Warehouse management system (WMS) software is a powerful tool that has been fine-tuned for decades to optimize the storage and flow of goods through a distribution center. But trends like the rise of e-commerce, omnichannel operations, and next-day delivery are putting tremendous pressure on the technology to evolve.
Recent improvements like cloud-based platforms and software-as-a-service (SaaS) delivery models have pushed WMS to new levels of performance. But competitive pressures continue to demand even more, and users in 2026 are turning to generative and agentic artificial intelligence (AI) to take the next step.
Experts agree that AI holds tremendous potential to deliver on that promise. But as warehouse management systems continue to soak up new “strains” of technology every year, everyday users are increasingly turning to their software vendors for guidance on how to use them.
Just ask Keith Whalen, corporate vice president for product management at supply chain software developer Blue Yonder. “Customers are asking about the journey of generative AI, saying, ‘Help us get to the next level and unlock new things,’” he says. “They want to reimagine traditional workflows, ease the burden of manual analytics, get better automation paths, and resolve problems faster.”
That may sound like a tall order, but Blue Yonder says it has already embedded AI capabilities into a number of its cloud-based modules as part of a recent series of upgrades. The company says the moves are aimed at transforming the WMS from a tool that optimizes fulfillment following static rules into a tool that constantly makes dynamic changes to improve fulfillment flows.
For example, the developer’s latest software version includes AI agents that “absorb” updates in real time, then apply what they learn to find better solutions. The agents follow that approach for the flow of goods in the warehouse itself as well as in related areas like supply chain networks and transportation management systems (TMS).
While powerful, this new approach can also be confusing to software clients who tend to be experts in logistics, not information technology (IT). So Whalen says he has been working closely with end-users to adopt new technology like AI in small steps, not in one great leap.
“Customers want to get moving on AI, but they also want to crawl and walk [before they] run,” he says. Blue Yonder does that by giving customers the opportunity to review AI-generated insights before approving the recommended changes. “Humans still want to be in the loop,” Whalen says.
THE AI AGENT IS AN ASSISTANT, NOT A CO-PILOT
Blue Yonder is not alone in its approach. Another big supply chain software developer, Manhattan Associates, recently added AI agents to its WMS and other supply chain software products and has been having similar conversations with users as they learn to use it. And like Blue Yonder, Manhattan says the new technology will allow its software to dynamically adapt to evolving needs as it orchestrates workflows, maximizing efficiency and minimizing risks.
“With agentic AI, we try to keep the applications concrete,” says Adam Kline, senior director for product management at Manhattan. “And we tell users that the technology is not a co-pilot but an assistant.” For example, the company’s WMS might flag a case where some orders can’t be fulfilled because of inventory shortages. But it doesn’t stop there. Manhattan says its new AI agent now tells users exactly which order can’t be fulfilled and why, and then presents them with options to fix the problem.
JUMPING INTO THE POOL
Other WMS developers are following suit. One example is Hardis Supply Chain, a French software developer that recently extended its reach into North America. Hardis says its Extended WMS Platform uses similar tools—such as AI and an API (application programming interface)-first architecture—to coordinate logistics across warehouses, factories, stores, and carrier networks, with real-time visibility and orchestration across every site.
Likewise, New Jersey-based software developer Made4net says its Retail WMS is designed to help users navigate the complexity of modern commerce by offering functions ranging from dynamic order orchestration and real-time inventory visibility to omnichannel fulfillment and performance tracking.
With WMS developers across the industry increasingly incorporating high-tech tools like AI into their platforms, the technology is rapidly evolving to meet the escalating fulfillment demands of today’s market. One result is the emergence of the so-called “dynamic WMS” that can adjust its workflows—and even the advice that its AI agents give to human users—to reflect operational changes in real time. And vendors say there is plenty more change to come.
In the words of Manhattan Associates’ Kline: “People think there’s no more innovation to be done in [warehouse management], but there’s still a lot of juice to be squeezed.”
