This study investigates the barriers to educator acceptance of Artificial Intelligence (AI) technologies in education through a systematic review and meta-analysis guided by the PRISMA 2020 framework. The research synthesizes empirical findings from peer-reviewed studies published between 2020 and 2025 to identify personal, contextual, institutional, and theoretical factors influencing AI adoption in educational settings. From an initial 404 records identified, 310 remained after duplicate removal. Following title and abstract screening, 33 records were retained. After a full-text eligibility review, 14 studies were included in the qualitative synthesis, of which 10 met the criteria for final analysis. The results highlight that demographic factor such as age, gender, and digital literacy significantly affect educators’ readiness to use AI. Common barriers include insufficient training, infrastructure limitations, ethical concerns, anxiety, and perceived misalignment between AI tools and pedagogical goals. Barriers vary by regional and institutional context—developing countries face technological and resource-based challenges, while developed nations encounter pedagogical and ethical issues. The study compares several theoretical models, including the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), to explain variations in AI adoption, further integrating perspectives on emotional response, professional identity, and institutional culture. The findings offer valuable insights for educational policymakers, leaders, and technology developers seeking to implement AI in inclusive, ethical, and pedagogically aligned ways.