<![CDATA[The rapid advancement of Artificial Intelligence (AI) opens transformative opportunities for education, yet its adoption in school environments still faces complex barriers. This study aims to analyze factors influencing teachers' and students' acceptance of AI technology in schools using an extended Technology Acceptance Model (TAM) framework incorporating Computer Self-Efficacy (CSE), Anxiety (ANX), and Subjective Norm (SN) constructs. A quantitative cross-sectional survey was conducted among 312 respondents (134 teachers and 178 students) from 15 secondary schools in DKI Jakarta and West Java. The research instrument used a validated 24-item questionnaire based on a 5-point Likert scale. Data analysis employed Partial Least Square-based Structural Equation Modeling (SEM-PLS) using SmartPLS 4.0. Measurement model evaluation confirmed all constructs met convergent validity (AVE > 0.50), discriminant validity (HTMT < 0.85), and composite reliability (CR > 0.80). Hypothesis testing through 5,000-subsample bootstrapping revealed: CSE significantly and positively affects PEOU (β = 0.512, p < 0.001), ANX significantly and negatively affects PEOU (β = -0.289, p < 0.001), PEOU positively influences PU (β = 0.387, p < 0.001), PU is the strongest predictor of BI (β = 0.421, p < 0.001), and SN significantly influences BI (β = 0.178, p < 0.001). The model explains 67.3% of Behavioral Intention variance. These findings provide strategic implications for AI integration policies in Indonesian schools.]]>
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