McKinsey projects that agentic commerce will orchestrate $5 trillion in global transaction volume by 2030, with $1 trillion of that in US B2C alone. ChatGPT now has 700 million weekly users, and half of all consumers already use AI when searching the internet.

The opportunity is real. The question is which merchants will capture it.

The answer depends on infrastructure. Not marketing strategy. Not brand awareness. The data systems that determine whether AI agents can see your products, understand customer intent, and complete transactions without friction.

Early movers like Walmart, Instacart, Etsy, and Shopify merchants are already processing agent-mediated transactions. They didn't wait for the market to mature. They built the infrastructure that makes agent commerce possible.

How big is the agentic commerce market opportunity

Multiple research firms have sized the agentic commerce opportunity, and the projections are converging around a consistent range.

‍McKinsey projects $5 trillion in global transaction volume by 2030, with $1 trillion in US B2C alone. Morgan Stanley estimates $190-385 billion in US e-commerce spending by 2030, representing 10-20% of online retail. Bain forecasts $300-500 billion by 2030, making up 15-25% of overall e-commerce.

The projections include:

• Direct agent-completed purchases (a customer tells ChatGPT to buy something)
• Agent-influenced purchases (a customer researches via AI, then buys elsewhere)
• B2B procurement automation (agents handling routine business purchases)

The current activity validates the trajectory. The McKinsey analysis estimates that ChatGPT processes approximately 50 million shopping-related queries daily, translating to significant transaction potential as conversion infrastructure matures.

What makes these projections credible is the conversion data. Research shows that AI-generated product recommendations achieve 4.4x higher conversion rates compared to traditional search. Adobe found that shoppers who land on retail sites from AI chatbots are 38% more likely to make a purchase. Retailers using AI/ML saw 14.2% sales growth between 2023-2024, compared to just 6.9% for retailers not using AI.

This conversion advantage explains why the opportunity is so large. Agents do not just change how customers discover products. They change the economics of conversion.

The behavioral shift is already visible. Kantar research forecasts that by 2028, one in five digital storefront interactions will be handled by machine customers: autonomous agents making purchase decisions on behalf of humans.

Consumer adoption is accelerating across demographics. Salesforce reports that 39% of consumers, and over half of Gen Z, already use AI for product discovery. Morgan Stanley estimates that 23% of Americans bought something via AI in the past month.

The traffic patterns confirm the shift. Adobe reported that AI traffic to US retail sites increased 805% year-over-year on Black Friday, with Cyber Monday seeing 670% growth. ChatGPT now drives more than 20% of referral traffic to Walmart, nearly 15% to Target, and 10% to eBay. The transition from "I'll search for it" to "handle this for me" represents the largest change in shopping behavior since mobile commerce.

For retailers, this creates urgency. The merchants who build agent-compatible infrastructure now will be indexed and recommended as agent usage scales. Those who wait will find themselves invisible to the fastest-growing discovery channel. Unlike SEO, there is no gradual optimization path. Agents either see your products or they don't.

Why AI shopping agents create attribution and measurement gaps

There's a structural challenge embedded in how agentic commerce currently works, and it determines which merchants can capitalize on this opportunity.

When a customer uses ChatGPT to shop, the conversation happens inside ChatGPT's interface. The discovery phase, comparison shopping, and shortlisting all occur before the merchant ever sees the customer. By the time the merchant receives a checkout request, most of the decision-making is already complete.

This creates a measurement gap. The Agentic Commerce Protocol (ACP) developed by OpenAI and Stripe secures the transaction. It handles payment tokenization, inventory verification, and order execution. But ACP doesn't capture intent signals from earlier in the journey.

For merchants accustomed to tracking the full customer journey through their own properties, this is a fundamental shift. You can't pixel a conversation inside ChatGPT. You can't see which products the agent considered and rejected. You can't attribute the sale to upstream marketing that may have influenced the customer's request to the agent.

The merchants who treat this as a problem will fall behind. Those who build infrastructure to capture and monetize intent signals at the checkout moment will win.

This has direct implications for retail media. If you can't see which products the agent considered, you can't prove which ads influenced the recommendation. Retail media networks that can't attribute agent-influenced purchases will lose advertiser confidence. The measurement infrastructure you build today determines whether your RMN remains viable as agent commerce scales.

Which retailers are already winning with AI shopping agents

The early adopters are not experimenting. They are operationalizing. What distinguishes their implementations is not the agent interface but the data infrastructure underneath.

The pattern: each treated agentic commerce as an infrastructure investment, not a marketing channel.

What the agentic commerce protocol does and doesn't solve

Understanding the protocol's scope clarifies what infrastructure you need to build.

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What ACP handles:

‍What ACP doesn't handle:

ACP is a transaction protocol, not a data infrastructure. It solves the "how do agents buy things safely" problem. It doesn't solve the "how do merchants understand and monetize agent-influenced commerce" problem.

The merchants who win will build the layer that sits between ACP and their commerce stack: capturing intent, resolving identity, and routing signals to personalization, attribution, and retail media systems.

What retailers need to capture agentic commerce value

The connectivity layer is commoditizing. Shopify handles ACP integration automatically. PayPal is enabling automatic ACP support for merchants in its network. Payment integration, API connectivity, and catalog exposure are table stakes.

The differentiator is data infrastructure. Retailers who invest in these four capabilities will capture disproportionate value:

‍Identity resolution across surfaces. Connect agent-mediated transactions to customer profiles from web, app, and store interactions. This enables personalization, attribution, and loyalty across every surface.

‍Real-time data sync. Agent transactions happen fast. Inventory, pricing, and product data updated in real-time ensures successful transactions and builds reliability scores with agents.

‍Intent capture at the first mile. The checkout request is your first opportunity to capture intent signals. Infrastructure that processes and routes these signals in real-time powers downstream personalization and attribution.

‍Cross-surface normalization. Agent transactions flowing into the same customer profiles, attribution models, and analytics systems as web and app transactions creates unified measurement and optimization.

The competitive landscape is moving fast. Salesforce reports that 84% of retailers are using AI in some form, with 43% piloting agentic AI specifically. NVIDIA found that 97% of retailers plan to increase AI spending in the next fiscal year. The merchants not investing in this infrastructure are falling behind competitors who are.

The infrastructure gap also explains why current agent commerce performance lags expectations. Research from Kaiser and Schulze found that ChatGPT referrals account for less than 0.2% of e-commerce sessions, and when traffic does arrive, it converts 86% worse than affiliate links. The problem isn't consumer demand. Most merchant infrastructure can't support the data quality, real-time sync, and identity resolution that agent commerce requires.

The merchants who close this infrastructure gap will see disproportionate gains as agent usage scales. Those who don't will watch competitors capture traffic they never see.

How retailers can capture the AI commerce opportunity

The $5 trillion projection will be captured by merchants who treat this as an infrastructure problem, not a marketing problem. The pattern from early adopters like Walmart, Instacart, and Shopify is clear: they built cross-surface data infrastructure that includes agents as one surface among many.

The timing matters. OpenAI's ACP launched in 2025. Shopify's Agentic Storefronts went live the same year. PayPal's automatic ACP support arrives in 2026. The protocol layer is stabilizing, which means infrastructure investments made now will compound as the ecosystem matures.

Merchants who wait for "proven ROI" before investing will find themselves locked out. Agent visibility depends on being indexed, and indexing depends on data quality that takes time to build. The 2025-2026 window is when early movers establish the infrastructure advantages that late entrants cannot replicate.

The opportunity is $5 trillion. The question is whether your infrastructure can capture it.

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MetaRouter sits at the ACP ingress point: the first moment customer intent crosses into merchant control. Enterprise retailers use MetaRouter's first-mile infrastructure to capture, normalize, and route intent data across all commerce surfaces. See how it works.

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