In the context of globalization and rapid technological advancement, traditional supply chains face mounting pressure to address environmental challenges like high energy use, waste, and carbon emissions. Growing sustainability awareness compels firms to innovate. Artificial intelligence (AI) has emerged as a key enabler of green supply chain transformation, offering advanced data processing, pattern recognition, and decision optimization to enhance both efficiency and sustainability. This study examines how AI-driven green innovation affects sustainable development across economic, environmental, and social dimensions. Using a mixed-methods approach—comprising a literature review, enterprise surveys, and case studies—the research quantifies AI’s benefits, including cost savings, lower emissions, and reduced waste, while identifying barriers such as high implementation costs, poor partner coordination, and inadequate infrastructure. Findings indicate that AI significantly advances sustainability by optimizing logistics, improving demand forecasting, cutting energy use, and enabling integration with technologies like blockchain and IoT to boost transparency and resilience. The study contributes theoretically by clarifying how AI fosters green innovation and offers practical guidance for businesses and policymakers to support AI adoption in pursuit of sustainable development goals. Despite limitations like potential sampling bias, it highlights AI’s transformative role in building sustainable supply chains.