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1723462 Vol 10 · Issue 3 Download Paper

Artificial Intelligence Adoption in The Nigerian Banking Industry: A Comparative Study of Bank Employees and Customers

Olagoke Kehinde James

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Intelligence

DOI: 10.64388/IREV10I3-1723462

Abstract

Artificial intelligence (AI) is increasingly embedded in banking, but adoption depends on perceived value, trust, organizational readiness, and regulation. This quantitative study examined AI adoption in the Nigerian banking industry from bank employee and customer perspectives. Using a cross-sectional survey, data were collected from 102 respondents (43 employees and 59 customers). The study assessed awareness and current exposure, perceived benefits, trust and transparency, implementation and regulatory challenges, and future AI adoption orientation. Mann–Whitney U tests found no statistically significant employee–customer differences. Spearman correlations showed positive associations between four explanatory constructs and future adoption orientation, with perceived benefits showing the strongest association (ρ = .662, p < .001). Multiple regression explained 50.0% of the variance (R² = .500), with perceived benefits the only independent predictor (B = .617, p < .001). The findings highlight the importance of value, skills, infrastructure, security, transparency, and governance for responsible AI adoption in Nigerian banking.

Keywords

Artificial intelligence, AI adoption, Nigerian banking industry, technology acceptance, trust, explainability, banking customers, bank employees.

References

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[3] F. M. Alnaser, S. Rahi, M. Alghizzawi, and A. H. Ngah, “Does artificial intelligence (AI) boost digital banking user satisfaction? Integration of expectation confirmation model and antecedents of artificial intelligence enabled digital banking,” Heliyon, vol. 9, no. 8, Art. no. e18930, 2023. ScienceDirect

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How to cite this paper

Olagoke Kehinde James "Artificial Intelligence Adoption in The Nigerian Banking Industry: A Comparative Study of Bank Employees and Customers" Iconic Research And Engineering Journals Volume 10 Issue 3 2026 Page 3184-3193 https://doi.org/10.64388/IREV10I3-1723462
Olagoke Kehinde James "Artificial Intelligence Adoption in The Nigerian Banking Industry: A Comparative Study of Bank Employees and Customers" Iconic Research And Engineering Journals, vol. 10, no. 3, Sep. 2026, doi: https://doi.org/10.64388/IREV10I3-1723462
Olagoke Kehinde James (2026). Artificial Intelligence Adoption in The Nigerian Banking Industry: A Comparative Study of Bank Employees and Customers. Iconic Research And Engineering Journals, 10(3). doi: https://doi.org/10.64388/IREV10I3-1723462
Olagoke Kehinde James "Artificial Intelligence Adoption in The Nigerian Banking Industry: A Comparative Study of Bank Employees and Customers" Iconic Research And Engineering Journals, vol. 10, no. 3, Sep. 2026. Crossref, https://doi.org/10.64388/IREV10I3-1723462
@article{1723462,
      author = {Olagoke Kehinde James},
      title = {Artificial Intelligence Adoption in The Nigerian Banking Industry: A Comparative Study of Bank Employees and Customers},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {3},
      pages = {3184-3193},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1723462.pdf},
      abstract = {Artificial intelligence (AI) is increasingly embedded in banking, but adoption depends on perceived value, trust, organizational readiness, and regulation. This quantitative study examined AI adoption in the Nigerian banking industry from bank employee and customer perspectives. Using a cross-sectional survey, data were collected from 102 respondents (43 employees and 59 customers). The study assessed awareness and current exposure, perceived benefits, trust and transparency, implementation and regulatory challenges, and future AI adoption orientation. Mann–Whitney U tests found no statistically significant employee–customer differences. Spearman correlations showed positive associations between four explanatory constructs and future adoption orientation, with perceived benefits showing the strongest association (ρ = .662, p < .001). Multiple regression explained 50.0% of the variance (R² = .500), with perceived benefits the only independent predictor (B = .617, p < .001). The findings highlight the importance of value, skills, infrastructure, security, transparency, and governance for responsible AI adoption in Nigerian banking.},
      keywords = {Artificial intelligence, AI adoption, Nigerian banking industry, technology acceptance, trust, explainability, banking customers, bank employees.},
      month = {September},
      doi = {https://doi.org/10.64388/IREV10I3-1723462}
  }