AI adoption decision-making styles and performance: the moderating role of decentralization

Abstract

Artificial Intelligence (AI) adoption is becoming a key strategic priority for firms seeking to enhance performance. Despite the growing prevalence of AI, little is known about how strategic decisions regarding AI adoption are made within organizations. This study investigates the impact of three decision-making styles—rational, intuitive, and political—on AI adoption performance. Additionally, we explore how decentralization moderates these relationships. Drawing on data collected from 208 firms in Egypt, our preliminary findings suggest that both rational and intuitive decision-making styles positively influence AI performance, while political decision-making shows no significant effect. Interestingly, decentralization weakens the positive impact of intuitive decision-making and does not significantly enhance the effect of rational decision-making, challenging assumptions about its benefits. These findings offer new insights into how organizations can align decision processes and structures to improve the outcomes of AI adoption.