Organisational Policy Reforms for Integrating Artificial Intelligence into Business Education in Nigeria
This study examined organizational policy reforms required for integrating Artificial Intelligence (AI) into business education in Nigeria. It investigated the extent of AI integration, the policy reforms required for effective implementation, and the relationship between organizational policy frameworks and institutional readiness to produce AI-competent graduates. A descriptive survey research design was adopted. The population comprised 56 lecturers and administrators in Business Education departments across 4 selected tertiary institutions in Nigeria. Total enumeration was employed, and all the 56 respondents participated in the study. Data were collected using a structured questionnaire and analyzed using mean, standard deviation, and Pearson Product Moment Correlation (PPMC). Findings revealed that AI integration in Nigerian business education is at a moderate level, characterized by partial inclusion of AI content in curricula, limited lecturer competence, and inadequate infrastructural support. Inferential results showed a strong positive and significant relationship between organizational policy frameworks and AI integration (r = 0.81, p < 0.05). A significant difference in institutional readiness was also observed between institutions with strong and weak policy frameworks (t = 3.56, p < 0.05). The findings concluded that organizational policy frameworks play a significant role in determining the extent of AI integration, institutional readiness, and competency development. The study therefore recommended that universities should prioritize the provision of essential AI infrastructure, including reliable internet connectivity, digital laboratories, and access to relevant AI software to support effective teaching and learning.
Authors
- Ann Mojisola Uwagwu
- Ifeloluwa Janet OYELEYE
Institutions
- University of Ibadan (NG)
Publication Details
- Journal
- Iconic Research and Engineering Journals
- Published
- 2026-10-14
- DOI
- https://doi.org/10.64388/irev10i4-1723966
- Primary Topic
- Artificial Intelligence in Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00