<![CDATA[The rapid deployment of Generative Artificial Intelligence (GenAI) technologies across educational institutions has transformed instructional design, assessment, and administrative workflows. However, the successful adoption of GenAI in classrooms depends fundamentally on teacher readiness rather than simple technology availability or physical infrastructure. This article critically synthesizes empirical, psychometric, and theoretical literature to examine how teachers' readiness for GenAI integration is influenced by three core determinants: AI self-efficacy, digital competence (operationalized through AI-TPACK and AI literacy), and institutional support. Methodologically, this synthesis draws upon international studies employing structural equation modeling (PLS-SEM and CB-SEM), machine learning predictive algorithms, fuzzy-set qualitative comparative analysis (fsQCA), and network psychometrics. The synthesis demonstrates that domain-specific GenAI self-efficacy serves as the primary psychological catalyst and strongest direct predictor of pedagogical integration, perceived ease of use, and perceived usefulness, far outperforming general digital competence alone. Digital competence provides the foundational capability system that shapes attitudes and perceived behavioral control. Institutional support functions as a critical structural antecedent and moderator that mitigates occupational demands, fosters self-efficacy, and enables the translation of intention into enacted classroom practice. The paper concludes with actionable recommendations for designing domain-sensitive professional development programs and ethical institutional governance frameworks.]]>
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