AI supply chains are no longer a future ambition — they’re a present-tense reality, and Blue Yonder has stepped forward with a clear vision to shape what comes next.

At ICON 2025 in May, Blue Yonder introduced its most expansive solution suite yet — the culmination of a $2 billion investment in next-generation cognitive applications and AI agents. The launch marks a strategic push to unify decision-making, break down silos and enable machine-speed precision across the global supply chain, according to Duncan Angove (pictured), chief executive officer of Blue Yonder.

“These are all written on the Blue Yonder platform, built on the Blue Yonder network and powered by the Snowflake AI data cloud and Azure,” Angove said. “They are incredibly powerful next-gen solutions, they’re very AI forward in the use that they deliver, and they’re more predictive, intelligent and quick.”

Angove spoke with theCUBE’s Dave Vellante during the “AI and the Autonomous Supply Chain” interview series on theCUBE, SiliconANGLE Media’s livestreaming studio. They explored how the future of AI supply chains isn’t just faster or more automated — it’s unified, cognitive and strategic. (* Disclosure below.)

AI supply chains bring precision with cognitive solutions and agentic intelligence

Beyond the hype, Blue Yonder’s agentic solutions are fully embedded and purpose-built for supply chains. The new suite includes five domain-specific agents and is grounded in a practical philosophy: Apply AI where it delivers accuracy, speed and strategic alignment — not where it risks hallucination or isolated optimization, according to Angove.

“We’ve been very pragmatic; we’ve worked with customers and been very responsible in thinking about the role that generative AI plays in improving supply chains,” he said. “Supply chains are critical as it relates to precision of decisioning, and generative AI has had issues over the last two years of hallucinating and not being the most accurate.”

For instance, the Shelf Ops Agent uses Blue Yonder’s proprietary large planogram model to automate planogram edits at scale, enabling retailers to adapt to changing store needs without the traditionally laborious processes. This elevates the planner’s role from repetitive tasks to strategic category growth.

“Today, retailers don’t change these because it’s incredibly laborious,” Angove said. “Loads and loads of tabs and right-click menus, and it just takes a long time to change a Planogram, so they don’t respond to changes and opportunities quickly as they should.”

At the heart of this transformation is Blue Yonder’s SADA loop concept — See, Analyze, Decide and Act. The goal is not just speed, but machine-speed precision, enabling companies to replan in near real time, not on rigid quarterly or annual cycles.

“If you look at the course of human history, we’ve always introduced technology that makes things go dramatically faster, not just faster, but fundamentally changes everything,” Angove said. “It’s the same thing for precision, so how do you take SADA and use agentic technology and everything else that we’ve built to make this thing dramatically faster?”

Traditional metrics, such as return on invested capital, may no longer reflect the value AI delivers, according to Angove. New metrics will likely emerge, centered around the velocity of decisions, adaptability and cost to serve across the entire supply chain.

“We’re going to see profound impacts on productivity and life and the wiring of the world and all of that,” Angove said. “And we’re probably going to need a new set of metrics in terms of how we think about all of this.”

Here’s theCUBE’s complete video interview with Duncan Angove, part of the “AI and the Autonomous Supply Chain” interview series:

(* Disclosure: Blue Yonder Group Inc. sponsored this segment of theCUBE. Neither Blue Yonder nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE