From Intention To Implementation: A UTAUT-based Study on AI Adoption In Industry

This study aims to identify the key factors that influence both AI use intention (AIuI) and actual AI use behaviour (AIuB) within industry. By extending the Unified Theory of Acceptance and Use of Technology (UTAUT) with AI-specific determinants. A quantitative survey was conducted among 41 industrial companies in the Netherlands, primarily SMEs. Hypotheses were tested using multiple and stepwise regression analyses, with additional constructs including trust, data management know-how, governance structures, data analytics know-how, and AI experience. AIuB was measured using a four-level AI maturity model. AIuI is significantly influenced by individual perceptions, explaining 49% of the variance. However, AIuB is not predicted by AIuI but instead by AI Experience (AIE) and Data Management (DM) capabilities, which together account for 62% of the variance. Moderation analysis showed no significant effects for gender, age, or SME status. This study contributes to the growing body of work critiquing the predictive power of intention in adoption models. By incorporating AI-specific variables and a maturity-based outcome measure, it offers a more accurate understanding of how organizations move from intention to implementation. Findings show that AI adoption depends not just on intent, but on experiential learning and organizational readiness, calling for a shift from awareness to actionable support in data governance and applied AI skills