When AI Agents Become the Shopper

Winning Digital Shelf Visibility in the Era of Agentic Commerce

By Rachel Birch & Andrew Turner · House Digital · June 2026

Search isn’t broken. But how people use it has fundamentally changed, and for retailers and brands, the consequences are significant. AI agents are increasingly doing the browsing, comparing, and recommending. If your products aren’t visible to these systems, you’re not on the shelf at all.

FROM SEARCH TO SUGGESTION

How shopper discovery has changed

The way people are using Google has changed dramatically…and quickly. Searches are getting longer and more conversational: traditional search averages 3–5 words; AI-powered search (Google AI Overviews) more than 8 (+800% growth); LLM-based search (ChatGPT, Claude, Perplexity) more than 20.

Over 50% of Google searches now return an AI Overview, up from near zero in mid-2024.

And according to McKinsey’s AI Discovery Survey (August 2025, n=1,927), AI-powered search is being used at every stage of the purchasing journey, not just awareness. Around 60–73% of users are turning to AI tools across awareness, consideration, and decision stages.

AI-powered search use cases by stage of purchasing journey (McKinsey, August 2025)

The implication: your brand’s AI visibility matters from the moment someone starts learning about a category, all the way to the final purchase.

WHY AI CHOOSES CERTAIN BRANDS

The three signals that determine AI visibility

Traditional SEO has had 30 years to mature. Major LLMs have been around for roughly one-tenth of that. We’re in the early days, but here at House Digital, we’ve analysed the data and determined three major signals emerging.

Accessibility: Can AI agents read and extract your data?

If your site renders product information via JavaScript with no structured schema, you’re invisible to AI crawlers. Fix: HTML text format, server-side rendering, agentic schema, crawlable navigation, and clear product USPs.

Authority: Do AI agents trust your data sources?

Authority is transitive, if a trusted site cites you, the LLM trusts you. Are you referenced on Wikipedia, Crunchbase, GS1? Do editorial sites link to you? Is there genuine human commentary on Reddit, Trustpilot, or review roundups?

Abundance: Does your content provide comprehensive, unique value?

AI searches are conversational. Someone asking about a casserole dish wants to know about materials, heat retention, cleaning, and induction compatibility, not just the product name. High density factual content, clear structure, and topic first writing wins.

“A smaller brand with genuinely rich, well structured content can outrank a market leader in AI search. Content depth matters more than domain age.”

We saw this in action: Pyrex outranked Le Creuset in Google AI Mode for “what to look for in a high quality casserole dish” not because of brand strength, but because Pyrex had invested in a long-form guide covering exactly what the AI needed to answer the query.

MAPPING THE NEW DIGITAL SHELF

What the data tells us about AI results by funnel stage

We built a tool that queries LLMs at scale and analyses what appears in responses. Using Philips air fryers as a client case study, we ran intent-based queries across four funnel stages. Two things stood out.

The type of site cited changes as you move down the funnel

At awareness, media and blog content dominates (58% of cited sources) and retailers barely register at 1%. By the decision and purchase stages, brand sites and retailers become far more prominent. The implication: you need editorial coverage to win at the top of the funnel, and strong product pages to win at the bottom.

Long-form content dominates, but product pages matter at purchase

Long form content is cited 80% of the time at the awareness stage. By the purchase stage, product pages account for 50% of cited content, the highest point across the funnel. You need a content strategy that spans both.

The Philips impact: 4 months, position 4 → position 2

After identifying accessibility and authority gaps, we ran a programme of link building with media publications, forum and review seeding, and expanded long form content based on actual LLM queries. Over four months, LLM brand mentions grew from ~300 to over 1,400, moving Philips from 4th to 2nd in category share of voice.

PREPARING FOR AGENTIC COMMERCE

When AI agents don’t just recommend, they buy

Agentic Commerce is when AI completes the purchase on the shopper’s behalf. It’s already live in the US.

Google AI Mode shopping: launched January 2026 in the US, zero platform fees, wider merchant base

UK release for both is estimated across H1/H2 2026. It is coming this year.

“For bottom funnel purchase intent queries, retailers currently outrank brands in AI search. Agentic Commerce will amplify that, unless brands act now.”

When an AI agent is making a purchasing decision on behalf of a shopper, it will favour brands with machine readable data, strong third-party authority, and comprehensive product content. Those without it will be bypassed entirely.

Where to start

Audit technical accessibility: can LLMs read your product pages, pricing, and reviews?
Check authority signals: databases, editorial backlinks, genuine customer commentary
Map content against funnel intent: long-form guides for awareness, detailed product pages for decision
Track LLM share of voice: use Ahrefs, SEMrush, or BrightEdge to monitor brand mentions in AI responses
Prepare for Agentic Commerce: ensure product data and checkout infrastructure is compatible with AI shopping agents

If you want to understand your brand’s AI visibility, get in touch with the team, we run LLM share of voice audits for retailers and brands across all major AI search platforms and can show you where you currently stand and what it would take to move up.