Artificial Intelligence Applications Integration and Socio- Economic Growth of Government-Owned Universities in South- South, Nigeria

Dick; Aa-Nu Sunday; Elekwachi; Happiness Nwanyi; Ogori; T. Mariana

doi:10.56201/ijssmr.vol.12no1.2026.pg274.286

📄 Download Paper

Artificial Intelligence Applications Integration and Socio- Economic Growth of Government-Owned Universities in South- South, Nigeria

Dick, Aa-Nu Sunday, Elekwachi, Happiness Nwanyi and, Ogori, T. Mariana

Abstract

This paper surveyed Artificial intelligence Applications Integration and Socio-economic Growth of Government-owned universities in South-South, Nigeria. Artificial Intelligences is said to be a reactive machine with limited memory and theory of mind. The functionality of the different artificial intelligence directly or indirectly depends on human input. In this paper, the cross-sectional design approach was adopted for effective data collection and analysis. The study population consisted of seventeen (17) government-owned universities in South-South, Nigeria. The sampling size technique adopted was the census while Regression Analysis was used to test the linear relationship between artificial intelligence applications integration and social economic growth of government-owned universities in South-South, Nigeria. The results obtained showed that there was a significant positive linear relationship between artificial intelligence applications integration and socio- economic growth of government-owned universities in South-South, Nigeria. Though, Artificial intelligence applications are modern tool that facilitated business modelling, new product development, students and staff training, nevertheless, it still has its own limitation as compared to human knowledge such as cultural background, algorithms biases and other factor that must be carefully handled during integration. Therefore, to achieve positive and reliable results, it requires both the qualitative and quantitative integration, the need for regular training of users of artificial intelligence to understand the symbiotic relationship between human and machines. As such, Universities in South-South, desiring for socio- economic growth should ensure that the integration of artificial intelligence application complied with moral principles, laws, ethical consideration, cultural background of the university.

Keywords

Artificial intelligence applicationsQualitative integrationQuantitative integrationand Socio-economic growth

References

African Development Bank Group. (2019). African economic outlook. https://www.afdb.org/en/knowledge/publications/african-economic-outlook Alfonso, M. (2023). Artificial Intelligence and Bias: Challenges, Implications, and Remedies. Journal of Socia Research, 2(11), 3808 – 3817. Anand, S., & Verweij, G. (2019). What’s the real value of AI for your business and how can you capitalise? Retrieved from; https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis sizing-the-prize- report.pdf. Chen, H. L. L. (2020). Explore success factors that impact artificial intelligence adoption on telecom industry in China. Journal of Management Analytics, 8(1), 36–68 Baker, R. S., & Hawn, A. (2021). Algorithmic Bias in Education. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-021-00285-9 Bolarinwa, A. O. (2025). Artificial Intelligence (AI) and Cultural Heritage: An Integration of AI in the Sustainability of Cultural Orientation. The Pastoral Counsellors: Journal of Nigerian Association of Pastoral Counsellors, 4, 68 -73 Borgesius, F. Z., & Poort, J. (2017). Online price discrimination and EU data privacy law. Journal of Consumer Policy, 40(3), 347-366. Cubric, M. (2020). Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study. Technology in Society, 62, 101-257. Debra, J. B., Robert, J. S. & Frederick, K. (2024). Artificial intelligence in the workplace: A philosophical approach to ethics and integrity. Issues in Information Systems, 25(3), 200 – 217. Felten, E., Raj, M., & Seamans, R. (2021). Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses. Strategic Management Journal, 42(12), 2195-2217 Fossen, F. & Sorgner, A. (2022), New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data. Technological Forecasting and Social Change, 175, 121-381. Furman, J. & Seamans, R. (2019), AI and the Economy. Innovation Policy and the Economy, 19, 161-191 Gamboa, A.J. P. & Díaz-Guerra, D. D. (2023). Artificial Intelligence for the development of qualitative studies International Monetary Fund. (2017). Global economic outlook: How artificial intelligence is shaping growth. Retrieved from: https://www.imf.org/en/Publications/WEO. Jobin, A. Ienca, M. & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature machine intelligence, 1(9), 389-399. Johnson, M., & Lee, S. (2018). Precision agriculture and AI: Transforming farming in emerging economies. Journal of Agricultural Informatics, 9(3), 45-59. Khaleel, M., & Jebrel, A. (2024). Artificial intelligence in computer science. International Journal of Electrical Engineering and Sustainability, 2(2), 1-21 Kumar, R. (2019). AI integration in healthcare: Policy challenges and growth prospects in Africa. Health Policy and Technology, 8(2), 123-132. Li, F., Ruijs, N. & Lu, Y. (2022). Ethics & AI: A systematic review on ethical concerns and related strategies for designing with AI in healthcare. Journal of Artificial Intelligence, 4(1), 28-53. Lund, B. D., Lee, T. H., Mannuru, N. R., & Arutla, N. (2025). AI and academic integrity: Exploring student perceptions and implications for higher education. Journal of Academic Ethics. https://doi.org/10.1007/s10805-025-09613-3 Mel, T., Wilfred, M., Vasilka, C., Harlan, B. & John, J. S. (2024). A quantitative study on the negative and positive impacts of artificial intelligence (AI) in the formation technology field, Issues in Information System, 25(1)341 – 351. Mu, T., Ping, D., Yingying, Z. & Maria, P. S. (2018). How does culture influence innovation? a systematic literature review. Management Decision, 56(5), 1088–1107. Ni, L. (2023). Ethical Considerations in Artificial Intelligence: A Comprehensive Disccusion from the Perspective of Computer Vision. SHS Web of Conferences 179, 04024 (2023). https://doi.org/10.1051/shsconf/202317904024 Ntoutsi, E., Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. E. & Staab, S. (2020). Bias in data?driven artificial intelligence systems. An introductory survey. Wires Data Mining and Knowledge Discovery, 10(3), 1456. Ronald, I. & Wayne, E. B. (2000). Modernization, cultural change, and the persistence of traditional values. American sociological review, 65(1):19–51. Shih-Yi, C., Michael, L., Katia, S., Jyi-Shane, L. & Asiye, K. (2018). The effect of culture on trust in automation: reliability and workload. ACM Transactions on Interactive Intelligent Systems, 8(4),1-31 Stupp, C. (2022). Fraudsters used AI to mimic CEO’s voice in un usual cybercrime case: Scams using artificial intelligence are a new challenge for companies. Available: https://www.wsj.com/articles/fraudsters-use-ai-to mimic-ceos-voice-in-unusual- cybercrime-case-11567157402 Williams, B.A., Brooks, C.F., & Shmargad, Y. (2018). How Algorithms Discriminate Based on Data They Lack: Challenges, Solutions, and Policy Implications. Journal of Information Policy, 8, 78. WIREs Data Mining and Knowledge Discovery, 10(3). https://doi.org/10.1002/widm.1456 Obara, C. E., Dick, A. S., Adewale, E., Allwel, I. U. & Nwosu, P. (2025). Cybersecurity management strategies and organizational sustainability of deposit money banks in Rivers State, Nigeria. International Journal of Artificial Intelligence & Business Management, 4(1), 14 – 29. Qin, Y., Xu, Z., Wang, X., & Skare, M. (2024). artificial intelligence and economic development: An evolutionary investigation and systematic review. Journal of Knowledge Economy, 15, 1736–1770. Ogunleye, I. (2021). Artificial intelligence for economic development in Nigeria. https: //citrispolicylab.org/wpcontent/uploads/2021/12/Artificial-Intelligence-for-Economic- Development-in-Nigeria_Ifejesu-Ogunleye.pdf. Roselli, D., Matthews, J., & Talagala, N. (2019). Managing bias in AI. In Companion Proceedings of the 2019 World Wide Web Conference, 539-544. Li, F., Ruijs, N. & Lu, Y. (2022). Ethics & AI: A systematic review on ethical concerns and related strategies for designing with AI in healthcare. Journa of Artificial Intelligence, 4(1), 28-53. Sheikh, H., Prins, C., Schrijvers, E. (2023). Artificial intelligence: Definition and background. In: Mission AI. Research for Policy. Springer, Cham. https://doi.org/10.1007/978-3- 031-21448-6_2 Peter, U.& Carman, M. (2024). Cultural Bias in Explainable AI Research: A Systematic Analysis. Journal of Artificial Intelligence Research 79 (2024) 971-1000 WEF. (2019). The AI revolution: How emerging technologies are transforming the global economy. Retrieved from: https://www.weforum.org/reports/the-ai-revolution. Wisdom, D. D., Vincent, O. R., & Igulu, K. T. (2024). The protection of Industry 4.0 and 5.0: Cybersecurity strategies and innovations. In Trends in Industry 5.0. Taylor & Francis. Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 1–37

Artificial Intelligence Applications Integration and Socio- Economic Growth of Government-Owned Universities in South- South, Nigeria

Abstract

Keywords

References

More Articles from INTERNATIONAL JOURNAL OF SOCIAL SCIENCES AND MANAGEMENT RESEARCH