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Blue Yonder redesigns supply chain operations around AI agents

From SiliconAngle

By Chad Wilson

August 28, 2026

Blue Yonder redesigns supply chain operations around AI agents

Blue Yonder redesigns supply chain operations around AI agents

Permanent disruption has turned supply chain management into a boardroom concern, sitting alongside security as tariff volatility, reshoring pressure and geopolitical shocks reset the cost of getting goods from origin to shelf. Forecast-and-execute planning models built for stable demand are buckling, and a new operating architecture is emerging in which artificial intelligence agents replace fragmented workflows and people supervise outcomes at machine speed.

That shift is already reshaping how software companies build for the sector, with agentic operations moving from pilot projects into production deployments. The change is less about adding intelligence to existing applications than about rebuilding the operating model underneath them, according to Duncan Angove (pictured, left), chief executive officer of Blue Yonder Inc.

“What we’re living through is now business as usual if you’re a supply chain professional,” Angove told theCUBE. “You’re in a permanent state of disruption. The old supply chains were built around forecasting demand and then orchestrating an entire value chain around that. And that just doesn’t work in today’s world.”

Angove and Nunzio Esposito (right), chief design officer at Blue Yonder, spoke with theCUBE’s Dave Vellante during theCUBE’s coverage of the Blue Yonder AI and the Autonomous Supply Chain interview series. TheCUBE, SiliconANGLE Media’s livestreaming studio, explored agent design, open-weight models and the change management challenge facing operators. (* Disclosure below.)

Designing the supply chain for operators and agents

Interfaces built for planners clicking through dashboards do not translate to a world where agents act and humans supervise. Blue Yonder has pushed that thinking into a design manifesto it calls frictionless outcomes, favoring commands over clicks and stripping out steps the system no longer needs a person to confirm Esposito explained.

“We don’t believe an agentic experience is just chat. It’s not messages to messages,” he said. “The way that we’re looking at it is ensuring that it is infused into the fabric of the experience. It’s not a sidecar or bolt-on.”

That means designing for two constituencies at once. Applications have to be headless, performant and secure enough to absorb machine-speed traffic, while the people running them move from executing tasks to setting objectives, Angove pointed out.

“You have to design for two participants. One is the agent, and the other is what we could call the augmented operator,” he said. “They’re no longer clicking. They’re actually expressing intent, guardrails, objectives. They’re managing agents.”

Model strategy follows the same logic. Blue Yonder is training specialized open-weight models with Nvidia Corp., routing to larger frontier models only where the token economics justify it, Angove noted. Looking out five years, he expects the departmental silos that shaped enterprise software to dissolve as orchestration becomes continuous. Labor shortages, not headcount reduction, will drive much of the adoption.

“People will start to think about supply chain software or even the supply chain you run more as one organic adaptive system versus today, it’s all siloed by different departments, different companies,” Angove said. “All those silos will go away inside a company departmentally, and there’ll be much better orchestration across companies as well.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Blue Yonder AI and the Autonomous Supply Chain interview series:

(* Disclosure: TheCUBE is a paid media partner for the Blue Yonder AI and the Autonomous Supply Chain event. Neither Blue Yonder, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

View original article on siliconangle.com

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