Predictors of Workplace AI Adoption in a Norwegian Sample

This study examines predictors of workplace adoption of artificial intelligence (AI) in a Norwegian employee sample (N = 196). Hierarchical logistic regression tested whether education, sector, sex, age, leadership, strengths-based leadership (SBL), training, and engagement predicted AI use. Education was the strongest predictor. Employees with a bachelor’s degree were 3.64 times, and those with a master’s degree more than 11.15 times, more likely to use AI than those with secondary education. Knowledge-intensive sector employees were 2.52 times more likely to adopt AI than those in skills-focused sectors. Men were 2.94 times more likely than women to use AI. Neither age nor leadership role showed significant effects. SBL independently predicted adoption (OR = 1.89). Training and engagement were unrelated to adoption. Overall, findings show that structural, sociodemographic, and organizational factors shape AI adoption, underscoring the need for targeted strategies to ensure equitable, effective uptake across the workforce.