Schema Markup for Local AI Visibility: The Technical Guide

When an AI agent tries to answer a local business query, it is looking for structured, machine-readable data it can cite with confidence. Schema markup is exactly that — a standardized vocabulary embedded in your website that tells AI agents: this is a business, this is what it does, this is where it is, these are its hours.

Without schema markup, AI agents have to infer everything from unstructured text. This inference process is error-prone. A plumber whose website says "we keep your pipes flowing" gives an AI agent far less to work with than one whose website has a LocalBusiness schema declaring the @type as Plumber, a service area, and explicit hours.

Schema markup does not guarantee AI recommendations — but the absence of it is one of the most common reasons AI agents skip local businesses entirely or get their information wrong.

Every local business website needs LocalBusiness JSON-LD on the homepage. This is the non-negotiable baseline. Without it, AI agents have no machine-readable confirmation of your business type, location, or contact information.

Use the most specific @type available. Plumber outperforms LocalBusiness for plumbing queries. Schema.org has specific types for dentists, lawyers, restaurants, and dozens more.

After LocalBusiness schema, FAQPage JSON-LD is the single highest-leverage schema addition for AI visibility. AI agents are question-answering machines. When a user asks whether a business offers emergency service, the AI looks for a direct answer to that exact question. FAQPage schema provides those answers in a format the AI can extract and cite directly.

Five FAQs is the minimum. Ten is better. Write them as the actual questions your customers ask — not marketing copy. Each FAQ answer should be a complete, standalone response. AI agents extract these answers and cite them directly. If your answer requires context from a previous sentence to make sense, it will not cite well.

The most common cause of wrong AI recommendations is that the AI does not know exactly what services a business offers. Service schema fixes this with explicit, typed service declarations. Add one Service schema block per major service offering. Five to ten services is ideal. Each service schema increases the range of specific queries your business can match.

Schema markup is implemented as JSON-LD — a script block in the head of your HTML. It does not change what visitors see. Validate your implementation at Google's Rich Results Test after adding schema. Common errors: required fields missing, incorrect @type used, schema present in template but not rendering on live pages.

GeoProof audits your schema markup as part of the free AI visibility audit and flags any errors or missing fields with specific fixes.