Featured by Inbound Logistics: What Are Major Pitfalls to Using Artificial Intelligence in Supply Chains?

Featured by Inbound Logistics: What Are Major Pitfalls to Using Artificial Intelligence in Supply Chains?

July 6, 2026
July 6, 2026

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Each month, Inbound Logistics—a trade publication and online resource focused on logistics, supply chain management, transportation, warehousing, and distribution—poses a thoughtful question related to supply chains, with the goal of receiving responses from various experts with experience and unique perspectives. This month, Marissa Licursi (along with other industry experts) replied to the question: What are major pitfalls to using artificial intelligence in supply chains?

Read Marissa's response here or by reading the full list of responses.

"In global, multi-tier supply chains, critical supplier information is often unavailable or inconsistent, leading to misleading outputs or excessive “noise” from irrelevant risk flags. Focus on strengthening data foundations, embedding human-in-the-loop validation, and prioritizing practical integration and usability across internal teams and supplier networks."

—Marissa Licursi, Director

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Marissa Licursi

Director

"In global, multi-tier supply chains, critical supplier information is often unavailable or inconsistent, leading to misleading outputs or excessive “noise” from irrelevant risk flags. Focus on strengthening data foundations, embedding human-in-the-loop validation, and prioritizing practical integration and usability across internal teams and supplier networks."

—Marissa Licursi, Director

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