Determinants of Artificial Intelligence Technologies Adoption in Kenyan Universities: A Case of United States International-Africa
DOI:
https://doi.org/10.47941/jts.2797Keywords:
Technical Capability, Trust, Relative Costs, Institutional Readiness, AI AdoptionAbstract
Purpose: This study sought to carry out analysis of factors influencing AI adoption in the education sector and focused on AI adoption determinants at the United States International University-Africa. This study sought to determine the effect of technical capability, trust, relative costs and institutional readiness on AI adoption at USIU-A. The study was founded on technology acceptance models and focused on analysis of technical capability factors, trust, cost factors and institutional readiness factors.
Methodology: The study was guided by a cross-sectional research design and targeted students when collecting data since these are the main targets of AI in the university. A sample of 378 students were considered in the research. The study relied on structured questionnaires to collect data, and a Likert scale was used to code the responses. Data analysis involved coding into SPSS software, descriptive and inferential statistics including correlation and multiple regression analysis. Findings revealed that technical capability had a significant positive influence on AI adoption, explaining 25.5% of the variance. Trust factors such as privacy, reliability, and ethical use showed a weak but significant influence, accounting for 10.7%.
Findings: Relative costs had an overall insignificant effect, though data management costs showed a weak positive significance. Institutional readiness factors such as culture and policy readiness had weak positive relationships, while resource readiness showed a negative correlation, with the combined factors explaining 8.4% of AI adoption. The study concluded that while cost factors are less influential, technical infrastructure, trust, and institutional readiness play important roles in AI adoption.
Unique Contribution to Theory, Practice and Policy: The study recommends that USIU-A enhance AI adoption by promoting hands-on learning through workshops, pilot projects, and industry collaborations. It should partner with external organizations to access advanced technical resources and training. To build trust, the university should involve students in selecting AI tools and implement systems with clear accountability frameworks. Strategic AI adoption plans are essential, focusing on professional training, scalable platforms, and minimizing non-monetary costs. Finally, the institution should regularly review AI tools for compatibility and appoint visionary leaders to foster a culture of innovation and readiness.
Downloads
References
Abaddi, S. (2024). Factors and moderators influencing artificial intelligence adoption by Jordanian MSMEs. Management & Sustainability: An Arab Review.
AlGerafi, M. A., Zhou, Y., Alfadda, H., & Wijaya, T. T. (2023). Understanding the factors influencing higher education students’ intention to adopt artificial intelligence-based robots. IEEE Access.
Almaiah, M. A., Alfaisal, R., Salloum, S. A., Hajjej, F., Shishakly, R., Lutfi, A., . . . Al-Maroof, R. S. (2022). Measuring institutions’ adoption of artificial intelligence applications in online learning environments: integrating the innovation diffusion theory with technology adoption rate. Electronics, 11(20), 3291.
Alupo, C. D., Omeiza, D., & Vernon, D. (2022). Realizing the Potential of AI in Africa: It all turns on trust. In Towards Trustworthy Artificial Intelligent Systems (pp. 179-192). Cham: Springer International Publishing.
An, X., Chai, C. S., Li, Y., Zhou, Y., Shen, X., Zheng, C., & Chen, M. (2023). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies, 28(5), 5187-5208.
Bakhadirov, M., & Alasgarova, R. (2024). Factors Influencing Teachers' Use of Artificial Intelligence for Instructional Purposes. IAFOR Journal of Education, 12(2), 9-32.
Cabero-Almenara, J., Palacios-Rodríguez, A., Loaiza-Aguirre, M. I., & Rivas-Manzano, M. D. R. D. (2024). Acceptance of educational artificial intelligence by teachers and its relationship with some variables and pedagogical beliefs. Education Sciences, 14(7), 740.
Chepchirchir, S. (2024). Integrating Artificial Intelligence Literacy in Library and Information Science Training in Kenyan Academic Institutions. Mba, Karatina University.
Chivose, E. M. (2023). The Adoption and Usage Patterns of ChatGPT Among Students and Faculty Members in Higher Education: A Study of the University of Nairobi, Faculty of Education (Doctoral dissertation, University of Nairobi).
Choung, H., David, P., & Ross, A. (2023). Trust in AI and its role in the acceptance of AI technologies. International Journal of Human–Computer Interaction, 39(9), 1727-1739.
Cubric, M. (2020). Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study. Technology in Society, 62 (2020): 101257.
Cukurova, M., Miao, X., & Brooker, R. (2023). Adoption of artificial intelligence in schools: unveiling factors influencing teachers’ engagement. In International conference on artificial intelligence in education. Cham: Springer Nature Switzerland, 151-163.
Dong, W., & Fan, X. (2024). Research on the Influence Mechanism of Artificial Intelligence Capability on Ambidextrous Innovation. Journal of Electrical Systems, 20(3), 246-262.
Emhmed, S., Al-Sanjary, O. I., Jaharadak, A. A., Aldulaimi, S. H., & HazimAlkawaz, M. (2021). Technical and organizational facilitating conditions—the antecedent factors and impact on the intention to use ERP system in Libyan universities. IEEE 17th International Colloquium on Signal Processing & Its Applications (CSPA) (pp. 41-46). IEEE.
Ezekiel, O. B., & Akinyemi, A. L. (2022). Utilisation of artificial intelligence in education: the perception of University of Ibadan lecturers. Journal of Global Research in Education and Social Science (JOGRESS), 16(5), 32-40.
Fundi, M., Sanusi, I. T., Oyelere, S. S., & Ayere, M. (2024). Advancing AI education: Assessing Kenyan in-service teachers' preparedness for integrating artificial intelligence in competence-based curriculum. Computers in Human Behavior Reports, 14, 100412.
Hassan, A. S. (2024). Factors driving artificial intelligence adoption in South Africa's financial services sector. Academic Journal of Interdisciplinary Studies, 13(5), 394.
Hlongwane, J., Shava, G. N., Mangena, A., & Muzari, T. (2024). Towards the integration of artificial intelligence in higher education, challenges and opportunities: the African context, a case of Zimbabwe. Int J Res Innov Soc Sci, 8(3S), 417-35.
Koros, H. K., Imbwaga, M. S., & Malaki, H. L. (2024). A Review of Kenya Medical Training Colleges’ Teaching and Learning as a Response to Artificial Intelligence Integration. The Kenya Journal of Technical and Vocational Education and Training. 7, 42.
Lin, H. C., Ho, C. F., & Yang, H. (2022). Understanding adoption of artificial intelligence-enabled language e-learning system: An empirical study of UTAUT model. International Journal of Mobile Learning and Organisation, 16(1), 74-94.
Mafara, R., & Abdullahi, S. (2024). Adopting Artificial Intelligence (AI) in Education: Challenges & Possibilities. Asian Journal of Advanced Research and Reports, 18(2), 106-111.
Nguyen, T. L., Nguyen, V. P., & Dang, T. V. (2022). Critical factors affecting the adoption of artificial intelligence: An empirical study in Vietnam. The Journal of Asian Finance, Economics and Business, 9(5), 225-237.
Nsoh, A. M., Joseph, T., & Adablanu, S. (2023). Artificial intelligence in education: Trends, opportunities and pitfalls for institutes of higher education in Ghana. International Journal of Computer Science and Mobile Computing, 12(2), 38-69.
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(6), 7893-7925.
Perello-Marin, M. R. (2022). Adoption Factors of Artificial intelligence in Human Resources Management. Future of Business Administration, 1(1), 1-12.
Radhakrishnan, J., & Chattopadhyay, M. (2020). Determinants and barriers of artificial intelligence adoption–A literature review. e-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation: IFIP WG 8.6 International Conference on Transfer and Diffusion of IT (pp. 89-99). Tiruchirappalli: Springer International.
Rana, M. M., Siddiqee, M. S., Sakib, M. N., & Ahamed, M. R. (2024). Assessing AI adoption in developing country academia: A trust and privacy-augmented UTAUT framework. Heliyon, 10(18).
Salas-Pilco, S. Z., & Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: a systematic review. International Journal of Educational Technology in Higher Education, 19(1), 21.
Shahadat, M. H., Nekmahmud, M., Ebrahimi, P., & Fekete-Farkas, M. (2023). Digital Technology Adoption in SMEs: What Technological, Environmental and Organizational Factors Influence in Emerging Countries? Global Business Review.
Singla, K., Kaur, P., Singla, K., & Kaur, S. (2024). Shaping Tomorrow's Education: A Deep Dive into AI Adoption Intention in Higher Education Institutions. Mba, Central University of Punjab.
Terblanche, N., & Cilliers, D. (2020). Factors that influence users’ adoption of being coached by an artificial intelligence coach. Philosophy of Coaching: An International Journal, 5(1), 61-70.
Tjebane, M. M., Musonda, I., & Okoro, C. (2022). Organisational factors of artificial intelligence adoption in the South African construction industry. Frontiers in Built Environment, 8, 823998.
USIU-A. (2024, November). Current Students. Retrieved from USIU: https://www.usiu.ac.ke/current-students/
Zaragoza, N. E., Tula, A. T., & Corona, L. H. (2024). Artificial Intelligence in Thesis Writing: Exploring the Role of Advanced Grammar Checkers (Grammarly). Estudios y Perspectivas Revista Científica y Académica, 4(2), 649-683.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Anne Mweru Chege, Prof. Allan Kihara
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
