<![CDATA[Background. Rapid advancements in artificial intelligence (AI) technologies are transforming educational environments and reshaping teaching practices worldwide. Educational institutions increasingly encourage teachers to integrate AI-powered tools such as generative systems, intelligent tutoring platforms, and automated feedback technologies into classroom activities. Despite the potential benefits of AI for improving instructional efficiency and personalized learning, many teachers initially demonstrate hesitation or resistance toward adopting these technologies. Psychological factors such as technological self-efficacy, perceived usefulness, technological anxiety, and professional identity concerns play a critical role in shaping teachers’ responses to AI-driven educational innovation. Purpose. This study aims to examine the psychological factors influencing teachers’ adoption of AI tools and to explore how educators transition from resistance toward resilience when interacting with emerging educational technologies. Method. A mixed-methods research design was employed involving 120 in-service teachers from various subject areas. Data were collected through structured questionnaires measuring psychological constructs related to AI adoption and through semi-structured interviews exploring teachers’ experiences with AI tools. Quantitative data were analyzed using descriptive and inferential statistics, while qualitative data were examined through thematic analysis. Results. The findings indicate that technological self-efficacy, perceived usefulness of AI tools, and psychological resilience significantly influence teachers’ intention to adopt AI technologies. Initial resistance tends to decrease as teachers gain practical experience, receive institutional support, and develop greater confidence in using AI tools. Conclusion. Psychological readiness is a key determinant of successful AI integration in education. Strengthening teachers’ self-efficacy, reducing technological anxiety, and fostering resilience through training and institutional support can facilitate more effective adoption of AI-driven teaching practices.]]>
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