Leveraging Artificial Intelligence (AI) Innovations for Sustainable Development Goals (SDGs) and Social Well-Being in Nigeria

Authors

  • Augustine Ele Asor Department of Economics, University of Education & Entrepreneurship (UEE), Nigeria
  • Ekoro Ekoro Igo Departent of Computer Science, University of Education & Entrepreneurship (UEE), Nigeria
  • Eyam, Stella Ogar Department of Continuing Education and Development Studies, University of Education & Entrepreneurship (UEE), Nigeria
  • Effiong Emmanuel Bassey Department of Economics, University of Education & Entrepreneurship (UEE), Nigeria

DOI:

https://doi.org/10.54536/ajdsai.v2i2.4786

Keywords:

AI, Education, Healthcare, Poverty, SDGs

Abstract

Artificial intelligence (AI) has emerged as a strong tool for tackling worldwide issues, including the United Nations SDGs. This paper investigates how AI innovations can be used to further the SDGs and improve societal welfare in Nigeria. Primary data gathered through questionnaires, surveys, and discussions with stakeholders from government bodies, private enterprises, and schools were used. The study focuses on three SDG targets: reducing poverty, delivering quality education, and ensuring affordable healthcare. Using chi-square analysis, the research found a notable positive link between AI tools and higher earnings in cities, but no meaningful effect in rural zones. It also observed improved educational access in both urban and remote locations. Moreover, AI-driven mobile health apps significantly boosted healthcare access in cities, though not in rural areas. While these results offer a guide for using AI to promote fairness and economic progress in Nigeria, the paper also looks at obstacles such as poor infrastructure, lack of skills, and ethical issues. It recommends that the Nigerian government extend electricity and internet connections to underserved regions, offer subsidies for AI tools, provide digital training, and foster public-private partnerships to roll out AI solutions in education, health, and poverty reduction.

References

Bini, L., & Dainelli, F. (2020). Artificial intelligence applications in finance: The role of big data. Springer.

Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W.W. Norton & Company.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Faccilongo, N., Iacoviello, M., & Marengo, A. (2024). Exploring the impact of artificial intelligence on healthcare management: A combined systematic review and machine-learning approach. Applied Sciences, 14(22), 10144. https://doi.org/10.3390/app142210144

Goertzel, B. (2014). Artificial general intelligence: Concept, state of the art, and future prospects. Springer.

Gonzalez, R. C., & Woods, R. E. (2018). Digital image processing. Pearson.

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.

Jurafsky, D., & Martin, J. H. (2021). Speech and language processing. Pearson.

Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), 12451. https://doi.org/10.3390/su151612451

Litman, T. (2020). Autonomous vehicle implementation predictions: Implications for transport planning. Victoria Transport Policy Institute.

Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. UCL Press.

MDPI. (2022). Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment. Healthcare, 10(12), 2493. https://doi.org/10.3390/healthcare10122493

Nedungadi, P., Tang, K.-Y., & Raman, R. (2024). The transformative power of generative artificial intelligence for achieving the Sustainable Development Goal of Quality Education. Sustainability, 16(22), 9779. https://doi.org/10.3390/su16229779

Omenihu, C. M., Brahma, S., Katsikas, E., Vrontis, D., Siachou, E., & Krasonikolakis, I. (2024). Financial inclusion and poverty alleviation: A critical analysis in Nigeria. Sustainability, 16(19), 8528. https://doi.org/10.3390/su16198528

O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing.

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson Education.

Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417-457.

Siciliano, B., & Khatib, O. (2016). Springer handbook of robotics. Springer.

Topol, E. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.

United Nations. (2015). Transforming our world: The 2030 Agenda for Sustainable Development. United Nations General Assembly. https://sdgs.un.org/2030agenda

Usmanova, A., Aziz, A., Rakhmonov, D., & Osamy, W. (2022). Utilities of artificial intelligence in poverty prediction: A review. Sustainability, 14(21), 14238. https://doi.org/10.3390/su142114238

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

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Published

2026-10-14

How to Cite

Asor, A. E. ., Igo, E. E. ., Ogar, E. S. ., & Bassey, E. E. . (2026). Leveraging Artificial Intelligence (AI) Innovations for Sustainable Development Goals (SDGs) and Social Well-Being in Nigeria. American Journal of Data Science and Artificial Intelligence, 2(2), 107-112. https://doi.org/10.54536/ajdsai.v2i2.4786

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