Generative AI for Supplier Relationship Management: Applications, Challenges, and Future Directions

Abstract

This research paper explores the transformative potential of generative artificial intelligence (AI) in supplier relationship management (SRM). As organizations face increasingly complex global supply chains, generative AI offers promising capabilities to enhance communication, optimize negotiations, predict supplier performance, and mitigate risks. This paper examines current applications, implementation challenges, and future directions for generative AI in SRM. By analyzing emerging use cases and technological developments, we identify key opportunities for organizations to leverage generative AI in creating more resilient, efficient, and collaborative supplier relationships. While significant challenges remain, including data privacy concerns and integration with existing systems, the strategic deployment of generative AI in SRM represents a competitive advantage for forward-thinking organizations. This study investigates the transformative role of generative artificial intelligence (AI) in supplier relationship management (SRM). With the growing complexity of global supply chains, generative AI presents significant opportunities to enhance communication, streamline negotiations, predict supplier performance, and mitigate risks. The paper delves into current applications of generative AI, the challenges encountered during implementation, and potential future directions for SRM. By examining innovative use cases and recent technological advancements, we highlight critical opportunities for organizations to harness generative AI to foster more resilient, efficient, and collaborative relationships with suppliers. Despite notable challenges, such as data privacy issues and integrating AI with existing systems, the strategic application of generative AI in SRM can provide a distinct competitive edge for progressive organizations.