Administrative tasks occupy a substantial portion of engineers’ working hours and are widely perceived as burdensome, stressful, and detrimental to productivity. This study investigates the key determinants influencing engineers’ behavioural intention to adopt AI assistants to reduce administrative workload. Using a quantitative survey design grounded in an extended UTAUT model, the descriptive findings highlight both the operational strain of administrative work and the growing familiarity of AI assistants, particularly ChatGPT, which establishes a favourable foundation for adoption. The inferential findings show that the regression model demonstrates strong explanatory power. Performance expectancy emerged as the strongest and most significant predictor of adoption, reaffirming its central role in technology adoption among technical professionals. Social influence also had a meaningful and positive effect, indicating the importance of peer norms inn early adoption. Effort expectancy, perceived risk, and hedonic motivation were not significant, suggesting that engineers prioritise productivity benefits over usability concerns or perceived enjoyment when evaluating new digital tools.

Keywords

AI assistant; adoption; perception; behavioural intention