Agentic AI Supporting Procurement in Manufacturing Organizations

Bernardo Nicoletti
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Bernardo Nicoletti: Temple University, Fox School of Business

Chapter Chapter 11 in Agentic AI for Procurement, 2026, pp 197-217 from Springer

Abstract: 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.

Keywords: Procurement; Agentic AI; Manufacturing (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-23024-9_11

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DOI: 10.1007/978-3-032-23024-9_11

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