AI Agents For Retail: How Retail AI Agents Work

AI agents are changing retail operations—answering customer questions at 2 a.m., automatically reordering inventory, and drafting marketing emails in seconds. And these capabilities aren’t reserved for massive brands with multimillion-dollar tech budgets.

Take Naadam, a direct-to-consumer (DTC) cashmere brand, which now uses AI to handle all frontline customer support. “Customers email to say, ‘I love so-and-so; they were so helpful,’ and I’m like, ‘That’s not a person; that’s an AI agent,’” founder Matt Scanlan says on an episode of the Shopify Masters podcast. With AI agents handling routine support inquiries, Naadam’s human team has more bandwidth for strategic initiatives, like product development and marketing.

Here’s how AI agents for retail work and how you can use them to improve customer satisfaction and operational efficiency—and deliver exceptional customer experiences.

What are AI agents for retail?

AI agents—or agentic AI systems—are intelligent systems that can complete tasks on their own. In the retail industry, they are autonomous software programs that act on behalf of your business—like digital employees. 

Unlike basic, rules-based automation, which follows a script (“if a shopper abandons their cart, send them an email”), an AI agent can observe customer behavior, decide what to do next, and act, either entirely autonomously or with minimal human intervention. And while an ecommerce chatbot typically responds to customer messages within a limited conversational script, an AI agent can access multiple business systems, make decisions, and take actions beyond a single chat interaction.

Agentic AI systems connect to your business’s existing data and tools—such as your product catalog, email marketing platform, shipping provider, and internal documentation—to understand your products, policies, and customers. They can act on that knowledge, whether by answering a customer’s sizing question or drafting an on-brand marketing email.

Alex Pilon, a senior developer at Shopify, describes an agent as “a purpose-specific configuration of AI” that’s been “tuned for a particular task or workflow.” AI agents take different forms, and many businesses use multiple agents, each specialized for a different job. Some handle customer interactions, like guiding shoppers to the right product via chat, while others manage back-office operations, like inventory management.

What can an AI retail agent do?

In practice, AI agents often follow what McKinsey calls “optimal delegation”: Human agents define the goals, set guardrails, and handle work that requires judgment or creativity, while AI agents take on the high-volume execution. 

Here are a few key ways that AI agents are working alongside humans in retail: 

• Customer support. AI customer support agents field common customer inquiries, providing 24/7 responses across chat, SMS, and phone, while routing more complex or sensitive cases to your human team.

• Sales. Virtual shopping assistants boost sales by drawing on customer data—like browsing history and past purchases—to surface relevant products and deliver personalized shopping experiences. 

• Marketing. AI agents connect to your business systems to generate and execute marketing campaigns. For example, an agent writes 100 ad copy variations for paid search ads, tests them on virtual audiences, and then deploys the winners in Google Ads on your behalf. 

• Agentic commerce. New agentic commerce protocols enable checkout directly within AI conversations on platforms such as ChatGPT, Google AI Mode, Gemini, and Microsoft Copilot. A shopper describes what they’re looking for, and the agent searches across retailers, presents results with details, and either provides a link to buy or completes the checkout in the conversation. 

• Inventory and supply chain. Intelligent agents monitor inventory levels and forecast demand so your team can make smarter purchasing decisions about what to buy and when. AI agents can also be configured to take action—for example, automatically placing orders based on their analysis or pausing ads based on buying signals and inventory.

Real-world examples of AI agents in retail 

• Automating customer support
• Inventory planning and demand forecasting
• Generating marketing content
• Selling products directly through Al platforms
• Simulating buyer behavior

The best way to understand what AI agents can do is to look at who’s already using them and how:

1. Automating customer support

Naadam transitioned its frontline customer service team to AI agents—a change the company says reduced operating expenses without sacrificing the customer experience.

Accessories brand Ridge also strengthened its support operations with AI customer service agents—a key part of the company’s ability to operate efficiently and generate $5 million in revenue per employee. “At this point, it’s like 60% of our tickets are being answered by AI,” CEO Sean Frank says on an episode of Shopify Masters. “It’s quicker; it’s more accurate.” 

If you’re interested in automating your support function with customer service agents, start with responses to your highest-volume inquiries—like order status, return instructions, and product availability. Shopify store owners have access to Shopify Inbox—a live chat and messaging app that can help automate routine customer communications.

2. Inventory planning and demand forecasting

Inventory planning—determining how much stock to hold and when to reorder it to meet customer demand—is one of the most time-intensive parts of retail operations. It’s also one of the easiest to hand off to AI.

Agentic systems are built to analyze multiple data streams (such as historical sales, seasonal patterns, current sales velocity, and upcoming product launches) and make a call about what SKUs to order and how many units. In some configurations, they can trigger the reorder automatically. They can also flag a product that’s selling faster than expected and needs to be reordered early or identify a slow-moving product that should be marked down.

3. Generating marketing content

What separates an AI marketing agent from a simple content generator is that it’s connected to your business systems. It can access your performance and sales data, glean what’s working, and then take action on that knowledge. 

“If you want to make a marketing agent,” Alex says, “you tell it that it’s an expert marketer, give it information about the system it’s working with, give it tools to set data and make campaigns, and hook it up to documentation. It’s not only a marketing expert, it’s a marketing expert that's connected to my systems in my business.”

Ridge built an automated system that generates 500 static ads a day. Sean says the entire pipeline runs automatically—“no hands on keyboard.” Humans set the creative direction and curate what runs; the agent handles the output at scale. As Sean says, “Our design team will always produce the 10-out-of-10 ads,” but the AI provides volume for ad platform algorithms to test.

Shopify Magic offers AI text generation, media creation, and email drafting. You can also use Marketing Automations to personalize messages across email, SMS, and push notifications based on customer behavior. 

Purpose-built agents can also further refine the content development process by testing creative via virtual focus groups and running winning variants on various paid marketing platforms.

4. Selling products directly through AI platforms

A shopper opens ChatGPT and says, “Find me a high-quality, waterproof parka under $300 for a trip to Iceland.” The AI agent searches across sellers, finds in-stock options that match, shows pricing and product details, and enables checkout—all within the conversation. 

This is now possible thanks to Shopify Agentic Storefronts, currently in early access for Shopify store owners. It lets you list and sell your products directly through ChatGPT, Google AI Mode, Gemini, and Microsoft Copilot, so shoppers can find your products, compare options, and check out without ever leaving the AI chat. Shopify’s Universal Commerce Protocol (UCP) provides the infrastructure that lets AI agents discover your products and complete transactions within these conversations.

The Shopify Knowledge Base app works alongside Agentic Storefronts, giving you control over how AI agents answer when customers ask about your brand’s return policies, sizing guidance, shipping windows, and other frequently asked questions.

“Agentic shopping enables us to meet customers where they already are,” says Victor Tam, CEO and cofounder of luggage brand Monos, in a Shopify press release. “It’s a new way for our story and product details to show up at the exact moment someone is asking real questions with real intent, in a format that feels helpful, not intrusive.”

The next step toward agentic shopping is for a customer’s AI agent to make the purchase for them. The infrastructure for fully autonomous purchasing, where a customer’s AI agent makes a purchase on their behalf, is now taking shape. Visa and Mastercard are piloting agent-led payment systems that make autonomous purchases, and Google’s Agent Payments Protocol (AP2) is designed to let AI agents make purchases with user-set budgets and guardrails. McKinsey projects agentic commerce could account for $3 trillion to $5 trillion of global consumer spending by 2030.

5. Simulating buyer behavior

AI agents allow you to test and optimize the design of your storefront by simulating how shoppers navigate and interact with your site. These simulated “AI shoppers” can identify usability issues and provide insights for design decisions. 

Shopify SimGym, currently available as an AI Research Preview, works like a flight simulator for your store. It runs AI shoppers with realistic personas through your storefront and reports back on performance—including add-to-cart rates, site navigation patterns, and average cart value. If you’re planning a site redesign, you can compare two themes and see which performs better—and get specific recommendations for improvement—before a single customer sees the change.