Adopting artificial intelligence (AI) into sustainable cold chain management (SCCM) implementation is an important strategy to control real-time temperature, maintain product quality, and increase the cold chain performance and effectiveness. However, most previous research offers individual insights and lack of comprehensive research to support SCCM management implementation with AI integration. Therefore, this study build a AI-driven SCCM framework and explore the interrelationship among attributes to illustrate the important impact in practicing SCCM. Nevertheless, AI-driven SCCM implementation is a complex process that can challenge firms in sustainable practices and operating smart procedures. Thus, this study adopts diffusion of innovation theory to explore the dynamic impact on AI implementation in the SCCM process and improve firms’ performance. To increase the accuracy and dependability of results, this study employs combination of various methods, including content analysis, entropy weight method, fuzzy delphi method, exploratory factor analysis, fuzzy synthetic evaluation and decision-making trial evaluation laboratory. The findings provides a systematic analysis to design suitable strategies and increase the SCCM performance by identifying the causal aspects, including autonomous intelligent agent implementation, resilient supply chain planning, low-carbon network competence, and smart cold chain operations. Besides, practical implication is suggested based on the top important criteria, including green packaging, reinforcement learning, inventory optimization, predictive control, distribution planning.