Artificial Intelligence Applications, Customer Satisfaction, and Network Performance in the Telecommunications Sector: Evidence from Ikeji-Arakeji, Osun State, Nigeria

Abstract

Artificial intelligence (AI) is increasingly used in customer-facing telecommunications services and network management. This study examined the association between customers’ perceptions of AI-enabled services and customer satisfaction, alongside observed network performance in Ikeji-Arakeji, Osun State, Nigeria. A mixed-methods design combined a questionnaire survey of 370 telecommunications subscribers with field-based speed tests of MTN, Globacom (Glo), and Airtel. The questionnaire data were analysed using descriptive statistics, Pearson’s product-moment correlation, and simple linear regression in SPSS version 26. The analysis found a positive, statistically significant association between AI and customer satisfaction (r = .412, p < .001). The regression model was statistically significant, F(1, 368) = 75.00, p < .001, and explained 16.9% of the variance in customer satisfaction (R² = .169; adjusted R² = .167). The speed-test observations showed variation in download speed, upload speed, and latency across operators and observation periods. However, because the study did not measure operators’ internal AI systems or control for infrastructure, traffic, and other network conditions, the speed-test results cannot establish that AI caused the observed differences. The findings suggest that customer-facing AI services are positively associated with customer satisfaction, while network performance should be interpreted as a separate descriptive outcome. Telecommunications operators should improve the usefulness and reliability of chatbots, personalized offers, and self-service tools, and monitor network quality continuously.