If you build or maintain sites for small businesses, "AI SEO" (generative engine optimization, or GEO) is quietly becoming a real line item on client checklists. Here's the technical breakdown, no $5,000-course fluff.
The core distinction: classic SEO optimizes for the Google crawler and ranking algorithm. GEO optimizes for what an LLM extracts and cites when answering a user's question. The audience shifts from a search index to a language model, and that changes what "well-optimized" actually means at the markup and content level.
Why it's worth your time as a builder
Google AI Overviews now appear in roughly 1 in 4 searches, often pushing organic results below the fold.
ChatGPT Search passed 300M+ weekly users in 2026.
Perplexity, Gemini, and Copilot collectively serve a meaningful chunk of what used to be pure Google traffic.
For any client site you ship, if it's not structured for LLM extraction, it's invisible in a growing share of discovery traffic.
Six things to actually implement
Entity clarity. NAP (name/address/phone) needs to be byte-identical across the homepage, contact page, footer, and every external citation (GBP, directories, socials). Pair it with explicit @type schema (LocalBusiness, ProfessionalService, or an industry-specific subtype); don't leave the entity type ambiguous.
Schema density. This is the highest-leverage technical lever. Minimum stack for a service-business site:
{
"@context": "https://schema.org",
"@type": "LocalBusiness",
"name": "...",
"address": { "@type": "PostalAddress", ... },
"telephone": "..."
}
Add Service schema per service page, FAQPage on any page with real Q&A, BreadcrumbList sitewide, and HowTo on process/tutorial content. FAQ schema specifically gets lifted verbatim by LLMs more than any other type I've tested against. If you implement one thing, implement that.
Declarative, self-contained paragraphs. LLMs extract sentences out of document context, so anaphora-dependent writing ("That said, it depends...") breaks. Write answer paragraphs that stand alone: direct claim first, 2-4 supporting sentences, no pronouns referring to the previous paragraph. This is a content-layer change, not a code change, but it's worth flagging to whoever writes client copy.
Citation signals. LLMs weight mentions from sources they already trust (GBP, established directories, local press) similarly to how backlinks weight in classic SEO. Not something you fix in code, but worth knowing when you're advising on the full strategy, not just the site.
Long-tail conversational content. AI queries run longer and more natural-language than Google queries ("best plumber for a leaking water heater after hours" vs. "plumber near me"). FAQ sections should mirror actual spoken questions, not keyword-stuffed headers.
Freshness signals. Keep dateModified in your schema actually accurate on meaningful edits (not bumped on every deploy), and ship content on a real cadence. Stale pages get cited less.
Testing it (there's no Search Console for this, at least not yet)
Manual process: query ChatGPT, Perplexity, and Gemini with the exact question a real customer would ask, log whether the site is cited and who else is, repeat monthly. Expect first citations in 8-12 weeks of consistent work if the foundations above are actually in place.
Bottom line
If a site already has solid classic SEO, it's roughly 80% of the way to AI-search-visible. The remaining 20% is schema density, answer-first content structure, and citation building, all genuinely implementable, none of it requires a course.
Original, longer version with a full 90-day rollout plan: https://www.cresoftech.ca/blog/ai-seo-for-small-business-gta-2026
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