Almost every retail technology team is having the same AI conversation right now: "How do we get AI into our systems quickly?" "What can we implement in AI to relieve the workload?" "What can AI automate?"
It is an understandable response to real pressure. Boards want to see AI strategies. Vendors claim to be ready with answers. And order management, with its complexity, its exception volumes, its constant friction between what was promised and what can be fulfilled, feels like exactly the kind of problem an intelligent agent should be able to solve.
Except it mostly cannot, or at least not in the way it is currently being applied today. An agent does not create intelligence; it acts on the data the system already has. And in most order management environments, that data is fragmented across silos and already stale by the moment a decision is made. Speed was never the problem. The completeness of what it is deciding on is.
The problem with silos that nobody names directly
Most enterprise order management environments were not designed as unified systems but evolved from new features developed in silos as business needs emerged. Available to Promise (ATP) gets managed in one place, allocation logic in another, and fulfilment execution somewhere else. Returns sit downstream in a separate queue, reconciled on a batch cycle rather than in real time. Each layer was optimized for its own function, connected to the others through integrations that were good enough when order volumes were lower and fulfilment networks were simpler.
An AI agent dropped into that environment does not fix the fragmentation; it simply inherits it. The reality is: An agentic recommendation made on fragmented inventory and order data that is thirty seconds stale may be fast, but it is not intelligent. A sourcing decision that does not account for what the warehouse is capable of today or the margin pressure the markdown team is managing is not optimized because it is incomplete. The agent simply becomes a more sophisticated interface to a system already making decisions with partial information.
This is the distinction that we are drawing. Agentic capability and data infrastructure connectivity are not the same investment - and conflating them is where we see the gap between what OMS modernization promises and what it delivers.
What we believe the IDC MarketScape recognition is validating
IDC MarketScape has positioned Blue Yonder in the Leaders Category in its 2026 Worldwide AI-Enabled Order Orchestration and Fulfilment Applications for Retail and B2C Vendor Assessment. The recognition matters, but more importantly, we believe it is critical to dissect the language and priorities that IDC MarketScape is evaluating as a leader in the OMS space.
Factors such as Real-time inventory visibility across channels, ML-based sourcing decisioning, depth of omni-channel fulfilment execution, and the scale to perform at high transaction volumes and across extensive store networks. These are not AI feature callouts, but connectivity callouts. This reinforces the importance of building the right foundation for your OMS – Driving a unified picture of inventory, orders, fulfilment capacity, and returns – which is what will make any AI implementations subsequently trustworthy. Because it reflects what is happening across the network, on a single platform that shares unified data.
What connected intelligence looks like in practice
When ATP and allocation run on unified data rather than syncing in batches, the availability picture that drives a promise is the same one that drives the sourcing decision behind it. When store capacity, labor signals, safety stock, and markdown risk inform fulfilment decisions in real time, the agent can recommend a routing action based on a complete operational signal rather than a snapshot. When a return re-enters the live inventory layer, forward orders & availability see it immediately instead of waiting for it to process in the warehouse.
AI then taps into the connected intelligence to provide the right metrics, briefs, and contextual recommended actions. But ultimately, It is a data architecture story that enables the AI story, and that changes the investment question. For the person doing the work, this is the difference between chasing answers across systems and different agents versus seeing them in one place, drawing on the same live picture.
[Blue Yonder processed over 444 billion SKU queries at 16 milliseconds average response time and 18 million real-time reservations at 30 milliseconds during 2025 peak]
Where we believe the market is heading and what to watch for
We believe the IDC MarketScape's assessment describes embedded agentic assistance as an emerging capability across the retail OMS category. That framing is accurate: The category is moving from AI at the edges toward AI embedded across the full order lifecycle, from promise through fulfilment through exception handling through returns recovery.
We also believe the vendors who deliver on that shift are the ones who invested in connectivity first. An agent that can see the full lifecycle and act within it rather than alongside it, is a fundamentally different capability to one operating on partial, fragmented data.
The question worth asking
Before the next OMS evaluation, before the next AI demo, ask a simpler question: When your OMS makes a sourcing decision, what data is it working from, and how current is that data at the moment the decision is made? How much of your returns are connected back into the order lifecycle via recommerce and disposition?
The answer will tell you more about what you are looking at than any feature comparison will. AI agents are a meaningful part of what modern order management needs to become. But the foundation they run on determines whether they improve your operation or simply accelerate the same decisions you were already making on incomplete information.
Connected intelligence is not a product feature. It is an architectural commitment. And in 2026, it is the commitment that separates credible AI in OMS from the version that looks good in a demo.
IDC MarketScape: Worldwide AI-Enabled Order Orchestration and Fulfillment Applications for Retail and B2C 2026 Vendor Assessment, #US53010725, July 2026
