People already ask AI systems for product picks, vendor shortlists, and local services before they ever hit your site. GEO—generative engine optimization—and the broader work of influencing AI positioning are about influencing how models categorize, compare, trust, and recommend your business.
That matters for revenue today, but it also matters for what comes next. The industry is moving toward agentic commerce: assistants that do not only recommend—they can help complete purchases, bookings, and signups with clear user consent and guardrails. When that becomes normal, the same layer that decides whether you show up in a good light in ChatGPT or Gemini is tightly linked to whether you are the business an agent routes a transaction to.
In other words, GEO is the on-ramp. Longer term, it converges with optimizing for agent purchases: being selected and being easy to complete against. The companies that fix representation and measurement now will not be starting from zero when checkout and tooling catch up.
From answers to actions
Today the fight is mostly about what models say and cite. Tomorrow it includes what they can do on the user's behalf—call a merchant, hold inventory, run checkout—against shared plumbing the whole ecosystem is building. The important part for most brands is not memorizing every protocol; it is understanding that who gets chosen still sits upstream of who gets the sale. Open standards and big-platform rollouts are making the “complete the purchase” step more interoperable. They do not, by themselves, fix a wrong category, a bad peer set, or weak trust signals in the model's view of your business.
Agents collapse discovery into routing, then completion—so how AI understands you moves closer to revenue.
Typical shopper today
Agent-shaped path
Why positioning is not a side project
If an AI system miscategorizes you, compares you to the wrong competitors, or repeats outdated claims, that is already a go-to-market problem. As purchase flows move into assistants, those errors become expensive faster: you may never reach the step where a cart or booking API matters.
Strong GEO work—clear positioning, structured reference content, continuous checks on what major models actually output—reduces that risk. It is the same muscle you will need when the question stops being “did we get mentioned?” and becomes “did we get routed for the money intent—and could an agent finish the job?”
Shared rails help with checkout; your AI positioning helps with who makes the shortlist.
GEO & positioning
How AI understands you
Category, peers, trust, citations—what models believe before any button click
Agentic commerce
Completion layer
Checkout, booking, tools—getting easier to standardize across platforms
Where the industry is heading
Major model providers are treating tool use and agent loops as core product. Retail and platforms are experimenting with conversational checkout and open commerce protocols so agents can discover what a merchant supports and complete a purchase without one-off integrations everywhere. The details will keep changing; the direction is clear: more completion inside the assistant, less dependency on the user retyping your brand into ten tabs.
For leadership teams, the takeaway is strategic. Execution plumbing will commoditize. Differentiation and margin will lean harder on selection quality—being the obvious, well-understood, trustworthy option when an agent (or the model behind it) decides where to send intent. That is continuous work on representation and evidence, not a one-time SEO project.
How Second Wind positions you for an agent-first internet
Second Wind exists at the intersection of GEO and infrastructure. We help companies publish and maintain a structured AI reference layer—the AI Surface—so models have a clear, citable source of truth for who you are, who you are not, and how you compare. We pair that with monitoring and telemetry across major AI surfaces so you see how behavior drifts over time and can improve with evidence, not guesses.
On the execution side, we are building toward the same future the protocols point to: machine-readable capability signals and scoped endpoints (quotes, eligibility, scheduling, purchase initiation) so that when an agent does choose you, the handoff is clean—without replacing Shopify, Stripe, or your existing stack.
The operating loop is simple to describe: probe how models behave, observe citations and routing patterns, update the reference layer, measure again. That loop is what turns GEO from a buzzword into a durable capability as assistants get more purchase authority.
Why this window exists now
Surfaces, models, and standards are still in motion. That creates a window: organizations that invest now in accurate AI positioning and measurement establish a baseline before agent checkout is ubiquitous in their category. Late entrants will be optimizing under pressure—playing catch-up on how they are described while competitors already look “obvious” to the same systems.
We are building the infrastructure for that path—reference, behavior intelligence, and execution readiness—so partners who work with us early compound instead of scrambling when the channel flips from “recommendation” to “recommendation plus transaction.”
Pulling it together
GEO and AI positioning are how you win in answers today. When executed correctly, they're also how you set up to win when those answers turn into actions. Agentic commerce does not replace that work—it raises the stakes.
If you want to explore what this looks like for your company—model-native reference layer, monitoring, and roadmap toward agent-ready completion—we welcome the conversation.
Further reading
- Agentic commerce, AI tools, and protocols for retailers — Google
- Universal Commerce Protocol (UCP) — Google Developers
- Developer's guide to AI agent protocols — Google Developers
- Function calling and agentic workflows — OpenAI