Supply chains have become increasingly global and complex, requiring advanced management strategies to mitigate risks, particularly in supplier management. Organizations seek to improve supplier relationships and sourcing strategies, necessitating better data processing capabilities despite analysts already spending a significant portion of their time on data gathering. AI is increasingly employed in supplier risk assessment to objectively evaluate supplier performance and uncover new risks through geolocation and public information, while also aiding in identifying alternate suppliers. Real-world applications demonstrate AI's effectiveness, such as in the automotive sector where it helps avoid costly production delays by integrating various data sources to assess risks, or in the aerospace industry where AI enhances fraud detection by validating component traceability. The Supplier Management Assistant, built on Dataiku's AI platform, exemplifies how AI can transform procurement by integrating diverse data into actionable insights, allowing procurement managers to make informed decisions quickly. Implementing such systems requires robust workflows, high data quality standards, and modular extensibility to ensure reliability and scalability, with a focus on critical procurement tasks and enforcing strict data governance.