The retail landscape has changed dramatically. Customers now expect instant answers about their orders, real-time inventory updates, and seamless returns. All delivered through AI-powered conversations. As retailers deploy AI agents to meet these expectations, one critical question emerges: where do these agents get their data?
The answer? From your distributed order management system (OMS). The central hub for all order-related data and operations. As such, the OMS is uniquely positioned to serve as the single source of truth that AI agents need to deliver exceptional customer service.
Starting Simple: Where Is My Order?
The most common customer service inquiry in ecommerce is straightforward: “Where is my order?” This simple question reveals why the OMS is essential for AI agents.
To answer accurately, an AI agent needs immediate access to two key data types.
- Order status information: Confirmation that the order was received, whether it’s been processed, if it’s currently being picked and packed, and when it shipped
- Tracking information: including the carrier being used, the tracking number, delivery status, and estimated delivery date
All of this data lives in your order management system. When a customer asks about their order, the AI agent queries the OMS and provides a complete, accurate response in seconds. No need to search multiple systems or ask customers for additional information, the OMS has everything in one place.
The WISMO Cost Problem
Here’s why this matters financially. WISMO (Where Is My Order) inquiries can represent 40-60% of all inbound customer service contacts. Each call may cost between $5.50 and $6.00 to process through traditional channels. For a retailer processing 100,000 customer service inquiries monthly, that’s 40,000 to 60,000 WISMO requests costing $220,000 to $360,000 every month, or $2.6 million to $4.3 million annually.
AI agents powered by your OMS data can handle these inquiries instantly and automatically, at a fraction of the cost. More importantly, this automation enables you to grow more easily. Without proportionally increasing your customer service team size. As order volume increases by 20%, 50%, or even 100%, your AI agents can scale effortlessly. Because they’re pulling data from a system designed to handle growth: your distributed order management system.
This isn’t about replacing human agents. It’s about freeing them from repetitive inquiries so they can focus on complex problems. The ones that require empathy, judgment, and creative problem-solving. The result is better service. Lower costs. And a customer service operation that scales with your business growth.
Expanding Capabilities: Order Modifications
As AI agents prove their value with basic inquiries, you can start to enable more complex actions. The next logical step is allowing customers to modify their orders before shipment.
Canceling orders requires the AI agent to access real-time fulfillment status data. The OMS knows exactly where each order sits in the fulfillment pipeline. If the order hasn’t been picked yet, the agent can cancel it immediately. If it’s already packed or shipped, the agent can inform the customer and offer return options instead.
Updating delivery addresses presents a similar challenge. The AI agent must check the current fulfillment stage, verify the new address, and update the order record, including the new expected delivery date. The OMS manages all these data points and provides the workflow logic to execute the change successfully.
These modifications aren’t just data lookups. They’re operations that require an AI agent to take action. Your OMS provides both the data and the operational framework to make these changes safely and accurately.
Advanced Operations: Returns and Exchanges
Returns represent one of the most complex customer service scenarios, involving multiple data types and operational steps. Yet this is where AI agents can deliver tremendous value by handling the entire process autonomously.
When a customer wants to initiate a return, the AI agent needs access to comprehensive data from the OMS, such as:
- Original order details including items purchased, prices paid, and payment methods used
- Return eligibility based on product type, purchase date, and customer status
- Inventory and location data to determine the best return destination and whether exchanges are possible
- Refund processing capabilities to calculate refund amounts and initiate payment reversals
- Return shipping options including carrier choices, prepaid label generation, and drop-off locations
The OMS has all this information and provides the workflows to execute returns efficiently. An AI agent can then use this data to:
- Verify eligibility
- Generate return authorization numbers
- Create shipping labels, and
- Set customer expectations about refund timing
All by connecting to the OMS as its data source. For exchanges, the complexity increases further. The AI agent must:
- Check inventory availability for replacement items
- Coordinate the return of the original product, and
- Create a new order for the exchange, often with special pricing rules
Only a system designed to manage order orchestration can handle this level of operational complexity.
Your OMS: The Hub for Order Data and Operations
A modern, distributed order management system is fundamentally different from simple order tracking tools. It serves as the operational hub for your entire commerce ecosystem. It manages not just data but the complex workflows that turn customer requests into completed actions.
Your OMS sits at the center of your operations. It connects digital sales channels, inventory systems, shipping carriers, pricing and promotions engines, and payment processors. It receives updates from all these systems in real time and maintains the definitive record of every order’s status and history.
This central position makes the OMS the natural single source of truth for AI agents. Rather than connecting agents to multiple systems (each with different data formats, update frequencies, and access requirements), you can provide one connection to the OMS that delivers everything the agent needs.
The benefits extend beyond simplicity. When AI agents rely on the OMS as their data source, you ensure consistency across all customer interactions. Every agent, whether handling a simple tracking question or a complex return, works from the same accurate, real-time information. There’s no risk of conflicting data or outdated status information causing customer frustration.
The Future of Agentic Commerce
As commerce moves toward automation, the OMS will define how intelligent your operations can become.
Tomorrow’s AI agents won’t just respond to customer questions. They’ll manage entire flows. Creating orders, reallocating stock, resolving exceptions, and continuously learning from outcomes. But to do that, they need a data foundation that’s clean, connected, and event-driven.
That’s the role of the distributed order management system. It’s not back-office plumbing anymore. It’s the operational brain that keeps every AI agent aligned with the truth of your business.
In a world where decisions happen in milliseconds, that truth is everything.
The Strategic Imperative
For C-suite leaders, investing in AI-powered customer service is essential for remaining competitive. But these investments only deliver results when AI agents have access to accurate, comprehensive, real-time data.
Your distributed order management system is the infrastructure that makes AI agents effective. Without it as your foundation, agents struggle with fragmented data, leading to poor customer experiences and operational inefficiencies. With a modern OMS at the heart of your operations, AI agents become powerful tools. Ones that reduce costs, increase customer satisfaction, and drive revenue growth.
The math is compelling. Eliminate millions in WISMO costs. Scale your business without scaling your support team proportionally. And deliver the instant, accurate service that today’s customers demand.
The future of commerce is agentic, intelligent, and customer-centric. But it all starts with having a single source of truth that your AI can trust. A modern OMS – like Fluent Order Management. If you want to find out how Fluent Order Management can ensure your AI agents are effective, contact us today.
