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How AI is changing procurement and supply chains

AI is transforming the procurement and supply chain landscape for manufacturing businesses. According to Boston Consulting Group, only 35% of procurement teams have adopted AI, despite the need for better supply chain management. A staggering 64% of manufacturers spend at least 10% of their manufacturing budget dealing with supply chain disruptions, often resorting to last-minute changes or emergency sourcing.

Magnetic, a procurement and supply chain automation company, is addressing this issue by deploying AI agents to manage the procurement and supply chain process. CEO Robin Van Aeken explains that direct procurement has lagged behind other business functions when it comes to automation, largely due to the reliance on personal knowledge and relationships. Traditional ERP systems, designed to record financial outcomes, fail to capture the context and decision-making behind procurement negotiations.

Magnetic's AI agents process and reason across unstructured data sources, such as emails, documents, and CAD drawings. This enables the procurement team to identify win-win scenarios with suppliers, perform value engineering, and pre-empt disruptions. By automating verification processes, Magentic's technology can generate cost savings directly within enterprise systems.

The company's outcome-based pricing model allows clients to pay only a percentage of the savings generated during a pilot phase, transitioning to a subscription model once daily operations are fully automated.

One client saw a $1.2 million saving in the first three months and another $4.2 million in the six months following implementation. AI agents can identify and close value leakage, which costs enterprises around 9% of their annual turnover. By automating administrative tasks, procurement professionals can focus on more strategic aspects of their roles, ultimately driving business growth in a competitive manufacturing environment.

Written by urgent.news from Sifted's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at sifted.eu →

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