Strong security frameworks are becoming more and more necessary to safeguard sensitive data and activities as supply chains becoming more complex and linked. Because modern supply chains are distributed and dynamic, traditional perimeter-based security solutions are no longer adequate. The AI-Enhanced Zero Trust Framework (AIEZTF), which uses artificial intelligence (AI) and machine learning (ML) to enforce zero-trust security principles across interconnected supply chain entities, is proposed in this study for dynamic supply chain ecosystems. The framework operates on the core premise that no user or device, regardless of location, should be trusted by default. It continuously authenticates and authorizes every transaction and interaction within the supply chain ecosystem, applying least-privilege access and continuous verification policies. The AIEZTF uses AI anomaly detection and real-time data analytics to find odd patterns or possible security risks that might jeopardize the supply chain's integrity. By dynamically adjusting to shifting circumstances, the system makes sure that new partners, devices, or technologies are safely on-boarded without sacrificing security.