Artificial intelligence at work: a socio-psychological model of employee adoption and innovation

Purpose This research aims to identify the key organisational, cognitive, and psychological predictors of perceived usefulness of artificial intelligence (AI) and to evaluate their influence on the AI adoption intention and innovative behavior of employees in the Jordanian setting. Design/methodology/approach A strict quantitative research design was adopted in the current study in which a structured online questionnaire was conducted among employees working in various industries in Jordan, mainly IT, retail, and banking. Quantitative data comprising 388 valid responses were then analyzed using partial least squares structural equation modeling to assess both the direct effects as well as moderating relationships between the constructs of interest. Findings The results show that organizational culture (β = 0.216), technology usage habits (β = 0.278), and AI self-image (β = 0.195) positively influence AI perceived usefulness, while AI literacy significantly reduces AI anxiety (β = −0.482). AI perceived usefulness strongly predicts employee innovative behavior (β = 0.608) and AI adoption intention (β = 0.657). Job insecurity weakens the relationship between perceived usefulness and adoption intention (β = −0.234), but its moderating effect on innovative behavior is insignificant. AI anxiety also weakens the effects of perceived usefulness on adoption intention (β = −0.208) and innovative behavior (β = −0.180). Originality/value A socio-psychological approach is used in this investigation, highlighting the significance of identity congruence and the importance of affective processes in the adoption of AI. It anticipates psychological and emotional engagement of employees in AI, breaking the false belief that acceptance is dictated by technical or rational factors only.