Adobe Commerce Adds Tools To Make Product Catalogues Discoverable By AI Assistants

Adobe has introduced new capabilities in Adobe Commerce designed to help brands surface their products in AI-powered shopping experiences, as an increasing share of product discovery shifts from traditional search engines to conversational AI tools like ChatGPT, Microsoft Copilot, Claude and Gemini.

The new functionality centres on Adobe Catalog Agent, a native feature that enriches product detail pages with structured, machine-readable data intended for AI crawlers and large language model (LLM) discovery systems – without altering the shopping experience for human customers.

The move comes as traffic from AI sources to US retail sites grew 125 per cent between April and June 2026 compared to the same period the previous year, according to Adobe Digital Insights. That trend builds on a 693 per cent year-over-year increase in AI-driven traffic observed during the November to December 2025 holiday shopping season.

Structured data layer sits behind existing storefronts

The approach Adobe has taken does not require merchants to redesign their storefronts. Customers continue to see the same product detail pages, imagery and buying journey they are accustomed to.

Behind the scenes, however, Adobe Catalog Agent adds a layer of structured product information drawn from the Commerce catalogue. This includes product names, attributes, specifications, compatibility information, availability, pricing and product relationships – all formatted in a way that AI systems can parse and reason about.

The goal is to give AI-powered shopping assistants enough context to interpret customer queries and recommend products with greater accuracy. Rather than relying on keyword matching alone, AI applications can use the structured catalogue data to understand shopper intent and connect it to relevant products.

Consistency across channels from a single source

A core element of Adobe’s approach is enriching product data at the source – within the Commerce product catalogue itself – rather than optimising it separately for each channel.

Adobe Catalog Agent enhances product names, descriptions and use case phrases directly in the catalogue. Because the enrichment happens at the source, every downstream channel draws from the same product data, whether that channel is a storefront, an advertising pipeline, a marketplace listing or an AI-powered discovery experience.

The intent is to ensure brands maintain consistent product messaging across all surfaces where their catalogue appears, reducing the risk of AI assistants encountering incomplete or inconsistent information that might lead them to overlook relevant products.

Addressing a new layer of product discovery

For eCommerce businesses, the shift toward AI-driven product discovery introduces a layer of visibility that sits alongside established channels such as search engine optimisation, product feed optimisation, marketplace visibility and on-site merchandising.

Adobe positions the new capabilities as complementary to those existing efforts rather than a replacement. Traditional SEO and merchandising remain relevant, but the company argues that product visibility increasingly depends on whether AI systems can understand and reason about product data – not just whether products rank for the right keywords.

The structured data exposed through Catalog Agent is designed to support conversational shopping queries. Adobe uses examples such as “show me lightweight trail running shoes suitable for marathon training” or “find accessories compatible with this camera” to illustrate the type of intent-based discovery the feature is built to serve.

Native to Adobe Commerce with no add-on required

Adobe has built the product discovery capabilities natively into Adobe Commerce rather than offering them as a separate add-on or third-party integration. The feature is available across all Adobe Commerce deployment models.

For existing Adobe Commerce customers, this means they can adopt the AI-readiness features without introducing a separate platform, duplicating product data or redesigning their catalogue architecture.

Adobe frames this as reducing implementation complexity for technical teams, who would otherwise need to build custom integrations or manually expose catalogue information to AI applications. The agent works with existing Commerce services including catalogue information, product attributes, inventory, pricing and relationships, allowing AI applications to retrieve live data rather than relying on outdated or inferred information.

AI traffic growth signals a broader shift in eCommerce

The Adobe Digital Insights data underpinning the launch points to a rapid acceleration in the role AI assistants play in the eCommerce purchase journey.

The 125 per cent growth in AI-sourced traffic to US retail sites over the April to June 2026 quarter suggests the trend is extending well beyond early adopter behaviour. The 693 per cent spike during the 2025 holiday season indicated that AI-assisted shopping was already gaining traction at scale during peak retail periods.

For brands and merchants, the implication is that a growing share of potential customers may form product preferences or make purchase decisions through conversations with AI assistants before they ever visit a brand’s website or marketplace listing.

Adobe’s response with Catalog Agent is to position the product catalogue itself as a strategic asset – one that needs to be structured and enriched in a way that AI systems can consume, rather than simply formatted for human browsing or search engine indexing.

Foundation for future agentic commerce capabilities

Adobe has flagged the Catalog Agent as a foundational element of a broader agentic commerce strategy within Adobe Commerce.

The company has indicated that further catalogue intelligence, enrichment, governance and discovery capabilities are planned, aimed at expanding how products are surfaced, understood and recommended across AI-powered shopping experiences.

As LLM-powered commerce continues to develop, Adobe is positioning structured product knowledge – rather than keyword density – as the primary factor determining whether products appear in AI-driven recommendations.

The capabilities are available now for Adobe Commerce customers. Further details are available on the Adobe Commerce website.

Last Updated on July 28, 2026 by Nick Ross