Artificial Intelligence Integration, Remote Work Arrangements and Employee Performance in Manufacturing Firms in South-East Nigeria

Abstract

The spread of artificial intelligence (AI) tools across workplaces has raised questions about how such technologies shape employee performance, particularly where they coincide with remote and hybrid work. This study examined the joint influence of AI integration and remote work arrangements on employee performance in manufacturing firms across the five states of South-East Nigeria. Working from the automation–augmentation paradox, the job demands–resources model, the technology acceptance model, and self-determination theory, the study pursued four objectives: to assess the effect of AI tool adoption on task performance; to examine the relationship between remote work autonomy and contextual performance; to test the interaction of AI integration and remote work autonomy on productivity; and to evaluate the influence of technological infrastructure readiness on AI-assisted work effectiveness. A cross-sectional survey design was used, with data drawn from 312 employees in manufacturing firms in Anambra, Enugu, Abia, Imo, and Ebonyi States. AI tool adoption predicted task performance (β = .43, p < .001). Remote work autonomy was positively associated with contextual performance (r = .54, p < .01). The interaction of AI integration and remote work autonomy predicted productivity beyond either predictor alone (β = .31, p < .001), and technological infrastructure readiness emerged as the strongest predictor of AI-assisted work effectiveness (β = .46, p < .001). The pattern of results suggests that the performance value of AI in this setting is conditional rather than guaranteed, and that it depends heavily on infrastructure and on how the technology is introduced. Implications for psychology in developing-economy industrial contexts are discussed.