Empowering Administrative and Technical Staff at the University of Cape Coast: Leveraging Prompt Engineering for Generative AI to Uphold Administrative Integrity in a Dynamic IT Era
DOI:
https://doi.org/10.70619/vol5iss13pp51-67-715Keywords:
Administrative integrity, prompt engineering, generative AI, public value theory, higher education administration, Ghana, technology governanceAbstract
The rapid integration of Generative Artificial Intelligence into public sector administration presents a dualistic reality of enhanced efficiency and significant threats to administrative integrity, a tension acutely felt in emerging digital economies. This study addresses the critical absence of an evidence-based framework for leveraging prompt engineering to ensure Generative AI use by administrative and technical staff at the University of Cape Coast reinforces, rather than undermines, administrative integrity. Employing an exploratory sequential mixed-methods design, the research combined qualitative interviews and a quantitative survey to first explore staff practices and then measure prevalent risks. The study achieved its purpose by diagnosing a bifurcated risk structure—comprising substantive Administrative Integrity and procedural Transparency & Accountability concerns—and subsequently developing a novel, theoretically-informed framework for prompt engineering. This framework fills a crucial gap in the literature, which has largely overlooked micro-practices of AI use in African administrative contexts, by providing a multi-layered governance model anchored in Public Value, Institutional, and Technology Acceptance theories. The new knowledge created demonstrates that integrity-preserving AI use requires an integrated system of institutional governance, iterative practice, and robust oversight, moving beyond technical skill-building. The study positions prompt engineering as a vital mechanism for upholding due process and due diligence. Key policy implications include the need to mandate structured prompt engineering literacy, institutionalise curated prompt libraries, and formally integrate AI accountability matrices into administrative procedures to guide effective resource allocation and decision-making for sustainable digital transformation.
References
Amissah, G. (2024). Digital transformation in Ghanaian higher education: A policy analysis [Unpublished doctoral dissertation]. University of Ghana.
Androutsopoulou, A., Karacapilidis, N., Loukis, E., & Charalabidis, Y. (2019). Transforming the communication between citizens and government through AI-guided chatbots. Government Information Quarterly, 36(2), 358-367.
Aoki, N. (2020). The importance of the human element in the AI-based automated administrative state. Public Performance & Management Review, 43(5), 1124-1146.
Asongu, S. A., & Odhiambo, N. M. (2021). The digital divide and inclusive growth in Sub-Saharan Africa. Sustainable Development, 29(4), 756-765.
Baxter, J., & Mujinga, M. (2022). Irembo and the evolution of e-government in Rwanda: A platform for service delivery and anti-corruption. The African Journal of Information and Communication, 29, 1-21.
Anim, S., Onyame, E. A., Sayibu, A.-G., Mensah, E. A., Blankson-Austin, R., & Owusu, B. (2025). Leveraging AI for Administrative Excellence: Assessing the Digital Readiness of UCC’s Tech-Savvy Administrators. Journal of Information and Technology, 5(10), 37–67. https://doi.org/10.70619/vol5iss10pp37-67
Boateng, R., & Anning-Dorson, T. (2024). Digital innovation in African universities: A research agenda. Information Technology for Development, 30(1), 1-20.
Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. SAGE Publications.
Bullock, J. B. (2019). Artificial intelligence, discretion, and bureaucracy. The American Review of Public Administration, 49(7), 751-761.
Cordella, A., & Paletti, A. (2019). ICTs and value creation in the public sector: Manufacturing logic vs service logic. Government Information Quarterly, 36(2), 333-342.
Crawford, K., & Calo, R. (2021). There is a blind spot in AI research. Nature, 538(7625), 311-313.
Creswell, J. W., & Plano Clark, V. L. (2021). Designing and conducting mixed methods research (4th ed.). SAGE Publications.
Criado, J. I., & Gil-Garcia, J. R. (2021). Creating public value through smart technologies and strategies: From digital services to artificial intelligence and beyond. International Journal of Public Sector Management, 34(5), 438-450.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2023). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy. International Journal of Information Management, 57, 102199.
Glaser, B. G., & Strauss, A. L. (2017). The discovery of grounded theory: Strategies for qualitative research. Routledge.
Johnson, G., & Lægreid, P. (2022). Digital transformation and public sector organizations: An institutional perspective. Public Management Review, 24(7), 1-22.
Klievink, B., Romijn, B. J., & Cunningham, S. (2022). The perils of algorithmic failure: A case study of the Dutch childcare benefits scandal. Government Information Quarterly, 39(4), 101717.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610.
Kweku, J., & Mensah, S. (2023). Generative AI usage among administrative staff in Ghanaian public universities [Unpublished manuscript]. Department of Information Technology, Kwame Nkrumah University of Science and Technology.
Leslie, D. (2019). Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector. The Alan Turing Institute.
Mikhaylov, S. J., Esteve, M., & Campion, A. (2021). Artificial intelligence for the public sector: Opportunities and challenges of cross-sector collaboration. Public Administration Review, 81(2), 278-282.
O'Flynn, J. (2021). From new public management to public value: Paradigmatic change and managerial implications. Australian Journal of Public Administration, 80(1), 23-34.
Saunders, M. N. K., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson.
Schuilenburg, M., & Peeters, R. (2021). The algorithmic society: Technology, power, and knowledge. Routledge.
Tavera Romero, C. A., Ortiz, J. H., Khalaf, O. I., & Prado, A. R. (2021). Business intelligence: Business evolution after Industry 4.0. Sustainability, 13(18), 10026.
University of Cape Coast. (2022). Strategic plan 2022-2026. Office of the Vice-Chancellor.
Venkatesh, V., & Davis, F. D. (2020). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Gilbert, H., ... & Schmidt, D. C. (2023). A prompt pattern catalog to enhance prompt engineering with ChatGPT. arXiv preprint arXiv:2302.11382.
Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2020). Artificial intelligence and the public sector—Applications and challenges. International Journal of Public Administration, 42(7), 596-615.
Young, M. M., Bullock, J. B., & Lecy, J. D. (2021). Artificial discretion as a tool of governance: A framework for understanding the impact of artificial intelligence on public administration. Perspectives on Public Management and Governance, 4(1), 33-48.
Zheng, N., Liu, Z., Ren, P., Ma, Y., Chen, S., Yu, S., ... & Wang, F. (2021). Hybrid-augmented intelligence: collaboration and cognition. Frontiers of Information Technology & Electronic Engineering, 22(12), 1532-1546.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Isaac Yeboah Nsaful, Amesimeku Prosper Yao, Dickson Senyo Yaw Amedahe, Fiifi Andoh-Kumi, Nelson Borketey-Coffie, Sayibu Abdul-Gafaar
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
