Whether or not you believe in the hype around “agentic commerce” (spoiler: mass adoption is years away), one thing is already proven: consumers are using AI to research purchases—products, travel, services, everything. And because AI makes research frictionless, shoppers are evaluating options more deeply than ever.
That shift changes the rules.
SEO Was About Ranking. GEO Is About Being Understood.
SEO has always been a human-driven discipline: optimize pages, structure metadata, insert keywords, earn links. Done well, it gets you the click.
GEO (Generative Engine Optimization) is fundamentally different.
Now the goal isn’t just visibility—it’s comprehension. AI systems must be able to understand your product well enough to explain it, compare it, and recommend it.
If they can’t? They’ll answer anyway.
The Real Risk Isn’t AI. It’s Missing Data.
Ask yourself: how often does AI reply “I don’t know”? Almost never. LLMs are designed to produce answers. When they lack authoritative product information, they fill gaps with:
- competitor content
- outdated sources
- or hallucinated details
That means shoppers can ask AI anything about your product—and if you haven’t supplied the data, someone else’s information becomes your brand narrative.
Why Agentic Commerce Isn’t the Point (Yet)
Yes, “agentic commerce protocols” are getting attention. But almost nobody is actually buying directly through AI chats today.
Research, though? That’s already universal.
Buying through AI requires behavioral trust shifts. Asking AI for product guidance does not. GEO matters now because AI-driven research is already mainstream.
Agencies Face a Structural Problem
Traditional SEO agencies are built around services:
- audit
- recommend
- optimize
- repeat
That model doesn’t scale for GEO.
To educate AI properly, brands need dramatically richer product content—often 10× more structured information than exists on current PDPs. No client team has the bandwidth to create that manually. No agency can sustainably deliver it as a service.
This isn’t a labor problem.
It’s a systems problem.
Systems Beat Headcount
The world generated 149 zettabytes of data in 2024, projected to reach 181 zettabytes in 2025. The information needed to educate AI about products already exists—spec sheets, internal docs, support logs, supplier files, PDFs, spreadsheets.
The challenge isn’t content creation.
It’s extraction, structuring, and activation.
Winning brands will deploy systems that:
- capture product knowledge from internal sources
- normalize and structure it
- encode it for machine understanding
- control what is exposed publicly
In other words: they build infrastructure for product intelligence.
The New Agency Question
Every agency serving ecommerce clients should be asking:
Do we know how to build systems that make our clients’ products intelligible to AI?
If the answer is no, your SEO offering has a ceiling.
If the answer is yes, you’re not just optimizing pages anymore.
You’re shaping how machines explain products to the world.
Brandfuel exists for exactly this transition: turning scattered product data into structured intelligence that AI can trust, cite, and recommend.