---
source_url: "https://www.forbes.com/sites/catherineerdly/2026/02/22/a-2026-guide-to-getting-agentic-ai-to-recommend-your-e-commerce-site/"
title: "2026 Guide: Agentic AI To Recommend Your E-Commerce Site"
mirrored_at: 2026-08-28T01:31:38.829Z
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> **Original source:** https://www.forbes.com/sites/catherineerdly/2026/02/22/a-2026-guide-to-getting-agentic-ai-to-recommend-your-e-commerce-site/

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In 2026, increasing numbers of customers will be using Agentic AI to make purchasing decisions. The key question that retailers and ecommerce brands need to answer is "how do I make it into these suggestions?"

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Retailers have spent years learning how to get found by humans - win a ranking, earn a click, convert a landing page. But in 2026, that discovery moment is increasingly being mediated by something else: agentic AI that researches, compares, and recommends before a shopper ever opens a browser tab.

[One of the key retail industry trends](https://www.forbes.com/sites/catherineerdly/2025/12/22/3-major-retail-trends-that-will-reshape-retail-in-2026/) for [2026](https://www.forbes.com/sites/catherineerdly/2026/01/25/7-consumer-trends-that-define-what-shoppers-want-in-2026/), agentic AI is already mainstream. Data from the [Organisation for Economic Co-operation and Development (OECD)](https://www.oecd.org/en/about/news/announcements/2026/01/ai-use-by-individuals-surges-across-the-oecd-as-adoption-by-firms-continues-to-expand.html) shows that more than one-third of individuals across the OECD used generative AI tools in 2025, a sign that AI is quickly becoming part of everyday decision-making, including shopping.

Furthermore, recent research from payment provider Checkout.com showed that 42% of consumers used AI to research gifts for Valentine’s Day, indicating how embedded and widespread it is becoming into consumer behaviour, even for highly personal occasions.

For e-commerce teams, the question is no longer just “How do we rank?” It’s: “How do we become the suggestion when an agent is asked to find the best option for a specific need?”

Five experts weighed in with the most practical steps retailers can take right now to improve their odds.

## Make Your Catalog Readable by Agentic AI

The fastest way to disappear in an agentic world is to assume good branding will carry you. Agents can’t recommend what they can’t reliably read. That makes product data less of a technical footnote and more of a growth lever.

MORE FOR YOU

Juan Pellerano, chief marketing officer of global commerce platform SWAP, puts it plainly: “The first priority is \[to\] make sure \[your\] website and product catalogue are agent-ready … does your site have rich structured data (i.e. JSON-LD), an AI-specific sitemap with robot permissions, and product catalog APIs? These are foundational, code-level changes—and without them, AI agents simply won’t “see” your products.”

In other words, before chasing clever prompts or new distribution channels, make sure your catalog is legible. Products need clear attributes. Policies need plain-language certainty. And your pages need to be accessible to the systems trying to understand them.

## Ditch the Keywords and Write Like Your Customers Speak

Agents don’t shop like traditional search engines. They respond to intent expressed in full sentences, from conversational search.

Chris Donnelly, founder of AI search optimisation software [Searchable](https://www.searchable.com/), describes the shift this way: “We have moved from a search bar to a chat interface, both in terms of typing and the rise of voice transcription. Shoppers no longer search for 'running shoes'; they ask, 'Which trainers are best for marathon training if I have flat feet?'”

That changes what “good content” looks like. Product pages need to answer questions, not just describe features. Category pages need to clarify tradeoffs, not just list SKUs. FAQs need to mirror the way customers actually ask for help, not the way internal teams label tickets.

The brands that show up more often will be the ones whose sites make it easy for an agent to extract a confident recommendation because the page already speaks the shopper’s language.

## Build a Trust Footprint Beyond Your Own Site

One of the biggest mistakes retailers can make is treating agentic discovery like a domain-only game. Agents cross-check and look for external validation. They compare what you claim with what the wider web seems to agree is true.

As Donnelly notes, “AI agents are now the ultimate personal shopper, and they are highly skeptical. To avoid recommending misinformation, they look for 'consensus' outside of your website.”

That “consensus” can come from many places, such as reviews, listings, editorial coverage, creator content, forums and more. But the principle is consistent. If your brand’s claims don’t echo elsewhere, then an agent may downgrade confidence even if your site is polished.

In practice, that means agents are likely to weigh signals like reviews, reputable coverage, and consistent listings more heavily than marketing copy.

In many ways, this is no different from existing SEO best practice, such as cultivating backlinks from relevant sites to help boost the domain authority of your own website. This task simply takes on an additional level of urgency as brands and retailers scramble to make sure they are clearly positioned to show up in agentic AI search results.

## Treat Your Brand Facts Like a Product

When AI systems cite and summarize, being accurate starts to matter as much as being persuasive. This is where retailers can regain control, because many of the strongest sources are the ones brands already manage.

Sam Davis, vice president at brand visibility platform Yext, says, “Our latest [research](https://www.yext.com/research/article/ai-citations-user-locations-query-context#introduction) shows that 86% of AI citations come from brand-controlled sources such as websites, listings, and reviews. In retail, almost half of those citations come directly from first-party websites.”

That’s good news, but it comes with a warning. If your stock, pricing, shipping promises, and return policies are inconsistent across pages or out of date, you are not only confusing customers but also training agents to hesitate.

Retailers that win this year will behave more like data publishers: one source of truth, updated relentlessly, distributed consistently across the places agents look to verify.

## Prepare for Agent-to-Agent Commerce

After visibility, the next battle is transactability: can an agent not only find your products but also confidently complete a purchase flow, or at least package your offer into a clean, accurate recommendation?

This is also why infrastructure announcements are accelerating.

Shopify recently unveiled the [Universal Commerce Protocol (UCP)](https://www.shopify.com/news/ai-commerce-at-scale), an open standard it co-developed with Google to help bring commerce to agents at scale. The specifics will evolve, but the direction is clear: more buying journeys will begin as a prompt, and end as a structured exchange of product, policy, and checkout information between systems.

Andrew Bialecki, co-founder and co-CEO of marketing automation software Klaviyo, sees the same shift coming.

“As agentic commerce grows in popularity, retailers need to prepare for a world where discovery isn’t just about browsing webpages but increasingly shaped by agent-to-agent interactions.”

For retailers, that’s the 2026 reframing: Brand visibility is no longer just about earning clicks. It’s about earning _confidence_.

The stores that agentic AI recommends will be the ones they can parse quickly, verify across multiple sources, and transact with cleanly because the facts are consistent, the promises are clear, and the buying journey leaves no ambiguity.