Agentic Commerce: What It Means for Advertisers and How to Prepare

AI Shopping Agents Are Already Processing Billions in Transactions

During Cyber Week 2025, 20% of global e-commerce orders were influenced by AI agents, according to Salesforce. AI chatbot traffic to U.S. retail sites grew 670% year-over-year during that same holiday season, as Adobe reported. And in January 2026, Google CEO Sundar Pichai announced the Universal Commerce Protocol (UCP) at the National Retail Federation conference — a clear signal that the infrastructure for AI-completed purchases is no longer theoretical.

McKinsey projects the global agentic commerce opportunity at $3 trillion to $5 trillion by 2030, with up to $1 trillion in U.S. B2C retail alone. AI platforms are expected to account for 1.5% of total U.S. retail e-commerce sales in 2026 — roughly $20.57 billion — nearly quadruple the 2025 figures, per EMARKETER.

These are not projections from AI enthusiasts. These are numbers from McKinsey, Morgan Stanley, and Forrester. The shift is measurable, and it has direct consequences for how brands advertise.

What Is Agentic Commerce?

Agentic commerce is an online shopping model where AI agents make purchasing decisions across the entire buying journey — from product discovery through checkout and post-purchase support — on behalf of the consumer.

The consumer sets intent and constraints. The AI agent handles research, comparison, selection, and in some cases, the transaction itself. 

This is different from conversational commerce, where a chatbot recommends a product and the consumer still completes the purchase manually. In agentic commerce, the agent queries product catalogs, evaluates pricing and availability in real time, checks shipping and return policies, and can execute the checkout.

Think of it this way: a chatbot that suggests a moisturizer based on your skin type is conversational commerce. An AI that queries multiple skincare brands, compares ingredients and prices, and selects the best option within your budget — that is agentic commerce.

Why Agentic Commerce Changes Everything for Advertising

For over two decades, digital advertising operated on a predictable model. Brands competed for attention on search results pages, product listing pages, and social feeds. The consumer clicked, browsed, compared, and purchased. Advertisers measured clicks, impressions, and conversions.

Agentic commerce removes the session layer. The consumer no longer opens ten tabs. They no longer scroll through product listing ads. They describe what they need, and the agent handles the rest.

This creates a structural problem for advertisers. If the AI agent does not surface your product, your brand is not part of that transaction. The consumer never sees your ad, your listing, or your landing page. The entire traditional advertising funnel — awareness, consideration, conversion — gets compressed into a single AI-mediated decision.

U.S. advertisers will spend $71.98 billion on retail media in 2026, up 18.7% from 2025, according to an EMARKETER March 2026 forecast. AI shopping agents that bypass traditional search and browse behavior directly reduce the value of sponsored product placements, display ads, and keyword advertising.

The metric that matters is shifting. Click-through rate measures human interaction with a page. In agentic commerce, the more relevant metric is the AI citation rate — whether a shopping agent retrieves, references, or recommends your product during fulfillment.

How Agentic Commerce Works: The Three-Layer Architecture

When a consumer types a request like "Find me running shoes under $120, size 10, that ship before Thursday," the AI agent activates three distinct layers:

Intent Layer. The AI model parses the request, extracting constraints: budget, size, delivery window, brand preference, and return policy requirements. This is where natural language understanding meets structured product queries.

Commerce Layer. The agent queries product catalogs, pricing services, inventory feeds, and shipping estimators through structured APIs. It evaluates options against the consumer's constraints and ranks results by relevance, trust signals, and fulfillment reliability.

Transaction Layer. For approved purchases, the agent communicates with the merchant's checkout systems using protocols like the Universal Commerce Protocol (UCP) or the Agentic Commerce Protocol (ACP). Payment is processed through pre-authorized methods, and the agent handles order confirmation, tracking, and returns.

The critical insight: this architecture does not rely on websites, product pages, or traditional ad placements. It relies on structured data, API accessibility, and machine-readable product attributes.

The Key Players Building the Agentic Commerce Ecosystem

Google, OpenAI, and Microsoft are building open or semi-open ecosystems. Amazon is taking a more controlled, proprietary approach. For advertisers, this fragmentation means maintaining product data for multiple agent ecosystems simultaneously.

What Brands and Advertisers Must Do: 5 Actionable Strategies

1. Treat Product Data as Advertising Infrastructure

In an agentic commerce environment, your product catalog becomes your most important advertising asset. AI agents do not read display ads. They read structured data feeds.

If your product data is incomplete, inconsistent, or lacks machine-readable attributes, the AI agent skips your product without a human ever seeing it. The difference between a "correct" catalog and an "optimized" catalog is no longer a marginal performance lift. It determines whether you are in or out of the conversation.

Priority actions: enrich product descriptions with real use-case language, add structured attributes for compatibility, accessories, substitutes, FAQs, and keep pricing and inventory synchronized in real time.

2. Invest in AI Engine Optimization (AEO) Alongside SEO

SEO was built for keyword-based search. AI agents operate differently. They interpret intent, evaluate tradeoffs, and surface products based on structured relevance, not keyword density.

Answer engine optimization and generative engine optimization are becoming operational requirements. This means structuring content so that AI systems can accurately represent your products when consumers ask questions across ChatGPT, Gemini, Perplexity, and Copilot.

Bain & Company estimates that 30% to 45% of U.S. consumers already use generative AI to research and compare products. If your brand does not appear in these AI-driven discovery moments, you lose consideration before the consumer even reaches a traditional advertising surface.

3. Build Structured Fulfillment Signals for Agent Legibility

AI shopping agents struggle with ambiguity. They need delivery windows, shipping costs, and return terms that are structured, comparable, and consistent. If this information is unclear across channels, the agent defaults to a competitor whose offer is easier to execute.

This is a form of competitive advantage that has nothing to do with creative or messaging. It is purely operational. Make your delivery promises, return policies, and availability data machine-readable and consistent across every channel.

4. Run Contextual and Cookieless Advertising to Reach Consumers Before Agent Delegation

Here is the part most advertisers are not discussing yet: agentic commerce compresses the funnel, but it does not eliminate the need for brand awareness and preference. Consumers still need to form opinions before they instruct their AI agents.

A consumer who tells their agent, "find me waterproof running shoes under $150 with next-day delivery," has already been influenced by something — a contextual video ad they saw during a trail running review, a brand mention in a comparison article, or a recommendation from a creator they follow.

This is where contextual targeting and cookieless advertising become critical. Brands that reach consumers in the right context — while they are still forming preferences — can shape the instructions consumers give to their AI agents.

Adello's cookieless advertising stack and its mobile DSP further support this approach, delivering programmatic advertising across mobile, DOOH, and video channels without reliance on deprecating identifiers.

The outcome: brands that invest in contextual, privacy-compliant advertising build the upstream awareness that shapes downstream agentic purchases.

5. Prepare for Agent-to-Agent Negotiation in B2B

Forrester predicts that by the end of 2026, 1 in 5 B2B sellers will face AI-powered buyer agents delivering dynamically generated counteroffers. This means advertising and pricing strategies need to account for machine-to-machine interactions, not just human decision-makers.

B2B advertisers should begin structuring their pricing, terms, and product data for agent consumption now — before competitors establish presence in these emerging channels.

Why Acting Now Matters: The Window Is Narrow

Retailers that deployed AI capabilities between 2023 and 2024 saw 14.2% sales growth, compared to 6.9% for those without AI capabilities, according to Capital One Shopping research. The performance gap is accelerating, and it applies to advertising strategy as well.

Shoppers directed to retail sites from AI platforms are 30 times more likely to make a purchase, per Adobe data cited by EMARKETER. That is an extraordinary conversion signal — but only for brands whose products the AI agent can find, evaluate, and recommend.

The practical window for establishing presence in agentic commerce ecosystems is 2026. The protocols are being standardized now. The consumer behaviors are forming now. The brands that structure their data, advertising, and fulfillment for AI agent accessibility in this window will have a measurable advantage over those that wait.

The Advertising Playbook Is Being Rewritten

Agentic commerce does not replace traditional advertising overnight. Consumer trust is still developing — only 46% of shoppers fully trust AI recommendations, and 89% still verify information before purchasing, according to the IAB. High-value and identity-sensitive purchases will remain human-directed for now.

But the direction is clear. The consumer journey is moving from pages to conversations. From clicks to delegated decisions. From keyword-based discovery to structured-data-driven recommendations.

Advertisers who prepare for this shift now — by investing in AI agents for advertising readiness, contextual targeting, cookieless advertising solutions, and structured product data — will be positioned to capture demand in a channel that is growing at multiples of traditional e-commerce.

The brands that will succeed in agentic commerce are the ones that are already visible, already trusted, and already structured for the machines that will increasingly do the shopping.