Agentic search and the next evolution of ecommerce buying

For most of ecommerce’s history, the purchase journey has followed a familiar pattern. Someone searches for what they want, compares a handful of options across one or more retailers, deliberates for a bit, lands on a product page, adds to cart, and checks out. That flow has been optimised relentlessly by conversion specialists and increasingly sophisticated software.

In the context of ecommerce, agentic search introduces something rather different. Instead of search leading someone to a store with product listings and merchant links, products and options are surfaced inside an AI conversation. The assistant does not just help someone find products. It can shortlist options, answer questions, handle objections and, in some cases, prepare an order ready for purchase.

This is developing quickly and it is worth paying attention to. Not because it replaces ecommerce as we know it, but because it introduces a new checkout lane alongside the ones brands already rely on.

What agentic search means in practice

At a high level, agentic search describes a shift from search as retrieval to search as action. Less “here is some information and links”, more “let me help you actually do the thing”.

In ecommerce, that thing is often buying something.

Practically speaking, this shows up in two connected ways. The first is conversational discovery. Shoppers describe what they are looking for in plain language, then refine their choices through follow-up questions. This already feels natural in AI tools and is changing how people research products.

The second is agentic action. The assistant can take steps on the shopper’s behalf. That might mean comparing options, checking availability, factoring in delivery times or preparing an order ready for checkout.

That second part is the real shift. When the assistant can act, the conversation stops being passive research and starts to look much more like a buying journey.

Why this matters now

AI is not replacing Google or traditional search for everyday use, and it probably will not for a long time. Habit is powerful, and search engines still do a very good job for many queries.

Ecommerce is different. People are already comfortable buying without “searching” in the traditional sense. They shop through marketplaces, social platforms, email, recommendations and repeat purchases. The path to purchase is already fragmented.

What is changing is where high-intent product research happens. Product comparisons, “best for” questions and specification-driven decisions are increasingly being handled inside AI tools, particularly by people who already use them day to day.

You do not need this behaviour to become mainstream overnight for it to matter. It only needs to influence enough buying decisions to start shifting how discovery and conversion work at the margins. That is usually how these things begin.

From conversation to checkout

Agentic search is often used as an umbrella term for experiences that behave quite differently in practice.

The most common model today is agent-assisted, merchant-led checkout. The assistant helps with discovery and decision-making, prepares the order, then sends the shopper to the merchant’s website to complete payment in the usual way.

A second model is emerging more gradually. Here, the entire journey, including payment, happens inside the AI interface itself. The customer never leaves the conversation and the order is placed without traditional navigation. This approach is live in limited contexts and is being actively developed, but it is not yet widespread.

Both models rely on the same fundamentals. Clear, accurate and structured product information.

What this changes for ecommerce teams

The biggest shift here is behavioural rather than technical.

When discovery and sometimes checkout happen inside a conversation, your product page is no longer the only place where your product is understood. Your storefront becomes the sum of your product data, policies, imagery and trust signals, whether or not the customer ever sees your website.

Brand experience also gets compressed. There are fewer opportunities to persuade through layout and long-form copy. Clarity starts to matter a lot.

At the same time, attribution becomes messier. More journeys begin in places analytics tools struggle to interpret, and fewer follow neat last-click paths. Customer ownership after purchase becomes more valuable, not less.

What ecommerce teams should do now

This does not require ripping everything up, but it does reward preparation.

Get your product data into good shape. Titles, variants, attributes and availability should make sense to someone who does not already know your brand. Tighten up policies that are likely to be summarised by machines, especially shipping and returns. Bring consistency to imagery so products present clearly wherever they appear.

Keep an eye on where traffic and assisted conversions are coming from, even if volumes are small, and focus on making your products easier to understand, easier to compare and easier to buy.

Final thought

Agentic search is not replacing ecommerce. It shortens the distance between intent and purchase and opens up a new lane alongside existing ones. For brands, that makes it less like a search trend and more like a development worth preparing for now rather than later.

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