AI Platforms Are Now Omnichannel: What CPG Brands Must Know

Product Catalog Quality Is Now a Revenue Channel

AI platforms like ChatGPT and Google Gemini are actively surfacing products to consumers, and brands with thin, poorly structured catalogs are invisible in those results. Academy Sports and Outdoors, a top-150 North American online retailer, has formally classified AI platforms alongside its website, mobile app, and physical stores as distinct omnichannel touchpoints. That decision has direct consequences for any CPG brand selling on Amazon or TikTok Shop right now.

The brands that get this right will capture discovery from an entirely new surface. The brands that ignore it will watch their organic visibility erode as generative AI intermediates more of the purchase funnel.

What 'AI-Ready' Product Data Actually Means

Academy Sports CIO Sumit Anand described a layered approach to catalog enrichment: start with a base set of attributes, run scraping services to add more, then deploy AI tools to identify additional attributes that increase findability across web surfaces. Human merchandisers then review that expanded list for relevance before it goes live.

That process is not simple, and it does not happen once. Anand explicitly said Academy Sports works through its catalog in waves by department, because doing it all at once becomes unmanageable across a large SKU count. For CPG brands with dozens or hundreds of active ASINs, this is the same challenge at a smaller scale but with the same structural requirement: someone needs to own catalog quality as an ongoing operational function, not a one-time setup task.

The implication for brands working with an Amazon management partner is direct. Your agency should already be treating listing content as a living asset, not a static deliverable. If your product detail pages were optimized once at launch and have not been touched since, you are already behind on both traditional search and emerging AI discovery surfaces.

Why This Matters Specifically on Amazon and TikTok Shop

Amazon has been integrating AI-generated responses into its search experience through Rufus, its conversational shopping assistant. TikTok Shop surfaces products through algorithmic recommendation and influencer content, where product descriptions and attributes feed directly into what gets matched to which audience. Both platforms reward catalog depth and attribute completeness in ways that compound over time.

A brand doing $75,000 to $500,000 per month on Amazon cannot afford to treat its backend catalog as an afterthought. The gap between a listing with 12 attributes and one with 30 well-structured attributes is not marginal. It is the difference between showing up in an AI-generated gift guide or product comparison and being absent from it entirely.

According to Digital Commerce 360, Academy Sports is also piloting Google's Universal Commerce Protocol and a Conversational Attributes Pilot, both designed to make product catalogs readable and actionable by agentic AI systems. These are early signals of where marketplace infrastructure is heading across the board.

What to Look for in a Partner Who Understands This

Most Amazon agencies optimized for 2021. They built listings for A9, loaded in keywords, and moved on. That approach is losing ground to operators who understand that catalog architecture now serves multiple simultaneous audiences: human shoppers, traditional keyword search, and AI retrieval systems that weight structured data differently than keyword density.

When evaluating a partner, ask specifically how they handle listing refreshes. A serious operator has a defined process for auditing attributes, updating backend search terms, and revising copy based on what AI surfaces are rewarding. They should be able to show you how their catalog work connects to organic rank improvements and, increasingly, to visibility in AI-generated results.

Ask about their approach to product feed management across channels. If you are selling on both Amazon and TikTok Shop, your catalog data needs to be structured consistently so it performs across both surfaces. A partner managing both channels simultaneously has a structural advantage here because they can identify attribute gaps that affect performance on one platform before those gaps surface as revenue problems.

The Alignment Problem Most Brands Have With Their Agency

The deeper issue behind catalog neglect is incentive misalignment. An agency paid on a flat retainer has little reason to invest ongoing effort into catalog enrichment. It is time-consuming work with results that compound slowly. An agency with skin in the game through revenue share or a hybrid model is structurally motivated to keep catalog quality high because their own returns depend on it.

Academy Sports is investing in AI-readiness because it sees the channel as a material driver of future revenue. Its ecommerce operations are built on the premise that wherever consumers discover and buy products, the retailer needs clean, complete, and structured data feeding that experience. CPG brands at the $75K to $500K monthly revenue range need to operate with the same discipline, even if the scale is smaller. The structural requirement is identical.

The brands scaling past $1M per month on Amazon are not doing it on ad spend alone. They are doing it because their catalog works harder than their competitors' catalogs across every surface where products get discovered and evaluated.