Supply-chain readiness requires visibility beyond just tier-one suppliers, says Kaitlyn Huissen, vice president of supply chain intelligence at Exiger.

Many companies use AI in an immature way, in Huissen’s view. For instance, they use ChatGPT and Claude more in a search engine fashion, asking a specific question for a specific answer rather than integrating the technology into their business process. The most successful organizations connect it to their enterprise resource planning and product lifecycle management systems, she says. “They have decision intelligence integrated into their supply chain functions. Again, many companies are immature in their ability to leverage AI across different business functions and make sure each business function is leveraging the same level of intelligence.”

Visibility is a key area where autonomous intelligence capability would be enormously beneficial, she says. Higher tariffs on steel and aluminum illustrate her point. Most organizations had country of origin data hidden in an Excel spreadsheet, but the information wasn’t accessible to teams in a timely fashion. “So when the CFO asked what is the real impact to our business today, it took them weeks to get to that answer instead of hours. Bringing autonomous intelligence into the decision-making process allows organizations to answer that question more rapidly.”

What’s the cost of that inefficiency? “Every hour, every minute that parts are not being manufactured on the floor is cost to top line,” Huissen says.

In her estimation, the real value of AI in the supply chain lies in providing the right ontology and context. “Whether you're chasing spend visibility, sustainability initiatives, or you want to chase down the impact of tariffs, it's really about what parts, products and materials are ultimately crossing your production line,” she says. “The value of AI is bringing that ontology and context to the supply chain questions that we're asking.”