AI Agents Slash Supply Chain Waste by 20%, Turning Losses Into Working Capital

Supply chain executives know the hidden tax of excess and obsolete inventory. Trucks running half empty, food expiring before it’s sold, or factories producing goods that sit idle. These inefficiencies tie up working capital, drag down service levels, and create waste that runs into billions annually. The root cause is often not capacity, but poor decisions—or worse, decisions delayed until it’s too late.

That is the gap AI is beginning to close. Aera Technology reports its decision intelligence platform is helping enterprises cut supply chain waste by as much as 20%. Instead of showing managers where problems are, Aera’s “skills” actively recommend and even execute actions. In consumer goods, one customer lifted truck utilization from the mid-80s to 95%. In biopharma, AstraZeneca has used the system to accelerate clinical trial planning and align production more closely with demand.

“We are preventing massive waste and loss at global scale by optimizing and orchestrating decisions across complex enterprise value chains,” said Fred Laluyaux, CEO of Aera Technology. “Beyond solving today’s inefficiencies, Aera enables companies to use decision intelligence and stay competitive in a digital, AI world.”

Fred Laluyaux, Co-Founder and CEO, Aera Technology

The technology works by continuously scanning material, production, and demand data for aging or at-risk inventory, then prescribing targeted moves: reallocate stock, throttle orders, shape demand, or discount before items expire. Other modules tackle procurement waste, detect supply-demand mismatches, and rebalance inventory across regions.

Competitors such as Kinaxis, o9 Solutions, and Blue Yonder are pitching similar AI-driven planning and execution layers. What’s new is the push from pilots to enterprise-wide deployment. Companies are moving past proofs of concept and into measurable financial outcomes, like millions in freed working capital and double-digit improvements in utilization.

As adoption spreads, the implications go beyond efficiency. Cutting 20% of supply chain waste is not just a margin win—it is a sustainability play, reducing spoilage, emissions, and plastic use tied to excess production and transport. Always-on AI agents that recommend, act, and learn are beginning to shift supply chains from reactive firefighting toward proactive, self-correcting systems.

For tips, leaks or anonymous sourcing: editor@thesupplychainer.com