AI assistants can now do more than answer product questions — some can browse a store, compare options against a brief, and complete a purchase on a customer's behalf, with the human approving the final step. This is agentic commerce, and while adoption in Australia is still early, the sites that adapt now will have a real head start once it's mainstream.
What agentic commerce actually looks like
A customer tells an AI assistant what they want — 'find me a waterproof jacket under $200 that ships to Sydney by Friday' — and the agent searches, compares specs and prices across sites, and returns a shortlist or completes the purchase directly. The AI is effectively doing the browsing, filtering and initial decision-making that a human used to do manually across multiple tabs.
Why this matters even before it's mainstream
The businesses that get discovered by shopping agents are the ones whose product data is clean, structured and machine-readable today. Waiting until agentic commerce is common to fix messy product feeds means starting from behind — the technical foundation is worth building now, while the upside is still low-risk to experiment with.
Structured product data is non-negotiable
An AI agent can't 'see' a beautifully designed product page the way a human can. It needs Product and Offer schema, accurate pricing, availability, and specifications in structured data — not buried in an image or rendered only via client-side JavaScript the agent may not execute. Clean, complete Product schema is the single highest-leverage fix here.
Reviews and trust signals matter to agents too
Agents weighing multiple options for a customer favour listings with genuine, verifiable review signals and clear return or shipping policies — the same trust signals a careful human shopper would look for. Real Review schema tied to real reviews (never fabricated) helps here, same as it does for regular search.
Let the right crawlers and agents in
Check your robots.txt doesn't accidentally block the crawlers and agent user-agents that power these AI shopping tools. If an agent can't access your product pages at all, it simply won't include you in its comparison — no matter how good your prices are.
Price and availability accuracy is now a discovery factor, not just a UX one
An agent that recommends a product at the wrong price, or that turns out to be out of stock, produces a bad result for the user — and agents are built to learn from and avoid sources that do this repeatedly. Real-time-accurate stock and pricing data is more important than ever.
This is an extension of GEO, not a separate discipline
Everything that makes you visible to ChatGPT and Perplexity as an information source — structure, clarity, schema, crawler access — is the same foundation that makes you visible to shopping agents as a transaction source. If you've already invested in GEO, you're most of the way there.
Getting ready without overbuilding
You don't need to build for a fully agentic future today — you need clean product data, accurate schema, and open access for the crawlers and agents already operating. If you want your ecommerce site's product data and AI visibility properly audited, our GEO / AI SEO service covers exactly this, and our AI automation team can help keep pricing and stock data accurate in real time — get in touch to talk through your setup.