AI agents—software programs that use artificial intelligence to independently complete tasks—are changing how ecommerce businesses operate. They give you the ability to automate tasks across a range of operational functions, such as managing inventory, sending marketing messages, reconciling financial records, and handling routine customer questions.
More than 60% of respondents in a 2025 McKinsey & Company survey say that their companies are at least experimenting with agentic AI. As adoption accelerates, 63% of global retailers surveyed for a 2026 Deloitte report believe retailers that fail to implement agentic AI technologies are likely to fall behind their competitors within two years.
Here’s where and how to use AI agents to streamline your ecommerce operations, automate routine tasks, support decision making, and free your team to focus on higher-value work.
What is agentic AI?
Unlike traditional AI systems that perform predefined tasks, agentic AI systems can complete multistep tasks with minimal or no human supervision. In ecommerce, AI agents typically work by connecting to your business systems—such as your ecommerce platform, customer relationship management (CRM) system, or accounting software—so they can gather the information needed to complete tasks.
How much independence you give these autonomous systems varies: You can require check-in before anything is finalized or, once you’ve confirmed the agent works accurately and consistently, let it run tasks start to finish.
For example, you might ask an AI agent to “build me a report on last quarter’s sales and send it to the sales manager.” The agent determines how to perform the work, pulling sales data from your ecommerce platform, calculating trends, identifying bestsellers, writing a summary, and checking the report for errors. Depending on how you’ve configured it, the agent can then either present the completed report for your approval or send it directly to the sales manager on its own.
7 agentic AI use cases in ecommerce and retail
- Website testing
- Sales and marketing
- Customer service and support
- Inventory management and demand forecasting
- Finance and bookkeeping
- Security and fraud detection
- Application design and creation
Ecommerce businesses have adopted AI agents to automate complex workflows across a range of operations. Here are seven examples:
1. Website testing
AI agents can help you improve your storefront by testing changes before the site goes live. Shopify’s SimGym app, for example, deploys hundreds of AI shoppers that browse your store like real customers, navigating collections, adding products to their carts, and evaluating the shopping experience. It can compare two themes or analyze a single storefront and then provides feedback you can use to improve conversion before publishing your site.
Using simulated AI agents allows you to perform A/B testing in minutes instead of waiting days or weeks—or even longer for smaller or new businesses—for enough real customer traffic.
2. Sales and marketing
Agentic AI solutions have the potential to automate much of the sales and marketing process. McKinsey estimates that AI agents could eventually handle about 60% of work across core marketing workflows, including strategy, content creation, campaign execution, and optimization.
Water-filter maker LifeStraw uses Flows AI from Shopify partner Klaviyo to create marketing automations using natural language prompts. Rather than manually configuring each trigger and workflow step, ecommerce head Eugenia Martin described the type of automation she wanted, and Flows AI generated the workflow structure for her. This saved more than 40 minutes per workflow, according to a Klaviyo case study.
3. Customer service and support
By 2029, Gartner predicts AI agents will resolve 80% of common customer interactions without human intervention, helping organizations slash operational costs by an estimated 30%. AI support agents are always available, can handle large volumes of customer queries with little to no wait time, and often cost less than human agents.
AI agents can do more than answer routine questions: They can draw on a customer’s purchase history, account details, unstructured data such as emails, and your product catalog to resolve issues and recommend relevant products. In the 90 days after deploying Klaviyo’s Customer Agent, LifeStraw reported an 111% increase in agent-recommended sales—and the agent resolved 75% of customer inquiries without human help.
4. Inventory management and demand forecasting
AI agents can continuously monitor inventory levels, forecast demand, and generate purchase orders before you run out of products. By automating much of the planning process, you can reduce manual work while keeping inventory aligned with customer demand.
For example, coffee brand Kuppa Joy uses an AI-powered inventory management tool from Prediko to automate purchase planning for its warehouse operations. Instead of deciding how much of each item to order manually, the company tells Prediko how many days of inventory it wants to keep on hand, and the system automatically generates purchase orders based on actual usage, seasonal trends, and lead times required for delivery.
As a result, the company reports saving 10 hours a week of inventory work while reducing order errors by 90%.
5. Finance and bookkeeping
Tasks that can take a human accountant hours—categorizing transactions, reconciling accounts, flagging questionable charges—can be handled largely autonomously by AI agents. Instead of waiting for your finance team to perform these tasks at the close of each month, AI agents monitor activity continuously, update accounts as transactions occur, and alert you to anomalies.
Apparel brand Dumbclub uses the Finaloop AI-powered accounting app to automatically categorize transactions as they happen, calculate cost of goods sold (COGS), reconcile accounts, and generate real-time financial reports. Dumbclub founders report having a continuous view of cash flow and profitability, which helps them decide when to increase or scale back marketing spend. The company also reduced bookkeeping and accounting costs by 40% to 50%.
6. Security and fraud detection
AI agents can actively defend your store against fraud and abuse. As traffic arrives, an agent can determine whether a visitor scanning your product catalog is a human or a bot and whether that bot is friendly (like a ChatGPT shopping assistant sending you a customer) or malicious (a scraper harvesting your content or prices). It then admits, challenges, or blocks the bot accordingly.
AI agents can also evaluate each transaction in real time, clearing legitimate orders while stopping suspicious ones, so you cut fraud losses without adding friction for real customers.
For example, Cymbiotika, an organic supplements shop, was suffering from high rates of false positives from its fraud detection systems. According to a case study, too many legitimate purchases were being flagged, leaving customers frustrated and costing the store revenue. The company turned to Signifyd, an AI commerce protection platform available in the Shopify App Store whose AI agents analyze each transaction, approve legitimate purchases, and reject suspicious transactions. As a result, Cymbiotika boosted its order approval rate to 98% and reduced chargebacks by 93%.
7. Application design and creation
AI agents let people with minimal coding skills build working apps using natural language instructions. Describe what you want the app to do, and a coding agent can build it for you, handling critical functions (like security protections) automatically.
For example, the developer of Shopify app ReviewMate, which helps stores collect and showcase customer reviews, built the application primarily by prompting Claude Code with natural language instructions. Claude generated more than 95% of the production code, including the application’s architecture, database design, APIs, security features, and error handling, while the developer focused on defining requirements, testing, and refining the results.
Shopify developers can connect AI coding agents like Claude Code, OpenAI Codex, Cursor, Gemini CLI, and VS Code directly to their stores through Shopify’s AI Toolkit. In addition to building new apps, these AI tools can help update products and automate store operations using natural language instead of requiring developers to write every line of code by hand.
Agentic AI use cases FAQ
What’s the difference between generative AI and agentic AI?
Generative AI creates content (text, images, code) in response to a single prompt, then stops and waits for your next instruction. Agentic AI takes a goal and may use multiple systems to reach it—researching, deciding, acting, and checking its work, without needing you to guide each individual step.
What’s an example of agentic AI in business?
A common example is an AI coding agent like Claude Code. Describe the kind of app you want it to build, and Claude figures out how to structure the code, write it, test it, fix any errors it finds, and deliver a finished product—without requiring human oversight of each step.
What are three common use cases of agentic AI for any business?
- Support agents that resolve queries by accessing live account and customer data, instead of simply relying on scripted responses.
- Finance and bookkeeping agents that automatically categorize transactions, reconcile accounts, and flag anomalies in real time.
- Fraud-detection agents that evaluate each transaction and independently approve or reject it based on risk, rather than simply flagging potentially fraudulent orders for human review.
