Generative AI Adoption and Business Performance in the United Kingdom: An Empirical Investigation of the Mediating Roles of Operational Efficiency and Product Innovation

Objective: This study provides an empirical analysis of the link between Generative AI (GenAI) adoption and business performance in UK firms, with a specific focus on the mediating effects of operational efficiency and product innovation. Methodology: Grounded in the Resource-Based View (RBV) and the Technology-Organization-Environment (TOE) framework, a conceptual model was developed and tested. Data were collected via a cross-sectional survey of 312 senior managers across diverse UK industries. The data were analysed using partial least squares structural equation modeling (PLS-SEM). Findings: The results indicate a significant positive direct relationship between GenAI adoption and business performance. Both operational efficiency and product innovation were found to be significant partial mediators, with product innovation exhibiting a stronger mediating effect. Key drivers of adoption included technological competence, top management support, and competitive pressure, while regulatory uncertainty was a significant barrier. Implications: The findings offer robust evidence for policymakers and business leaders, positioning GenAI not just as a tool for cost reduction but as a strategic lever for growth, primarily through enhanced innovation. The study underscores the need for sustained investment in technological infrastructure and workforce skills. Originality/Value: This research is one of the first large-scale quantitative studies to empirically validate the mediating pathways through which GenAI influences business performance, providing nuanced, context-specific insights for the UK market.