What is AI agents?

Unlike a search bar or a question-answering tool, an AI agent can chain multiple steps together: look something up, evaluate the result, decide what to do next, and act on that decision. Agents are given a goal and the tools to reach it, then left to work through the problem on their own. In commerce, this might mean browsing product categories, filtering by criteria, reading descriptions, and surfacing the best match - all within a single session.

How does ai agents work?

• The agent receives a goal from the user (for example, 'find me a reliable SUV under $40,000').
• It selects from a set of available tools - web search, catalog lookup, comparison functions - and decides which to call first.
• It evaluates each result and decides whether to refine, continue, or stop.
• When it reaches a satisfactory outcome, it returns the result or takes a final action like adding an item to a cart.

Why does it matter?

For ecommerce and dealership operators, AI agents represent a shift in who - or what - is doing the shopping. An agent browsing your catalog needs clear product data, well-structured descriptions, and accurate availability information to make the right decisions. Stores with sparse or inconsistent product content risk being skipped over entirely when agents are making the call.

As AI agents begin shopping on behalf of users, a structured, well-described storefront like the one Nobi enables is easier for them to navigate and more likely to surface the right products at the right moment.

Frequently asked questions

Are AI agents the same as AI assistants? Not exactly. An AI assistant answers questions and waits for the next prompt. An AI agent can pursue a multi-step goal on its own, taking actions and adjusting its approach until the task is complete.

Can AI agents actually make purchases? Some can, when given access to payment and checkout tools. Most current deployments stop at recommendations or adding items to a cart, with the human completing the final step.

What should merchants do to prepare for AI agent traffic? Focus on product data quality - complete descriptions, accurate attributes, and consistent naming. Agents rely on structured information to make decisions, so gaps in your catalog are harder to recover from than they are with human browsers.