Rise of Agentic Commerce: Why Product Data Is the New Competitive Frontier

Mark founded Netalico after seeing too many merchants struggling with expensive internal tech teams that couldn’t deliver. He earned his MBA from The Wharton School of the University of Pennsylvania and has over 20 years of development experience at NASA, HP, and top agencies. He built Netalico to be the tech partner you wished you had internally without the overhead, training costs, or management headaches. In this article, Mark shares his insights on how data is influencing the world of agentic commerce right now.

This is a gold rush. And like every gold rush in history, the merchants who move first will stake the best claims while everyone else fights over what’s left.

Agentic commerce isn’t a theoretical future state. It’s happening right now. AI assistants are recommending products, comparing options, and increasingly completing purchases on behalf of consumers. The interfaces vary: ChatGPT, Perplexity, Google’s AI Overviews, Bing Copilot, and whatever launches next month. But the underlying shift is the same: discovery and purchasing are moving from human-driven browsing to AI-mediated recommendations.

The data tells the story. According to Adobe Analytics, traffic to U.S. retail sites from generative AI sources increased 760% year over year from November 1 to December 1, 2025. On Cyber Monday alone, AI traffic was up 670% YoY.

But here’s what makes this different from typical channel growth: this traffic converts better. Adobe found that shoppers arriving from AI sources were 54% more likely to purchase than those from other referral sources. People trust an LLM recommendation the way they used to trust a friend’s suggestion.

The shift isn’t coming. It’s here. And the infrastructure to capitalize on it is falling into place right now.

The commerce layer is being built in real time

Multiple players are racing to become the transaction layer for AI-driven discovery.

Perplexity launched “Buy with Pro” in November 2024, letting users research and purchase products without leaving the platform. OpenAI followed with “Instant Checkout” in September 2025, enabling purchases directly inside ChatGPT. Google continues expanding AI Overviews with shopping intent. Amazon has Rufus. Microsoft has Copilot with commerce capabilities.

The competitive landscape is still forming, but the pattern is clear: every major AI platform is building native commerce functionality. They’re not just sending traffic to retailers anymore. They’re becoming the point of sale.

Here’s the infrastructure detail that matters most: OpenAI and Stripe co-developed the Agentic Commerce Protocol (ACP) and open-sourced it. This isn’t proprietary technology locked to one platform. It’s an open standard designed to work across AI systems, payment processors, and business types.

Shopify merchants are among the first to integrate. But BigCommerce can use it. Home Depot already announced adoption. Any retailer with Stripe integration has a path to this capability. The protocol is platform-agnostic by design.

This means agentic commerce infrastructure is coming to everyone. The question isn’t whether your platform will have access. The question is whether you’ll be ready when it does.

Why this is a gold rush

In gold rushes, timing is everything. The first prospectors to reach California in 1848 found gold lying in streambeds. By 1850, you needed heavy equipment and significant capital to extract anything. The easy claims were gone.

The same dynamic is playing out in agentic commerce.

Right now, AI assistants are indexing product catalogs and surfacing recommendations. The merchants who get their products optimized for AI discovery now will have compounding advantages as this channel scales.

The early movers are already outperforming. Shopify merchants generated $14.6 billion in sales over Black Friday and Cyber Monday 2025, up 27% year over year. Meanwhile, overall U.S. ecommerce grew 7.7% during Cyber Week, according to Adobe. That’s nearly a 4x difference in growth rate. Part of that gap comes from first-mover positioning on emerging AI channels and tighter platform integrations with AI discovery tools.

The merchants who establish presence now, who get their data structured and their products discoverable across AI platforms, are staking claims in territory that will only get more crowded and more competitive.

Wait too long, and you’re the prospector showing up in 1850 with a gold pan while everyone else has industrial equipment.

What AI platforms are hiring tells you everything

Watch where the talent is moving. OpenAI just hired Glen Coates, who spent nearly seven years leading product development at Shopify, to head their app platform. Perplexity has been aggressively building merchant partnerships. Google keeps expanding its commerce-focused AI capabilities.

These platforms aren’t treating e-commerce as an afterthought. They’re staffing up with people who understand retail at scale. The investment signals where this is heading.

What actually matters: your data is your new storefront

Here’s where the “product data is the new competitive frontier” thesis holds up, and it’s platform-agnostic.

When humans shop, they respond to visuals, storytelling, brand identity, and emotional appeals. When AI agents process your catalog, they see structured data. Attributes, specifications, category context, pricing, availability. That’s it.

The agent isn’t evaluating your hero image. It’s parsing your data fields and comparing them against millions of alternatives in milliseconds. This is true whether the agent lives in ChatGPT, Perplexity, Google, or whatever platform emerges next.

This changes the game in ways most merchants haven’t internalized:

First, AEO is the new SEO. Answer Engine Optimization is becoming a real discipline, and it works differently than traditional search optimization.

SEO has always been about links. Google ranks you based on who’s linking to you and their domain authority. You could use “nofollow” tags to link without passing SEO value.

LLMs don’t care about any of that. They don’t need links. They need mentions. A brand mentioned in the Wall Street Journal that doesn’t include a hyperlink is worthless for SEO but incredibly valuable for AEO. The LLMs treat publications as sources of truth regardless of link structure.

Content format matters too. Q&A structured content performs better because that’s how people query AI assistants. “What’s the best ski gloves for cold weather?” is how people ask these tools. Content structured to answer that directly gets pulled as source material.

And here’s a technical detail most people miss: many AI platforms, including ChatGPT, use Bing’s index for their search queries. If you’ve been ignoring Bing because Google dominates, you now have a reason to care. Your Bing ranking affects your visibility across multiple AI platforms. If your site isn’t indexed by Bing, you may not appear in AI recommendations at all.

Second, complete product data means visible products. When an AI agent is comparing options, structured attributes aren’t optional. Delivery timelines, sizing specs, materials, warranty info: the merchants who have this data complete and consistent are the ones who show up in recommendations. Across every platform.

Third, the bar for “good enough” data just got higher. It used to be that decent product descriptions and some keywords got you by. Now you need structured attributes, semantic context, complete specifications, and consistency across your entire catalog. The agents processing your data are efficient at surfacing the best options, which is great news if you’re one of them.

The cost of falling behind

The merchants who aren’t optimizing are watching their organic traffic erode. Google’s own AI Overviews are changing user behavior. People are being trained to trust written explanations and recommendations. The top of search results now often feature an AI-generated summary that directly answers the query.

This pattern is accelerating across platforms. Perplexity users get direct answers with product recommendations. ChatGPT users get conversational shopping assistance. The common thread: AI is mediating more discovery, and the merchants who aren’t visible in AI results are losing ground.

Adobe’s data shows this isn’t cannibalization in the traditional sense. It’s channel evolution. The traffic you’re getting from AI channels is higher quality than what you were getting from generic organic search. But you only capture that upside if you’re visible in the AI results.

The growth trajectory is steep. Adobe reported AI traffic to retail sites increased 1,300% during the 2024 holiday season compared to the prior year. By July 2025, that figure had reached 4,700% YoY growth. The channel is doubling every two to three months. The merchants who optimize for this reality are capturing a growing share of high-intent traffic. The ones who don’t? They’re losing ground every month, and the gap compounds.

Where fabric fits

I’ve looked at a lot of solutions in this space. Most of them are either too theoretical (pretty dashboards, no practical output) or too manual (consultants charging by the hour to do what should be automated).

fabric’s Product Agent actually solves the core problem. It takes your existing catalog, benchmarks it against category leaders to show you where opportunities exist, then automates the enrichment with structured attributes and semantic signals that AI agents can actually process.

The output is practical: agent-ready product data that flows to your demand channels. Not a report telling you what to fix. Actual enriched data you can deploy. And it works regardless of what e-commerce platform you’re on or which AI assistants your customers use.

Three things I like about their approach:

1. Benchmarking that shows you the gap 

They compare your catalog against what’s winning in your category and surface specific opportunities. Not abstract “data quality scores.” Concrete improvements in depth and context that translate to visibility.

2. Automated enrichment that scales 

Manually enriching thousands of SKUs with structured attributes is a nightmare. Their AI handles the heavy lifting and creates data profiles that agents can reliably act on.

3. Channel activation built in

The enriched data doesn’t just sit in a database. It pushes to AI search, recommendation engines, and discovery platforms. Visibility is the whole point.

If you’re running a catalog of any meaningful size and you’re watching AI referral traffic become a real channel, this is the kind of infrastructure investment that positions you to capture the upside regardless of which AI platforms win.

The window is now

Here’s the bottom line: agentic commerce is early enough that the merchants who invest now will have structural advantages as it scales.

The Agentic Commerce Protocol is open-sourced and spreading. Multiple AI platforms are building native purchase flows. The talent moving into this space signals serious long-term investment.

The data is unambiguous: AI traffic to retail sites is up 760% YoY. Conversion rates from AI sources are 54% higher than traditional channels. The channel is doubling every few months. Merchants positioned for AI discovery are growing at nearly 4x the rate of the broader market.

This is a gold rush. The merchants who stake their claims now, who get their product data structured for AI discovery, who show up in recommendations while competitors are still figuring out what’s happening: those are the merchants who will capture a disproportionate share of this emerging channel.

The agents are already driving higher-intent traffic across multiple platforms. Native commerce functionality is rolling out everywhere. The infrastructure is built on open standards designed to spread across the industry.

The question isn’t whether agentic commerce matters. The question is whether you’ll have staked your claim before the easy ground is taken.

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