Introduction
For over two decades, SEO has shaped how we reach audiences online. But the web is changing again. Generative AI now writes, reasons, and recommends, drawing directly from structured data rather than keyword lists.
Generative Engine Optimization (GEO) represents the next evolution of discoverability. Instead of optimizing for a list of blue links, we’re optimizing for inclusion in AI-generated answers and actions.
I’ve been implementing schema.org structured data for over ten years, and it’s clear that structured data is quickly becoming the language of machine understanding.
From SEO to GEO
Traditional SEO rewarded matching strings of text to search queries. Generative search rewards structured meaning and factual precision.
- SEO: Optimizing for visibility in a list of results
- GEO: Optimizing for inclusion in generative answers and actions
To be included in an AI-generated response, your content must serve as a source of truth that an LLM can interpret confidently.
Check out these recent queries to my site and their format:
Structured Data as the Foundation
Structured data defines how entities relate: products, reviews, organizations, and prices all become nodes in a knowledge graph.
Proper schema implementation allows AI to interpret facts with precision rather than inference.
By marking up your content with schema.org types like Product, Offer, Review, and Organization, you make your content both human-readable and machine-actionable.
Validate your schema using the Schema.org Validator rather than Google’s limited Rich Results Test. The former shows all structured data, while the latter only displays what’s eligible for enhanced search listings.
From Knowing to Doing with Action Schema
GEO is not only about being readable. It’s about enabling AI to act on your behalf.
For instance, a newsletter signup form and confirmation page marked up with Action > InteractAction > RegisterAction schema data tells an AI agent that:
- A registration form exists
- The action can be completed successfully
- A confirmation occurs after submission
This is how websites move from being indexed to being interactive. AI agents can understand and complete structured actions without direct human input, truly becoming autonomous agents.
Agentic AI and the Commerce Ecosystem
Agentic AI differs from generative AI by focusing on autonomous decision-making and learning. It perceives, reasons, acts, and learns from outcomes.
In eCommerce, this evolution allows AI agents to handle:
- Product discovery and comparison
- Price verification and purchase authorization
- Warranty and return policy checks
- Automated order placements
To prepare, developers must ensure that:
- All product and policy data is structured and current
- Payment endpoints are ready for AI-based transactions
- Policies are transparent and accessible
Protocols like AP2 (Agents-to-Payments) and ACP (Agentic Commerce Protocol) are already defining how AI can transact responsibly.
Why GEO Matters Now
Search engines are becoming answer engines. Visibility is no longer about ranking; it’s about relevance and reliability.
Generative Engine Optimization ensures that your content is both discoverable and citable within AI ecosystems. Structured data and semantic clarity are the keys to being part of those answers.
The web of the future is not just crawled; it’s comprehended.
Continue reading: Building AI-Ready eCommerce Sites: A Practical Guide to Generative Engine Optimization (GEO)