Artificial Intelligence and Employee Job Performance of Tertiary Institutions in Ogun State, Nigeria

Ochuko Mary Amori, Volume 7 Issue 1, July 2026 Pages 14-22, Published: 2026-06-02

Abstract

This study explored the effect of artificial intelligence on employee job performance in tertiary institutions in Ogun State, Nigeria. Specifically, the study scrutinized the influence of automation capability, data analytics and predictive ability, and decision-support intelligence on employee job performance. A quantitative study approach was employed and data were gathered from a sample of 359 respondents. The reliability of the instrument was validated using Cronbach’s alpha coefficient of 0.940, demonstrating elevated internal consistency. Data were examined utilizing descriptive statistics, Pearson correlation and multiple regression analysis. The outcomes revealed that artificial intelligence dimensions jointly have a significant effect on employee job performance (R = 0.730, R² = 0.533, p < 0.05), explaining 53.3% of the variance in performance. Individually, automation capability showed a weak but significant positive effect on employee job performance (β = 0.264, p < 0.05). Data analytics and predictive ability exhibited a strong positive and significant effect (β = 0.688, p < 0.05), emerging as the most influential predictor. Decision-support intelligence also had a moderate positive and significant effect on performance (β = 0.594, p < 0.05). However, in the combined regression model, automation capability demonstrated a negative significant relationship, suggesting possible inefficiencies or implementation challenges. The study concludes that artificial intelligence significantly enhances employee job performance, particularly through data-driven decision-making and intelligent support systems. It is recommended that tertiary institutions should invest more in advanced data analytics capabilities and optimize automation processes to improve employee productivity and overall institutional performance