Abstract
The study aimed to assess the effect of eight factors that shape employees’ behavioural intentions regarding the use of AI systems in their professional environments: performance and effort expectancy, social influence, facilitating conditions, relative advantage, compatibility, complexity and trialability. These factors were used as predictors of behavioural intention and use behaviour. Data for PLS-SEM analysis were collected from tourism employees using an online survey. Findings revealed a positive and substantial correlation between factors like performance expectancy, effort expectancy and social influence on the one hand and behavioural intentions on the other. In addition, facilitating conditions, compatibility, complexity and trialability were found to be positively and significantly correlated with behavioural intentions, which were also correlated with employees’ use of AI. The study contributes to a more nuanced understanding of the human dimension in the implementation of AI, offering insights for organisations seeking to navigate the complex behavioural landscape of technological change.