In the era of artificial intelligence, the concept of interdisciplinary integration has increasingly demonstrated its significance as a pivotal driver for advancing innovation in university physics education. This study explores strategies for integrating computational thinking into university physics curricula within this context and proposes three implementation pathways: (1) Adopting student-centered instructional design to facilitate collaborative development between educators and students; (2) Synthesizing physics and computational thinking curricula by embedding Python programming in physics instruction, enabling both analytical problem-solving and visualization of physical phenomena; (3) Establishing an interdisciplinary, multi-perspective framework for curriculum development, assessment, and feedback mechanisms. The incorporation of computational thinking has effectively enhanced traditional teaching methodologies in university physics, deepening students' comprehension of abstract physical principles while serving as an impactful approach to advancing higher vocational education reform and cultivating innovative interdisciplinary talents.