Teacher adoption of artificial intelligence in autism education: A contextual UTAUT study in Saudi Arabia

Artificial intelligence is receiving growing attention in autism education, but less is known about the factors associated with teachers' intention to use it and their self-reported use in Saudi Arabia. This study examined these relationships using the Unified Theory of Acceptance and Use of Technology framework. A quantitative cross-sectional online survey was completed by 400 special-education teachers in Saudi Arabia. The 25-item questionnaire measured performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, and self-reported use. The measurement model and the hypothesized relationships among these constructs were examined using confirmatory factor analysis and structural equation modeling. The findings supported the proposed measurement structure and all five hypothesized relationships. Performance expectancy showed the strongest association with behavioral intention, while behavioral intention and facilitating conditions were positively associated with self-reported use. Overall, the findings indicate that teachers' adoption of artificial intelligence was associated with both their perceptions of the technology and the conditions supporting its use. Within this sample, teachers' intentions and self-reported use of artificial intelligence were associated with both individual perceptions and enabling school conditions. The study extends technology-adoption evidence to special-education teachers working in autism education in Saudi Arabia and highlights the importance of considering both intention and practical implementation conditions. The findings do not establish causal effects or observed classroom use.