Agentic Commerce Is Here. Your Buyers Are Already Using It Without Telling You.

The announcement most coverage missed

Google Marketing Live 2026 didn't get enough coverage for what it actually announced. Most of the writeups went to the AI Overview updates and the new ad placements. The thing worth paying attention to was agentic commerce — the infrastructure Google is building for AI agents to research, compare, and complete purchases on behalf of users without a human confirming each step.

For B2B digital sales leaders, this is not a future concern to monitor. The agent infrastructure is being built now. The question that matters is whether your company is visible to it — and most companies have no idea whether they are.

Why this is not just AI search with extra steps

It is easy to file agentic commerce under the same heading as AI search and move on. That would be a mistake, because the two work differently at the step that decides who wins.

AI search keeps a human in the loop. A buyer asks ChatGPT or Perplexity a question, reads the answer, and makes the final call. Your job is to appear in that answer so the human considers you. The human still chooses.

Agentic commerce removes the human from the selection step. The agent is given a goal — renew this software, source this service, replace this vendor — and it evaluates the options itself against criteria it can read. It narrows the field. It often acts. The buyer reviews the outcome, not the longlist.

That is the shift. The optimization target moves from appearing when humans search to being selectable when agents transact. Those are not the same problem, and the signals that solve them are not the same signals.

What an agent actually reads when it picks a vendor

A human evaluating your company browses your site, reads your case studies, gets a feel for your brand, and forms a judgment. An agent does almost none of that. It parses data.

What it looks for is machine-readable: structured data describing what you sell, verified and current pricing, clear capability descriptions it can match against the goal, and entity signals that let it confirm you are a real, established company that does what you claim. Schema markup. Consistent descriptions across sources. A verifiable footprint.

What it largely ignores is the layer most B2B marketing budgets are spent on. Brand storytelling, narrative case studies, the carefully written About page — none of that parses cleanly into the criteria an agent uses. A company can have a beautiful website and be almost invisible to an agent because nothing on that site is structured for a machine to read and act on.

This is the same underlying problem as the Perplexity Citation Gap — being technically present but semantically invisible — pushed one step further. In AI search you lose a citation. In agentic commerce you lose the transaction.

Which B2B categories are exposed first

Agentic commerce will not arrive everywhere at once. It arrives first where the decision can be expressed in data an agent can read.

Software subscriptions and SaaS renewals are the clearest early case. The criteria — features, pricing, integrations, compliance — are already structured. An agent tasked with renewing or replacing a tool can evaluate alternatives against those criteria without human input, and switching costs are often lower than buyers assume.

Recurring procurement is next. Standardised supplies, repeat orders, vendors selected on specification and price. These are decisions that were already semi-automated and are natural candidates for full agent handling.

Standardised professional services follow — the engagements where scope and deliverables can be specified clearly enough that an agent can compare providers. The more bespoke and relationship-driven the service, the later it is exposed. But the direction of travel is consistent: as more decision criteria become expressible in structured data, more of the selection moves to agents.

What digital sales leaders should do now

The work that makes a company visible to agents is not exotic. It is mostly GEO discipline applied with selection, rather than citation, as the goal.

Make your product and service descriptions machine-readable. Write them so the core facts — what it is, what it does, who it is for, what it costs — are stated plainly and can be extracted, not buried in narrative.

Implement schema markup on pricing and capabilities. Give agents structured, parseable data about what you offer rather than forcing them to infer it from marketing copy.

Establish clear entity signals. A Wikidata entry, consistent third-party descriptions, and structured data that lets an agent verify your company exists and does what it claims. An agent will not transact with a vendor it cannot confirm is real.

Treat your AI citation strategy as the foundation and extend it. The same signals that earn citation in AI answers are the signals an agent reads when selecting a vendor. Companies that have done the citation work are most of the way to being agent-visible. Companies that have not are starting from zero on both.

The window, again

This is the same story as every other shift in AI visibility, which is exactly why it is worth taking seriously. The infrastructure is early. Most B2B companies are not optimised for it. The ones that move while the field is empty establish positions that are harder to displace once everyone else catches up.

The difference with agentic commerce is the stakes. AI search visibility decides whether a human considers you. Agentic visibility decides whether an agent buys from you. One is the top of the funnel. The other is the transaction.

Your buyers are already starting to delegate these decisions. They are not going to tell you when an agent quietly drops you from a renewal or picks a competitor for a recurring order. You will just see the number move, with no obvious cause, the same way the GEO shift has been moving numbers no dashboard explains.

If you want to know whether your company is visible to AI agents and AI search today, the free GEO Audit at getaicited.co runs a baseline across the platforms that increasingly decide what your buyers see — and choose. That baseline is the place to start.