Factors influencing the outcomes of generative ai implementation in private sector organizations in Thailand

Abstract

This study examines individual, leadership, and system-quality factors driving employees' Behavioral intention, satisfaction, and perceived net benefits from generative AI (GenAI) use in Thai private-sector organisations. An integrated framework combining UTAUT2, the AIDUA model, KOL, IS Success Model, and Technology Innovation (TI) was tested via PLS-SEM on 410 employees. The model explained 76.8% of variance in satisfaction, 60.5% in Behavioral intention, and 58.3% in net benefits, with attitude toward GenAI emerging as the strongest predictor across all outcomes. Self-efficacy and AI System Quality were key drivers of satisfaction and net benefits, while TI negatively moderated individual-level barriers, suggesting innovative environments compensate for such constraints. Findings highlight that fostering positive attitudes, building self-efficacy, and investing in AI system quality are the most effective levers for sustained GenAI adoption in Thai organisations.