for strengthening institutional capabilities, fostering data-driven governance, and building a future-ready public sector aligned with ASEAN’s digital transformation agenda.
##plugins.themes.bootstrap3.displayStats.downloads##
Rincian Artikel
Artikel ini berlisensiCreative Commons Attribution-ShareAlike 4.0 International License.
https://creativecommons.org/licenses/by-sa/4.0/
Referensi
Abdul Aziz, T. Z. (2025, June 23). My Say: Leaping ahead to continue leading with conviction. The Edge Malaysia. https://theedgemalaysia.com/node/759973
Acar, A., Fereidooni, H., Abera, T., Sikder, A. K., Miettinen, M., Aksu, H., ... & Uluagac, S. (2020, July). Peek-a-boo: I see your smart home activities, even encrypted!. In Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks (pp. 207-218).
Agarwal, A. (2022). AI adoption by human resource management: a study of its antecedents and impact on HR system effectiveness. foresight, 25(1), 67-81.
Agustono, D. (2023) ‘Artificial Intelligence in Human Resource Management Practices’, KSS. Available at: https://doi.org/10.18502/kss.v8i9.13409.
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes (50:2), pp. 179-211.
Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Prentice-Hall Inc.
Akter, S., Fosso Wamba, S., & Dewan, S. (2017). Why PLS-SEM is suitable for complex modelling? An empirical illustration in big data analytics quality. Prod Plan. Control 28, 1011–1021. doi: 10.1080/09537287.2016.126 7411
Aphirakmethawong, J., Yang, E., & Mehnen, J. (2022). An overview of artificial intelligence in product design for smart manufacturing. https://doi.org/10.1109/icac55051.2022.9911089
Assemi, B., Paz, A., & Baker, D. (2021). On-street parking occupancy inference based on payment transactions. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2021.3095277.
Avci, S. (2022). Examining the Factors Affecting Teachers' Use of Digital Learning Resources with UTAUT2. Malaysian Online Journal of Educational Technology, 10(3), 200-214.
Aziz, M. (2023, November). Malaysia’s digital evolution: Unleashing the power of AI for inclusive. The Malaysian Reserve; The Malaysian Reserve. https://themalaysianreserve.com/2023/11/01/malaysias-digital-evolution-unleashing-the-power-of-ai-for-inclusive-growth/
Babbie, E. R. (2020). The practice of social research. Cengage Au.
Bakheet, E. M., & Gravell, A. M. (2019). Flipped classroom from computer science instructors' perspectives: A proposed model. In Proceedings of the 2019 8th International Conference on Educational and Information Technology (pp. 131-136).
Balfe, N., Sharples, S., & Wilson, J. R. (2018). Understanding is key: An analysis of factors pertaining to trust in a real-world automation system. Human factors, 60(4), 477-495.
Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory, Prentice Hall, Englewood Cliffs, NJ.
Behl, A., Chavan, M., Jain, K., Sharma, I., Pereira, V. E., & Zhang, J. Z. (2021). The role of organizational culture and voluntariness in the adoption of artificial intelligence for disaster relief operations. International Journal of Manpower, 43(2), 569-586.
Bostrom, N. (2014). The Cambridge Handbook of Artificial Intelligence. Cambridge UP.
Brendel, A.B.; Mirbabaie, M.; Lembcke, T.-B.; Hofeditz, L. (2021). Ethical Management of Artificial Intelligence. Sustainability, 13, 1974. https://doi.org/10.3390/su13041974
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Fang Lee Cooke, Decker, S., DeNisi, A., Prasanta Kumar Dey, Guest, D., Knoblich, A. J., Malik, A., Paauwe, J., Savvas Papagiannidis, Patel, C., Pereira, V., Ren, S., & Rogelberg, S. (2023). Human Resource Management in the Age of Generative Artificial intelligence: Perspectives and Research Directions on ChatGPT. Human Resource Management in the Age of Generative Artificial Intelligence: Perspectives and Research Directions on ChatGPT, 33(3), 606–659. https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1748-8583.12524
Burgos, Z. A. M. (2024). Artificial Intelligence in Businesses: Adoption, Acceptance, and Implementation (Doctoral dissertation, Universidad Ana G Méndez-Gurabo).
Calvani, A., Cartelli, A., Fini, A., & Ranieri, M. (2008). Models and instruments for assessing digital competence at school. Journal of E-learning and Knowledge Society, 4(3), 183-193.
Celebi, C., Yılmaz, F., Demir, U., & Karakuş, F. (2023). Artificial intelligence literacy: An adaptation study. Instructional Technology and Lifelong Learning, 4(2), 291-306.
Celik, I. (2023). Exploring the determinants of Artificial Intelligence (AI) literacy: Digital divide, computational thinking, cognitive absorption. Telematics and Informatics, 83, 102026. https://doi.org/10.1016/j.tele.2023.102026
Chandler Good Government Index (2024). https://chandlergovernmentindex.com/wp-content/uploads/2024-Chandler-Good-Government-Index-Report.pdf
Chandler Good Government Index (2025). https://chandlergovernmentindex.com/wp-content/uploads/2024-Chandler-Good-Government-Index-Report.pdf
Chao (2019). Factors Determining the Behavioural Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model. Frontiers in Psychology doi:10.3389/fpsyg.2019.01652
Cheng, M. M., & Hackett, R. D. (2020). A critical review of algorithms in HRM: Definition, theory, and practice. Human Resource Management Review, 31(1), 100698. https://doi.org/10.1016/j.hrmr.2019.100698
Chui, M., Manyika, J., & Miremadi, M. (2017). The countries most (and least) likely to be affected by automation. Harvard Business Review, 12.
Dahabreh, F. M. (2023). The Continued Usage of Artificial Intelligence in the United Arab Emirates Public Sector Organisations: An Extended Information System Success Model (Order No. 30764931). Available from ProQuest Dissertations & Theses Global. (2925081428). https://ezaccess.library.uitm.edu.my/login?qurl=https%3A%2F%2Fwww.proquest.com%2Fdissertations-theses%2Fcontinued-usage-artificial-intelligence-united%2Fdocview%2F2925081428%2Fse-2%3Faccountid%3D42518
Dai, T., Singh, S., (2021). Artificial intelligence on call: the physician’s decision of whether to use AI in clinical practice. Available at. https://tinglongdai.com/wp-content/uploads/Dai-Singh-2021-AI-on-Call.pdf.
Davenport, T. H. (2019). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. MIT Press.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly (13:3), pp. 319-339.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology (22:14), pp. 1111- 1132.
de Freitas, M. M., & da Rosa, F. S. (2022). Literature review on the application of the Unified Theory of Acceptance and Use of Technologies in e-Government. Contabilidad y Negocios: Revista del Departamento Académico de Ciencias Administrativas, 17(34), 233-262.
Dhillon, H. (2024). Critical Analysis of the Scope of AI Agents in Agency Contract and Its Ethical-Legal Implications in the Indian Legal Framework. Available at SSRN 4893499.
Dillman, D. A. (2009). Internet, Mail and Mixed Mode Surveys: The Tailored Design Method (3rd ed). New York: Wiley.
Dowdy, A. E. A. (2020). Public librarians’ adoption of technology in two southeastern states (Doctoral dissertation, Walden University).
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & 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.
Economic Planning Unit (EPU). (2021). Malaysia Digital Economy Blueprint (MyDIGITAL). Prime Minister’s Department, Malaysia.
Eggers, W., Schatsky, D., Viechnicki, P., & Eggers, D. W. (2017). AI-augmented government: Using cognitive technologies to redesign public sector work. In Deloitte Center for Government Insights. https://www2.deloitte.com/content/dam/insights/ us/articles/3832_AI-augmented-government/DUP_AI-augmented-government.pdf.
Erdélyi, A., & Goldsmith, J. (2020). Regulating Artificial Intelligence: Proposal for a Global Solution. Journal of Corporate Governance, 15(3), 201-215. doi:10.1007/joc.2020.003
Felemban, H., Sohail, M., & Ruikar, K. (2024). Exploring the readiness of organisations to adopt artificial intelligence. Buildings, 14(8), 2460.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Vayena, E. (2018). AI4People—an ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds and machines, 28, 689-707.
Fraenkel, J., Wallen, N., & Hyun, H. (1993). How to Design and Evaluate Research in Education 10th ed. McGraw-Hill Education.
Fryer, L., Coniam, D., Carpenter, R., & Lăpușneanu, D. (2020). Bots for language learning now: Current and future directions.
Fujimori, R., Liu, K., Soeno, S., Naraba, H., Ogura, K., Hara, K., ... & Goto, T. (2022). Acceptance, barriers, and facilitators to implementing artificial intelligence–based decision support systems in emergency departments: quantitative and qualitative evaluation. JMIR formative research, 6(6), e36501.
Gado, S., Kempen, R., Lingelbach, K., & Bipp, T. (2022). Artificial intelligence in psychology: How can we enable psychology students to accept and use artificial intelligence?. Psychology Learning & Teaching, 21(1), 37-56.
Gohil, H. (2023). Factors influencing the adoption of artificial intelligence for qualitative data analysis: a quantitative study using UTAUT model. University of the Cumberlands.
Gómez-Caicedo, M. I., Gaitán-Angulo, M., Bacca-Acosta, J., Briñez Torres, C. Y., & Cubillos Díaz, J. (2022). Business analytics approach to artificial intelligence. Frontiers in Artificial Intelligence, 5, 974180.
Hadi, M. A., Al-Baltah, I. A., & Zahary, A. T. (2022). A survey on mobile payment applications and adopted theoretical models. Sustainable Engineering and Innovation, 4(2), 112-126.
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (p. 197). Springer Nature.
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial management & data systems, 117(3), 442-458.
Hamm, P., & Klesel, M. (2021). Success factors for the adoption of artificial intelligence in organizations: A literature review. In 27th Americas Conference on Information Systems, AMCIS 2021: Digital Innovation and Entrepreneurship. Association for Information Systems.
Handayanto, E., & Ambarwati, R. (2022). Continuance intention of mobile payment Using modified extending model of acceptance and use of technology. AMCA Journal of Science and Technology, 2(1), 1-9.
Hindrasti, N. E. K., & Sabekti, A. W. (2020). Pengalaman calon guru sains dalam pembelajaran daring selama masa pandemi COVID-19. Jurnal Pendidikan Sains Universitas Muhammadiyah Semarang, 8(2), 139-152.
Ho, P., Weill, P., & Gable, G. G. (2022). AI in the Public Sector: From Innovation to Implementation. *Journal of Public Sector Management*, 34(4), 567-587.
IMD (2024, June 10). IMD World Competitiveness Centre https://www.imd.org/centers/wcc/world-competitiveness-center/rankings/world-competitiveness-ranking/rankings/wcr-rankings/#_tab_Rank
INTAN. (2024). Mandatory Courses. INTAN Official Portal. https://www.intanbk.intan.my/iportal/en/civil-servant/mandatory-courses/seap
Ismail, W. S. (2024). Human-Centric AI: Enhancing User Experience through Natural Language Interfaces. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 15(1), 172-183.
Jain, R., Garg, N. & Khera, S. N. (2022) Adoption of AI-Enabled Tools in Social Development Organizations in India: An Extension of UTAUT Model. Front. Psychol. 13:893691. doi: 10.3389/fpsyg.2022.893691
Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes—an interview study of organizational AI readiness factors. Business & information systems engineering, 63(1), 5-20.
Joiner, I. A. (2018). Emerging library technologies: it's not just for geeks. Chandos Publishing.
JPA (2024). Public Service Department Official Portal - Skim Perkhidmatan. Jpa.gov.my. https://www.jpa.gov.my/en/service-scheme
Kala, D., & Chaubey, D. S. (2023). Cryptocurrency adoption and continuance intention among Indians: moderating role of perceived government control. Digital Policy, Regulation and Governance, 25(3), 288-304.
Kaldero, N. (2024, February 19). Council Post: Decision Making 2.0, Powered By Generative AI. Forbes. https://www.forbes.com/sites/forbestechcouncil/2024/02/14/decision-making-20-powered-by-generative-ai/?sh=79cef9912192
Khan, T., Nag, A. K., Joshi, B., Acharya, R., & Thomas, S. (2021). Influencing Factors of Behavior Intention and Actual Use of Technology: An Application of UTAUT Model on Science Undergraduates. Journal of Higher Education Theory & Practice, 21(13).
Khando. K., Sirajul Islam, M., & Gao, S. (2022). "The Emerging Technologies of Digital Payments and Associated Challenges: A Systematic Literature Review," Future Internet, MDPI, vol. 15(1), pages 1-21, December.
Kline, R. B. (2016). Principles and Practice of Structural Equation Modelling (4th ed.). New York: Guilford Press.
Krafft, P., Young, M., Katell, M., Lee, J., Narayan, S., Epstein, M., … & Barghouti, B. (2021). An action-oriented ai policy toolkit for technology audits by community advocates and activists.. https://doi.org/10.1145/3442188.3445938
Kreinsen, M., & Schulz, S. (2023). Towards the triad of digital literacy, data literacy and AI literacy in teacher education–A discussion in light of the accessibility of novel generative AI.
Kurup, R. and Gupta, V. (2022). Factors influencing the AI adoption in organisations. Metamorphosis, 21(2), 129-139. https://doi.org/10.1177/09726225221124035
Lee, J., & Kim, S. (2021). Leadership Support and AI Adoption: The Mediating Role of Organisational Readiness. Journal of Management and Organisation, 27(4), 567-583. doi:10.1017/jmo.2021.009
Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16).
Ma, Y., Wang, Z., Yang, H., Yang, L., 2020. Artificial intelligence applications in the development of autonomous vehicles: a survey. IEEE/CAA J. Automatica Sin. 7 (2), 315–329.
Malay Mail (2024, September 14). Public Service Dept unveils new job grade structure, renames civil service positions under new remuneration system. Malay Mail; Malay Mail. https://www.malaymail.com/news/malaysia/2024/09/14/public-service-dept-unveils-new-job-grade-structure-renames-civil-service-positions-under-new-remuneration-system/150368
Malik, S. A. (2023). Unlocking Organizational Potential: Harnessing AI literacy for Dynamic Capabilities through sensing, seizing and reconfiguring initiatives in IT firms.
Mansoori, K. A. A., Sarabdeen, J., & Tchantchane, A. L. (2018). Investigating Emirati citizens’ adoption of e-government services in Abu Dhabi using modified UTAUT model. Information technology & people, 31(2), 455-481.
McCarthy, J. (2007). From here to human-level AI. Artificial Intelligence, 171(18), 1174-1182.
McCorduck, P. (2004). Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence. A.K. Peters/CRC Press.
Menon, D., & Shilpa, K. (2023). Chatting with ChatGPT”: Analyzing the factors influencing users’ intention to Use the Open AI’s ChatGPT using the UTAUT model. Heliyon, 9 (11), e20962.
Merhi, M. I. (2023). An evaluation of the critical success factors impacting artificial intelligence implementation. International Journal of Information Management, 69, 102545.
Mikalef, P., Lemmer, K., Schaefer, C., Ylinen, M., Fjørtoft, S. O., Torvatn, H. Y., ... & Niehaves, B. (2022). Enabling AI capabilities in government agencies: A study of determinants for European municipalities. Government Information Quarterly, 39(4), 101596.
Mohamed Radhi, M. (2024, January 16). Malaysians urged to take advantage of AI Untuk Rakyat. NST Online; New Straits Times. https://www.nst.com.my/news/nation/2024/01/1001837/malaysians-urged-take-advantage-ai-untuk-rakyat
Mohd Adnan, N., Aminudin, R., Jamaiudin, N. (2023, September 25). The Case for Reviewing Malaysian Civil Servants’ Salary – Stratsea. Stratsea.com. https://stratsea.com/the-case-for-reviewing-malaysian-civil-servants-salary/
Mohd Rahim, N. I., A. Iahad, N., Yusof, A. F., & A. Al-Sharafi, M. (2022). AI-based chatbots adoption model for higher-education institutions: A hybrid PLS-SEM-neural network modelling approach. Sustainability, 14(19), 12726.
Mohsin, F. H., Isa, N. M., Ishak, K., & Salleh, H. M. (2024). Navigating the Adoption of Artificial Intelligence in Higher Education. International Journal of Business and Technopreneurship (IJBT), 14(1), 109-120.
MOSTI. (2021). Artificial Intelligence Roadmap 2021-2025. Ministry of Science, Technology and Innovation. https://mastic.mosti.gov.my/publication/artificial-intelligence-roadmap-2021-2025/
Murdoch, B. (2021). Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Med Ethics 22, 122. https://doi.org/10.1186/s12910-021-00687-3
Owusu Kwateng, K., Osei Atiemo, K. A., & Appiah, C. (2019). Acceptance and use of mobile banking: an application of UTAUT2. Journal of enterprise information management, 32(1), 118-151.
Oxford Insights (2024) Government AI Readiness Index. (2025, January 7). Oxford Insights. https://oxfordinsights.com/ai-readiness/ai-readiness-index/
Park, S., & Lee, H. (2019). Potential Added Value of AI for Specific Domains: A Case Study of Successful Adoption. International Journal of AI Applications, 12(3), 201-215. doi:10.1002/ijai.1234
Park, W. J., & Park, J. B. (2018). History and application of artificial neural networks in dentistry. European journal of dentistry, 12(04), 594-601.
Pasquinelli, M., & Joler, V. (2021). The Nooscope manifested: AI as instrument of knowledge extractivism. AI & society, 36(4), 1263-1280.
Pechtor, V., & Basl, J. (2023). Unraveling the Processes and Challenges of Artificial Intelligence Implementation in the Swiss Public Sector: a TOE Framework Analysis. IDIMT-2023: New Challenges for ICT and Management.
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226.
Pillay, L., van Rensburg, D. C. C. J., van Rensburg, A. J., Ramagole, D. A., Holtzhausen, L., Dijkstra, H. P., & Cronje, T. (2020). Nowhere to hide: the significant impact of coronavirus disease 2019 (COVID-19) measures on elite and semi-elite South African athletes. Journal of science and medicine in sport, 23(7), 670-679.
Pournader, M., Ghaderi, H., Hassanzadegan, A., & Fahimnia, B. (2021). Artificial intelligence applications in supply chain management. International Journal of Production Economics, 241, 108250.
Povera, A. (2024, January 21). All civil servants told to complete “AI untuk Rakyat” self-learning programme. NST Online; New Straits Times. https://www.nst.com.my/news/nation/2024/01/1003781/all-civil-servants-told-complete-ai-untuk-rakyat-self-learning-programme
Prieto, I. M., Revilla, E., & Rodriguez-Prado, B. (2017). "Organisational agility and the role of the CIO: Implications for the adoption of IT." Information & Management, 54(1), 89-103.
Radhakrishnan, J., & Chattopadhyay, M. (2020, December). Determinants and barriers of artificial intelligence adoption–a literature review. In International Working Conference on Transfer and Diffusion of IT (pp. 89-99). Cham: Springer International Publishing.
Rahi, S., & Abd. Ghani, M. (2019). Investigating the role of UTAUT and e-service quality in internet banking adoption setting. The TQM Journal, 31(3), 491-506.
Rai, A.; Constantinides, P.; Sarker, S. (2019). Editor’s Comments: Next-Generation Digital Platforms: Toward Human–AI Hybrids. Manag. Inf. Syst. Q., 43, iii–ix.
Rea, L.M. and Parker, R.A., (2014). Designing and Conducting Survey Research: A Comprehensive Guide. 4th Ed. Jossey-Bass, CA: John Wiley & Sons, Inc.
Reim, W., Åström, J., & Eriksson, O. (2020). Implementation of artificial intelligence (AI): a roadmap for business model innovation. Ai, 1(2), 11.
Reinhardt, K. (2023). Trust and trustworthiness in AI ethics. AI and Ethics, 3(3), 735-744.
Riffai, M. M. M. A., Grant, K., & Edgar, D. (2012). Big TAM in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman. International journal of information management, 32(3), 239-250.
Rogers, E. (1995). Diffusion of Innovations, Free Press, New York,
Russell, S., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.). Pearson.
Sagar, R., Jhaveri, R., & Borrego, C. (2020). Applications in security and evasions in machine learning: a survey. Electronics, 9(1), 97.
Samsurijan, M. S., Ebekozien, A., Azazi, N. A. N., Shaed, M. M., & Firdaus, R. B. R. (2022). Artificial intelligence in urban services in malaysia: a review. PSU Research Review. https://doi.org/10.1108/prr-07-2021-0034
Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., & Ringle, C. M. (2022). Progress in partial least squares structural equation modeling use in marketing research in the last decade. Psychology & Marketing, 39(5), 1035-1064.
Saunders, M.N.K., Lewis, P. and Thornhill, A. (2019) Research Methods for Business Students. 8th Edition, Pearson, New York.
Sayed Abul Khair, S. M. A., Zainall Abidin, M. N., Khamaruzaman, A. R., Anuar, I., & Yuserrie, F. A H. (2023). Measuring Undergraduate Architecture Students' Acceptance Using Artificial Intelligent Image Generator Bot for Conceptual Study: A Case Study of Midjourney. International Journal of Business and Technology Management, [S.l.], v. 5, n. S3, p. 195-210, oct. 2023. ISSN 2682-7646. Available at: <https://myjms.mohe.gov.my/index.php/ijbtm/article/view/24157>. Date accessed: 05 may 2024.
Sedjelmaci, H. (2021). Cooperative attacks detection based on artificial intelligence system for 5G networks. Computers & Electrical Engineering, 91, 107045.
Sekaran, U. (2011). Research methods for business. A Skill Building Approach (4th Edition). India: Willy India Edition
Sharma, G. D., Yadav, A., & Chopra, R. (2020). Artificial Intelligence and Effective Governance: A Review, Critique and Research Agenda. Sustainable Futures, 2, Article 100004. https://doi.org/10.1016/j.sftr.2019.100004
Siregar, Z. A., Anggoro, S., Irianto, H. E., & Purnaweni, H. (2022). A systematic literature review: UTAUT model research for green farmer adoption. International Journal on Advanced Science, Engineering and Information Technology, 12(6), 2485-2490.
Smith, T., & Johnson, A. (2021). Organisational Agility and AI Success: A Longitudinal Study. Journal of Organisational Change, 15(3), 201-215. doi:10.1002/joc.123
Steinbauer, G., Kandlhofer, M., Chklovski, T., Heintz, F., & Koenig, S. (2021). Education in artificial intelligence K-12. KI-Künstliche Intelligenz, 35(2), 127-129.
Šumak, B., & Šorgo, A. (2016). The acceptance and use of interactive whiteboards among teachers: Differences in UTAUT determinants between pre-and post-adopters. Computers in Human Behavior, 64, 602-620.
Taddeo, M., & Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751-752.
Talib, A. M., Al-Hgaish, A., Atan, R., Alshammari, A. A., Alomary, F. O., Yaakob, R., ... & Osman, M. H. (2025). Evaluating Critical Success Factors in AI-Driven Drug Discovery Using AHP: A Strategic Framework for Optimization. IEEE Access.
Taylor S, & Todd P.A. (1995). Understanding Information Technology Usage: a Test of Competing Models. inf. syst. Res., 6 (2):144 – 176.
Teece, D. J. (2018). "Dynamic capabilities and strategic management: Organizing for innovation and growth." Oxford University Press.
Thian, S. Y. (2025). Malaysia aims to be a global leader in responsible AI innovation. Govinsider.asia. https://govinsider.asia/intl-en/article/malaysia-aims-to-be-a-global-leader-in-responsible-ai-innovation
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Quarterly (15:1), pp. 124-143.
Tortoise. (2023). The Global AI Index - Tortoise. https://www.tortoisemedia.com/intelligence/global-ai/
Totonchi, A. (2025). Artificial Intelligence in E-Government: Identifying and Addressing Key Challenges. Malaysian Journal of Information and Communication Technology (MyJICT), 10-24.
Tran, L. T. T., & Nguyen, P. T. (2021). Co-creating blockchain adoption: theory, practice and impact on usage behaviour. Asia Pacific Journal of Marketing and Logistics, 33(7), 1667-1684
van Noordt, C. & Misuraca, G. (2020) Exploratory Insights on Artificial Intelligence for Government in Europe. Social Science Computer Review, 40, 426-444. https://doi.org/10.1177/0894439320980449
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Vincent-Lancrin, S. & Vlies, R. van der, 2020. Trustworthy artificial intelligence (AI) in education: promises and challenges. In: OECD Education Working Papers No. 218, 218, p. 17. https://www.oecd-ilibrary.org/education/trustworthy-artificial-intelligence-ai-in-education_a6c90fa9-en.
Von Krogh, G. (2018). Artificial intelligence in organizations: New opportunities for phenomenon-based theorizing. Academy of Management Discoveries, 4(4), 404-409.
Wachter, S., Mittelstadt, B., & Floridi, L. (2017). "Why a right to explanation of automated decision-making does not exist in the General Data Protection Regulation." International Data Privacy Law, 7(2), 76-99.
Wang, B., Rau, P. L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & information technology, 42(9), 1324-1337.
Wang, K., & Wang, Y. (2017, September). How AI affects the future predictive maintenance: a primer of deep learning. In International workshop of advanced manufacturing and automation (pp. 1-9). Singapore: Springer Singapore.
Wang, K., Ruan, Q., Zhang, X., Fu, C., & Duan, B. (2024). Pre-service teachers’ genai anxiety, technology self-efficacy, and tpack: their structural relations with behavioural intention to design genai-assisted teaching. Behavioural Sciences, 14(5), 373. https://doi.org/10.3390/bs14050373
Wang, L., & Smith, J. (2020). Understanding AI Capabilities and Limitations: Implications for Successful Adoption. Journal of Information Technology, 25(4), 432-448. doi:10.1111/joit.12045
Willinsky, J. (2017). The new literacy: Redefining reading and writing in the schools. Routledge.
Wyman, O. (2018): Digitalization of the Construction Industry: The Revolution Is Underway. Xu, L. Da., Xu, E. L. and Li, L. (2018). Industry 4.0: State of the Art and Future Trends. International Journal of Production Research, 56 (8): 2941–2962.
Xiang, H., Lu, J., Kosov, M. E., Volkova, M. V., Ponkratov, V. V., Masterov, A. I., Elyakova, I. D., Popkov, S. Y., Taburov, D. Y., Lazareva, N. V., Muda, I., Vasiljeva, M. V., & Zekiy, A. O. (2023). Sustainable Development of Employee Lifecycle Management in the Age of Global Challenges: Evidence from China, Russia, and Indonesia. Sustainability (Switzerland), 15(6). https://doi.org/10.3390/su15064987
Xu, X. (2024). Unleashing the power of perceived enjoyment: exploring chinese undergraduate efl learners' intention to use chatgpt for english learning. Journal of Applied Research in Higher Education. https://doi.org/10.1108/jarhe-12-2023-0555
Yadav, S. K. (2023). Research ethics. In Research and Publication Ethics (pp. 23-39). Cham: Springer International Publishing.
Yigitcanlar, T., Corchado, J. M., Mehmood, R., Li, R. Y. M., Mossberger, K., & Desouza, K. (2021). Responsible urban innovation with local government artificial intelligence (AI): A conceptual framework and research agenda. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 71.
Young, J. K., Choi, J. H. & Major, G. (2024). Medical Professionals’ Adoption of AI-based Medical Devices: UTAUT Model with Trust Mediation. Journal of Open Innovation, 10(1), 100220–100220. https://doi.org/10.1016/j.joitmc.2024.100220
Zainab, A. M., Kiran, K., Karim, N. H. A., & Sukmawati, M. (2018). UTAUT’S performance consistency: Empirical evidence from a library management system. Malaysian Journal of Library and Information Science, 23(1), 17-32.
Zainol, M. H. (2023), Acceptance Toward A.I. Use among KPTM Bangi Students in An ESL Classroom. Jurnal Evolusi, Vol 4, Issue 2, 2023
Zainun, N. F. H., Johari, J., & Adnan, Z. (2021). Machiavellianism, locus of control, moral identity, and ethical leadership among public service leaders in Malaysia: the moderating effect of ethical role modelling. International Journal of Sociology and Social Policy, 41(9/10), 1108-1133.
Zhang, C. & Lu, Y., 2021. Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, p.100224.
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.