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Agentic AI Supporting Procurement in Manufacturing Organizations

In: Agentic AI for Procurement

Author

Listed:
  • Bernardo Nicoletti

    (Temple University, Fox School of Business)

Abstract

This case study shows how a manufacturing organization can use agentic AI (AAI) to automate procurement choices and improve partner networks. It indicates that problems with integration can lead to lower prices, more flexibility, and more new ideas. This chapter thoroughly explains how ACME Industries, a fake name for a manufacturing organization operating internationally, used AAI in its procurement processes. The research shows that AAI was able to automate complex procurement decisions and improve partner networks over the course of three years. The main conclusions are that expenses went down by 24.7%, decision-making accuracy went up, and response times in the procurement network went down by 73%. The example shows significant problems with implementation, like getting partners to work together, getting all stakeholders on the same page, and ensuring that existing systems work together. This study highlights essential elements for effective adoption in intricate manufacturing settings. It provides empirical proof of the revolutionary potential of artificial intelligence (AI) through an extensive investigation of both quantitative and qualitative outcomes.

Suggested Citation

  • Bernardo Nicoletti, 2026. "Agentic AI Supporting Procurement in Manufacturing Organizations," Springer Books, in: Agentic AI for Procurement, chapter 0, pages 197-217, Springer.
    • Handle: RePEc:spr:sprchp:978-3-032-23024-9_11
    DOI: 10.1007/978-3-032-23024-9_11
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