<![CDATA[Driven by digital educational transformation, generative AI is profoundly reshaping traditional classrooms. Grounded in Thailand’s local educational reality, this study investigates the role transformation and practical challenges of local Chinese language teachers in Thai secondary schools under generative AI empowerment. By integrating the SAMR model with Bloom's Taxonomy, this study constructed a specialized behavioral analysis framework, based on which in-depth interviews and behavioral analyses were conducted with 15 in-service Chinese language teachers. The findings indicate that generative AI does not completely replace traditional teaching roles but instead facilitates a pragmatic and selective adaptation. Specifically, pre-class, teachers transition from content producers to human-AI co-creators, using AI to reduce workload while actively serving as quality controllers for instructional content. In-class, they shift from knowledge transmitters to smart teaching assistants, leveraging AI to enhance instructional efficiency while maintaining absolute classroom authority and order. Post-class, they evolve from homework graders to evaluators and reflective practitioners, establishing an efficient AI-screening and teacher-vetting workflow to reallocate the time saved toward deeper pedagogical reflection and humanistic care for students. Finally, targeted recommendations are proposed, ranging from government policy formulation on digital equity and ethical guidelines, through school environment upgrades involving infrastructure and the procurement licensed tools, to teacher training focused on prompt engineering and localized development capabilities, aiming to achieve an organic integration of technological efficiency and humanistic warmth.]]>
