The global supply chain is becoming increasingly complex due to growing demands for speed, accuracy, and efficiency. Businesses are struggling to keep up with these demands using traditional manual tasks and legacy systems. Supply chain automation uses artificial intelligence (AI), robotics, and data-driven systems to streamline operations from warehouse management to delivery. However, companies face new challenges in handling unstructured data and optimizing AI models for real-world applications. To overcome these challenges, businesses must adopt high-quality, structured data, advanced annotation tools, and intelligent data management solutions to train reliable AI models and ensure seamless system integration. By doing so, they can build smarter, more scalable automation tools for supply chains that enhance resilience, adaptability, and overall decision-making.