Every AI Supply Chain Strategy Ran a Pilot. Under 1% Got Enterprise Impact.

Arizona State University’s Brett Duarte on AI supply chain strategy, part 1: procurement, supplier risk, and contract intelligence

Boston Consulting Group found AI leaders doubling revenue on specific projects and cutting costs 40 to 50%. McKinsey found that under 1% of organizations that adopted AI have seen enterprise-wide impact. The distance between those two numbers is the whole job of an AI supply chain strategy.

Season 2, Episode 13 of Data Blades opens a 3-part mini-series with Professor Brett Duarte of Arizona State University's W. P. Carey School of Business, home to the #2 ranked supply chain program in the country. The series follows ASU's AI-Enabled Supply Chain Strategy executive program running October 5 to 7 on the Tempe campus: procurement in part 1, operations in part 2, logistics in part 3.

Today we start where the money starts. Brett names the two things supply chain leaders keep hitting. First, infrastructure: siloed systems, data quality problems, fragmentation, and AI "slapped on the legacy systems" so nobody can see the supply chain end to end. Second, adoption, which is just whether employees pick the tools up and use them.

Then he gets specific about agentic AI in procurement. Agents are a digital workforce that can plan, reason, act, and learn. A procurement agent pulls structured and unstructured data, reads a new tariff into a pricing picture, runs sentiment analysis on news about a supplier or a region, and automates the supplier back-and-forth that used to live in email threads and manual ERP lookups. A contract agent reads the whole contract portfolio, flags what has expired or is up for renewal, checks terms against real purchase orders and delivery performance, and schedules the renegotiation conversation with evidence attached.

Casey and Ricardo also get into what supplier scorecards and Kraljic matrix segmentation look like when an agent maintains them, and why ASU built an AI lab with a supply chain digital twin to watch how agents behave when a disruption hits.

What you'll learn in this episode.

Why AI pilots keep working while enterprise-wide impact stalls, and the two blockers Brett hears most from supply chain leaders [00:04:59]How ASU's three-part mission shows up as an AI lab and a supply chain digital twin for testing agents against simulated disruptions [00:07:21]What the 3-day AI-Enabled Supply Chain Strategy program covers, day by day, and who it's built for [00:09:15]Agentic AI explained: plan, reason, act, learn, and the maturity curve from AI assistant to automated workflows to a frontier firm [00:12:16]Why executives build their own agent in the room, then watch three agents talk to each other through a simulated disruption [00:14:08]Where agentic AI in procurement lands first: tactical work like supplier identification and purchase orders, strategic work like spend analytics, category management, and supplier risk [00:15:22]How a contract agent handles renewals, terms violations, delivery misses, and supplier scorecards, and where the Kraljic matrix fits [00:17:12]

Next Episode.

Part 2 moves downstream into operations: forecasting, inventory, and the gap between a model that predicts well and a business that acts on it. If procurement is where you decide what to buy, operations is where you find out whether you got it right. Taken together, the three parts cover a full AI supply chain strategy from the front end to the back. Follow Data Blades so you don't miss it.

Support Our Sponsors.

There’s still time to join us at RetailClub AI Festival.