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This investigation examines the complex interrelationships between teachers’ cognitive load, technological adaptability, and innovative teaching behavior in AI-enhanced educational environments. Through the integration of Cognitive Load Theory, Technology Acceptance Model, and Innovation Diffusion Theory, we develop a sophisticated theoretical framework for understanding how cognitive demands influence teaching innovation through adaptive mechanisms. Employing exploratory structural equation modeling with WLSMV estimation (N = 600), we analyze data collected through rigorously validated instruments measuring AI-assisted Teaching Cognitive Load (ATCL), technological adaptability, and innovative teaching behavior. Results reveal a significant negative relationship between cognitive load and innovative teaching behavior (β = −.134, p β = −.171, p