AI search optimisation is the process of improving your content, technical setup, and brand authority so that AI-powered search tools — including ChatGPT, Perplexity, Gemini, and Google AI Overviews — are more likely to cite your brand in generated answers.
This guide is structured as a practical playbook for enterprise SEO and content teams. It covers the five-step process from audit to measurement, with enterprise-specific considerations at each stage.
Step 1: Audit your current AI search visibility
Baseline your AI citation frequency
Before optimising, establish where you currently stand. Test your brand across ChatGPT, Perplexity, and Gemini for the 20–30 queries most relevant to your commercial goals.
Run a structured audit using these inputs:
- Your top commercial queries ("best [product category] for enterprise")
- Your brand name directly ("what do you know about [brand]?")
- Competitor queries ("who are the leading providers of [service]?")
- Problem-aware queries ("how do enterprise teams [solve problem X]?")
Record which AI tools mention your brand, where in the response, and with what framing. This is your baseline.
Step 2: Identify and fix crawl access issues
Remove AI crawler blocks in robots.txt
Check that GPTBot, ClaudeBot, Google-Extended, and Applebot-Extended are not blocked. Any block removes your content from that model's index.
Check your robots.txt for these user agent names and remove any Disallow: / rules against them. Separately, update your sitemap.xml to include all key commercial, editorial, and support pages so AI crawlers can discover your full content scope.
Step 3: Restructure priority pages for AI extraction
Rewrite the top 10–20 pages for direct-answer format
Identify the pages that target your highest-value AI query categories and restructure them to lead with direct answers, use clear H2/H3 headings, and include FAQ sections.
The restructuring checklist for each priority page:
- Does the page open with a direct definition or answer to the core query?
- Are H2 and H3 headings written as questions or direct statements?
- Is there a FAQ section with 4–8 questions matching likely user queries?
- Is there a
FAQPageJSON-LD schema block? - Is there author attribution with a linked author profile?
- Is the page internally linked from the pillar article on this topic?
Step 4: Implement schema across all key pages
Add JSON-LD to every indexable page
Schema markup helps AI models understand the type, context, and authority of your content. At minimum: Article, FAQPage, Person, BreadcrumbList on editorial pages; Course or Service on product pages.
Priority schema types for enterprise AI search optimisation:
Article— on every editorial and thought leadership pageFAQPage— on every page with a FAQ sectionPerson— on author profiles and instructor pagesCourse— on online training and course pagesService— on service and solutions pagesOrganization— on the homepage and about pageBreadcrumbList— on all sub-pages
Learn the full AI search optimisation framework
The AI SEO course for enterprise teams covers this entire process with templates, real examples, and measurement frameworks.
View the AI SEO course →Step 5: Track and report AI search visibility
Build an AI citation tracking cadence
Re-run your baseline query set monthly across ChatGPT, Perplexity, and Gemini. Track citation rate, position in response, and framing. Report alongside traditional SEO metrics.
AI search visibility metrics worth tracking:
- Citation rate — % of target queries where your brand is mentioned
- Citation position — early vs late in the AI response
- Sentiment — positive, neutral, or negative framing in citations
- Competitive share of AI voice — your citations vs competitors
- Branded search trends — indirect signal of AI-driven brand awareness
Related reading
- What is AI SEO? The complete enterprise guide
- Enterprise SEO for AI search
- AI SEO course for enterprise teams
Frequently asked questions
What is AI search optimisation?
AI search optimisation is the process of improving your content, technical setup, and brand authority so that AI-powered search tools — including ChatGPT, Perplexity, Gemini, and Google AI Overviews — are more likely to cite your brand in generated answers.
How do I measure AI search visibility?
AI search visibility can be measured by tracking citation frequency across ChatGPT, Perplexity, and Gemini for target queries, monitoring brand mentions in AI-generated responses, and tracking indirect signals like branded search volume and referral traffic patterns.
Where should enterprise teams start with AI search optimisation?
Start with a baseline audit of your current AI citation frequency, then fix any crawl access issues in your robots.txt. After that, restructure the 10–20 pages that target your highest-value query categories for direct-answer format and implement JSON-LD schema.
