This morning, I asked OpenClaw to buy me a pair of running shoes. I didn’t open a browser or walk into a store. I didn’t search for brands. I didn’t compare prices on half a dozen websites. I simply texted my AI agent to send me new running shoes, and it did all the work autonomously, from discovery to execution. I didn’t even have to tell it my shoe size.
That, in a nutshell, is agentic commerce and while McKinsey projects it will drive up to $1 trillion in US retail revenue by 2030, it’s already transforming the e-commerce battleground, today. As Target’s traffic from ChatGPT is growing 40% month-over-month, I’m already seeing some customers attribute 10% of their revenue to agentic channels — from first prompt to final transaction.
That’s the full customer journey brands must now own — end to end.
The Death of the Front Door
For decades, the shopping journey had a front door. Platform visibility, ad spend, search ranking: all of it depended on a shopper arriving somewhere before they could buy anything. Whoever owned that destination owned commerce.
That era is ending.
Today, when I ask ChatGPT, Gemini, Claude, or Perplexity for a running shoe recommendation, I am effectively delegating the entire discovery process to an AI agent powered by large language models (LLMs). My AI agent decides which products to surface — and which products never get seen at all. There’s no sponsored listing, no search rank, no destination.
With the execution layer rapidly catching up through agent-capable browsers and protocols like OpenAI’s UCP and Gemini’s ACP, the result is seamless, end-to-end agentic commerce. The brands visible to AI agents can also win AI search without being the top page result on Google.
Your Real Customer Is Now a Bot
Successful CMOs are recognizing a fundamental shift: AI agents are no longer just tools their customers use. They are the customers.
Just as UX defined the era of B2C digital commerce, Agent Experience (AX) is defining this fast-emerging Business to Agent (B2A) age. If you’re a brand, that means your real audience increasingly includes the automated crawlers you may still be actively trying to block from your website. But these agents don’t browse the way humans do.
One study revealed only 12% of URLs cited by AI tools overlap with Google’s top 10 results, while another found that 90% of the sources ChatGPT cited were not even on Google’s first 20 pages. Traditional SEO, on its own, is no longer enough.
And the optimization discipline to match it —Agentic Web Optimization — is already separating winners from the rest.
What Winning in the Agentic Web Actually Looks Like
I’ve seen brands lose positions overnight — not because their product changed, but because their content wasn’t structured in a way agents could parse reliably. I’ve also seen clients invisible in the AI-first world climb to the #1 spot by embracing AX and Answer Engine Optimization (AEO).
One robotics customer achieved a 94% increase in agentic visibility in four months by restructuring its content for AEO.
The original content was engaging for human readers — but an analysis revealed it lacked the structured formatting that LLMs rely on to extract and cite information: a clear FAQs section and real-world use cases, precise answers to the exact questions users were actually asking AI tools.
By deepening content relevance and restructuring for machine comprehension — while competitors remained vague, promotional, and poorly formatted — this brand became the reference point in its category. LLMs started quoting it. Agents started recommending it.
The playbook for brands that want to compete looks like this:
- Audit how agents see you. Tools now exist to simulate how LLMs crawl and interpret your site. Most brands are shocked by the gaps.
- Structure content to make it visible to agents, not just SEO. That means FAQs, specific use cases, precise answers to real user queries — not keyword-stuffed landing pages.
- Own your external citations. AI models weight sources like Reddit and Wikipedia heavily. Understand how you’re being referenced there, and actively shape that narrative.
- Build machine-readable product data. APIs, structured schemas, and clean product feeds are the new storefront.
The New Commerce Battleground
This is not a thought experiment. Big players like Target, Walmart, and Etsy are investing in APIs, schemas, and content products tuned for how AI agents consume and act on information, and as a result, seeing their referral traffic from ChatGPT reach up to 35%.
Consumer behavior is already moving to meet them. A recent Adobe study found that while nearly half of U.S. consumers use TikTok as a search engine, 14% are already relying on ChatGPT over Google. The leap from “search and click” to “ask an agent and approve” is not a large leap — and it’s happening faster than most brands realize.
In the next 12 months, I expect to see major advances in B2A, where companies need to market, sell, and communicate — not just to human buyers, but to AI agents acting on their behalf. More consumers are delegating purchases to agents, fewer are manually browsing websites, and the first real agent-to-agent networks will appear, where agents learn from each other’s successful transactions to make better recommendations.
The brands winning this new e-commerce battlefield aren’t waiting for a standard s to emerge. They’re auditing how agents see them today, investing in AX over UX, and structuring their content for machines — not just people.
The next decade of commerce won’t be won by the brands with the best websites or the highest Google rankings. It will be won by the brands that machines understand, trust, and recommend.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
