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As more supply chain technology providers embed AI functionality into their platforms, the technology is moving deeper into the space. Some recent high-profile announcements point to just how quickly the conversation is shifting from copilots and dashboards to systems that can plan, test scenarios and act.
But it’s not as easy as it looks. AI holds a lot of promise, and supply chain teams are already using it at a higher rate than many other business functions. The harder part is figuring out how to move beyond narrow use cases and use AI to support better decisions across planning, operations, finance and commercial teams.
Supply chain operators, logistics companies and transportation providers are putting those advances front and center. That is a lot different from earlier technology cycles, when major planning, routing or execution wins were kept close to the vest (or, highlighted later in customer case studies).
Putting AI Gains Front and Center
Last week, C.H. Robinson Worldwide announced that it had built the first AI technology designed to operate a shipper’s global supply chain while continuously assessing and improving its performance. According to Seeking Alpha, the company’s Lean AI Engineer can assess an entire supply chain in 25 to 30 minutes and come up with potential improvements before performance is impacted.
“That compares favorably to other supply chain assessments that typically take up to four weeks and look backward at what has happened instead of what should happen,” the publication notes. Seeking Alpha says the technology is autonomously handling 92% of 4PL shipments globally across trucking, ocean, air and rail. Lean AI Planner uses hundreds of interconnected AI agents to manage shipments, and then feeds the data back to a system that develops smarter refinements.
In another example, Optilogic just introduced Ada, an agentic AI system that supports better supply chain modeling, analysis and redesign. The company says Ada shifts supply chain teams from manually building models and reacting to change to, “evaluating scenarios and accelerating decisions at enterprise scale.”
“Historically, design was slow and inaccessible,” said CEO Don Hicks, in a press release. “That’s not anyone’s fault. Technology just hadn’t risen to the challenge yet.” Now Ada can handle the technical work, while supply chain teams manage the strategy, validate every output and make the final call.
Amazon Brazil was one of 40 early adopters of the new tech. “Optilogic helps us build supply chain resilience,” said Felipe Moraes, head of supply chain and integration, “by providing artificial intelligence and optimization tools to enhance our future.”
5 Tips for Optimizing Agentic AI in Supply Chains
Companies continue to invest in the fast-growing AI in supply chain market, which MarketsandMarkets expects to grow from $13.93 billion in 2025 to $50.41 billion by 2032, with a 20.1% CAGR.
For best results, BCG says companies using AI agents (the kind of AI that can take actions) should start by upgrading the parts of supply chain management they already depend on. Connect those areas first, it says, before automating larger pieces of the operation. BCG also tells companies to:
- Start with the data that drives decisions. Find the gaps that slow planning, replenishment, routing or inventory decisions, then use AI to help close those first.
- Pick high-value decisions first. Look for areas where teams keep weighing cost, service, inventory and timing across multiple systems.
- Build the workflow around the recommendation. Decide how AI recommendations get reviewed, who approves them and when people step in.
- Buy the platform, customize the agents. Use the base platform and tailor the agents around the company’s supply chain needs.
- Make the reasoning visible. Make sure teams can see the data, assumptions and tradeoffs behind each recommendation.
