Traditional AI is quick to spot a demand shift. Agentic AI in retail responds before the window closes. It coordinates across merchandising, inventory, pricing, and fulfilment, keeping the right product in front of shoppers while your people stay in control of the calls that shape margin and brand.
Demand for agentic AI in retail is on the rise – and anyone who runs a retail business knows why. This sector never holds still: a promotion takes off, the weather turns, a trend catches fire online, a supplier slips, and stock has to be in the right place, at the right price, across every channel at once. Get it right and the shopper never notices. Miss it and you’re staring at empty shelves in one store and markdowns in another. Keeping that whole picture balanced – demand, inventory, pricing, and fulfilment – while the ground keeps shifting is the real work of a retail team.
Traditional AI already helps – forecasting demand, flagging a likely stockout, personalising an offer. Agentic AI is the next step. It doesn’t just see the shift; it coordinates the response across merchandising, inventory, pricing, and fulfilment – carrying approved actions forward and looping in your people when judgement is needed. It won’t replace the instinct that makes a great merchant. It extends it, across far more decisions than any team could track on its own.
Agentic AI in retail is a coordinated system of AI agents that work across your systems and teams to carry out operational tasks – not just analyse them. Where traditional AI identifies patterns and makes recommendations, agentic AI takes the next step: coordinating a response across demand, inventory, pricing, and fulfilment, using trusted data and your own business rules, with people in control.
The building block is the AI agent – a smart software assistant that monitors conditions, evaluates information, and carries out the tasks it was built for, usually within one area of the business, such as watching availability for a category or keeping replenishment on track. Agentic AI is what happens when many of these agents work together across processes, applications, and people – advancing routine work and making sure important details don’t fall through the cracks.
| Traditional AI | Agentic AI |
|---|---|
| Spots demand patterns, risks, and opportunities in retail data | Coordinates action across merchandising, inventory, pricing, and fulfilment |
| Produces forecasts, alerts, and recommendations | Carries approved actions forward within defined business rules |
| Typically supports a single team, function, or channel | Shares context across stores, e-commerce, inventory, and merchandising |
| Helps teams make faster, better-informed decisions | Helps coordinate the response when demand or supply shifts |
| Well suited to forecasting, personalisation, and decision support | Well suited to multi-step work spanning many teams and channels |
| Operates under direct human review and direction | Operates with human oversight while handling routine coordination |
| Delivers value through insight and prediction | Delivers value through orchestration, execution, and governed action |
Modern retailers are facing unprecedented complexities and competition. A single missed signal can have an impact upon dozens of global operational and customer touchpoints. And that is exactly the kind of fast-moving, interconnected work agentic AI is built to support – catching shifts early, understanding what they affect, and coordinating a response before a small problem becomes a big one.
Great retail depends on specialists like merchants, planners, allocators, store and e-commerce teams – all moving in concert toward a goal of getting the right product, in the right place, at the right price. Agentic AI works the same way. It isn’t simply a tool you bolt on, but several capabilities integrated into your systems and built to operate together, coordinating decisions, actions, and information across your business.
Retail is complex, following seasons, assortments, promotions, and the rhythm of how shoppers actually buy. Agents add the most value when they’re trained on your specific industry, its patterns, rules, and challenges. Their decisions can then best reflect how your business really runs.
A merchant, an allocator, or a store manager all must be able to get different things from the same data. Adaptive experiences surface the right priorities, dashboards, and next steps that are tailored for each role – cutting the time spent hunting across reports and screens.
Orchestration is the part that makes AI “agentic.” It is a coordination layer that tracks business rules, shared context, and progress. This lets agents to unify efforts and direct what happens next as they work across demand, inventory, pricing, and fulfilment, and much more.
When agents act across channels and have an impact upon pricing and customers, trust is everything. Agentic systems need clear business rules, role-based permissions, auditability, and human oversight – so every action stays transparent, accountable, and on-brand.
From demand spikes and stockouts, to markdowns and late suppliers, here's where agentic AI earns its keep: quickly grasping and coordinating responses to risks, sudden changes, and hot opportunities – from one end of your business to the other.
A promotion takes off, the weather turns, an online trend takes off – and demand suddenly moves faster than the plan. Agents can read these shifts, weigh it against stock and capacity, and coordinate the response. They can recommend transfers, reprioritize allocations, or resequence replenishment, ensuring that bigger calls get routed to your planners.
Curb-side pick-up, home delivery, or in-store purchasing are just a few of the purchasing and fulfilment options today’s customers expect. Agents weigh inventory, location, cost, and promised delivery times across all options. They then route each order the smartest way, helping you ease the cost of complex logistics, and protecting the margin on every fulfilment.
As inventory ages, your markdown strategy really comes down to two things: when to cut the price, and by how much. Agents can track sell-through, stock, and seasonality across multiple data sets and locations to propose the right cut at the right moment. This keeps pricing consistent across stores and channels and helps you clear out stock as profitably as possible.
Stock runs short in one store yet sits unsold in another. Agents are able to coordinate across inventory, orders, and transfers to rebalance this discrepancy in your network. They can steer surplus product to where data shows it will sell and avoid the cost of uninformed “just in case” stockpiling decisions – where surplus only gets discovered after it’s too late to adjust.
In its 2025 returns report, the National Retail Federation projects that U.S. returns will reach roughly $850 billion, with about 19.3% of online purchases sent back. Agents can help you more efficiently restock, transfer, and update availability in real time. But they can also spot the products and impulse buying patterns driving the highest return rates – so you can sharpen listings or limit an item's online reach.
If a vendor slips or a shipment runs late, this can (of course) have a direct impact upon customer experience and sales numbers. Agents can learn, spot, and report the early warning signs of these kinds of gaps, weighing alternate suppliers, adjusting open orders, and ensuring that merchandising, planning, and sourcing are all working from the same view.
The agents in today’s best agentic systems are trained on a vast range of real and relevant retail processes. They draw on trusted data, trigger approved actions, and orchestrate work across every system and channel in your business.
Before you point agents at anything, it helps to know where they’re likely to best perform. Process mining maps how work actually moves through your business in real time, not just how it’s supposed to on paper. It catches the delays, rework, and manual handoffs that hide across every area of your business. Process mining gives you the evidence for where to start.
Agents are only as good as the data you give them. In retail, that cross-channel information spans demand, POS and e-commerce sales, inventory, pricing, promotions, supplier performance, and more. A cloud-connected, well-governed data foundation lets agents reason from one shared view of the business instead of trying to sift through siloed or conflicting intel.
Retail work typically must span several of your systems to get done, and it depends on data flowing in from suppliers, carriers, and other external partners. Integration connects those systems with partner feeds and compiles that data into one shared view. Agents can then act on the whole picture and carry a process through instead of stalling where information breaks.
Modern retail teams already automate many routine tasks. Agentic AI builds on that foundation to better decide when, where, and how each automation should run as conditions change. This means your existing processes not only keep running; they keep improving to absorb new channels, seasons, assortments, or whatever is fluctuating and shifting in your business.
A single response can span many steps and systems, and something has to hold it all together. The orchestration layer decides what happens next, keeps every agent working from the same goal, and carries the whole effort toward the outcome you approved. Routine steps resolve on their own and anything that requires human judgement arrives with context already provided.
As agents take on more, the trail they leave behind must be clear. Every single action is logged, reversible, and can be explained on demand, so you can always see what happened, on which data, and under which rule – with no black-box decisions. Where pricing, customer data, and brand reputation are on the line, that provides the ability to safely make faster, more confident decisions.
Agentic systems are built to remove errors, chase down details, and keep routine work moving. But what they can’t supply is human judgement. No AI can replace the merchant's instinct for a hot trend, the sales team's read on their customers, or the feel for a brand that comes from years of experience. When a decision impacts your reputation, customers, or bottom line, that judgement is invaluable.
So, the aim is never to hand retail entirely over to software agents. It’s to leverage those agentic tools at every step, letting them complement and empower your talented team members – making them faster, more accurate, and more confident, without losing the value of their learnt skills and instincts. Furthermore, “in the loop” has to mean more than a final approval click. It’s essential to set clear rules for agents to explain why issues are getting escalated to humans, and what specifically needs to be addressed.
Done well, oversight makes the whole system stronger. Routine exceptions clear themselves, and the decisions that do reach your team members arrive with the context already gathered and some viable options laid out. And because every action is traceable, there’s always a named owner behind the calls that shape your business. Most retailers are already formalising that discipline: 86% now have AI governance policies in place (NRF). That accountability isn’t a constraint on good retail. It’s part of what protects and nurtures it in a fast-changing market.
When you start with mature, industry-specific software solutions, a lot comes built in – like governance, business rules, and proven integration. The harder problems tend to emerge when teams assemble agentic capabilities themselves, without those foundations. Below are a few common challenges and how to steer around them.
It can be hard to know which calls an agent can make by itself and which need a person. The best plan is to define and enforce – as early as possible – clear agreed-upon rules and escalation paths. This ensures accountability across all your operations.
Prices, promotions, assortments, and store clusters are constantly changing. If agents work from bad data, they’ll coordinate the wrong things – and do so with confidence. Keep pricing, promo, and assortment data current and reflected everywhere agents can reach it.
Agents act fast – sometimes too fast. An agent that over-reacts to a short-lived trend can leave you with the wrong stock in the wrong place. Set guardrails and establish a range of clear thresholds so agents know when to hold steady and when a person should weigh in.
Early experiments can spawn siloed agents, trained to optimise just one operation with no shared context. Agentic initiatives work best when agents can operate across many operations in real time, assessing multiple data sets and focusing on business goals.
Success isn’t measured by how many things you’ve automated. The metrics that matter are the ones you already know about such as sales, gross margin, sell-through, in-stock rates, markdown, shrink, and inventory turns. Measure those, and the agentic value picture gets clearer faster.
Strip away the modern bells and whistles, and retail has always come down to a simple promise: have what the shopper wants, where and when they want it, at a price that works for both of you. And while that promise has never changed, pretty much everything around it has. There are more channels, choices, competition, and complexity than at any time in the past. To meet these challenges, retail technology has had to evolve quickly and meaningfully – with agentic AI emerging as one of the most powerful and competitive innovations this sector has ever seen.
Used thoughtfully and governed well, an agentic system more than earns its place. It senses shifts early, coordinates the best responses across every channel, and frees up your merchants and planners for the tasks and decisions that need them most. The goal is not to build stores that entirely run themselves. Rather, the aim is to build retail networks that run better – are more available, more profitable, and more in tune with the needs of both your customers and your valued team members.
Discover how Infor Velocity Suite can help transform your retail business into an agentic enterprise – no matter where you are on your journey.
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