AI-SEO: The Complete Guide with 11 Essential Checks to Rank in AIs
After analyzing 60+ AI citations across multiple platforms and running controlled experiments with Savannabay's AI comparison tool, I identified 11 critical patterns that determine whether content gets cited by AI systems. This guide shares everything I learned from that research—the exact elements that made the difference between being cited and being ignored.
What Is AI-SEO?
AI-SEO (Artificial Intelligence Search Engine Optimization) is the practice I've been developing to optimize content for discovery and citation by artificial intelligence systems like ChatGPT, Perplexity, Gemini, Claude, and Grok.
Unlike traditional SEO, where the goal is to rank in Google's top positions, in AI-SEO the objective is to be cited in AI-generated responses when users ask questions relevant to your niche.
Why I Started This Research
I wanted to understand what sources AI platforms trust when answering questions. So I ran a controlled experiment analyzing dozens of citations to see what patterns emerged. What I discovered changed how I think about content optimization entirely.
This research is part of a broader investigation into AI citation patterns in 2025, where I analyzed 60+ citations across multiple platforms to understand what actually gets cited by AI systems.
The numbers tell a compelling story:
- ChatGPT has over 800 million weekly active users and processes 2.5 billion prompts daily
- Perplexity processes over 780 million queries per month, up 239% year-over-year
- AI platforms generated 1.13 billion referral visits in June 2025, representing a 357% increase from 2024
- 52% of ChatGPT users prefer using AI over traditional search
- AI search traffic converts at 14.2% compared to Google's 2.8% - over 5x higher conversion rates
If your content isn't optimized for AI-SEO, you're missing a massive opportunity.
My First Discovery: One Word Changed Everything
In my initial tests, my first few queries returned zero citations. ChatGPT gave generic advice without sources.
Then I added one word to my query: "2025".
Suddenly, full citations appeared.
The insight: Temporal specificity triggers citation behavior. AI models interpret year-specific queries as requiring current, sourced information rather than general knowledge.
AI-SEO vs Traditional SEO
Through my research, I found that while AI-SEO shares fundamental principles with traditional SEO like E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), there are important differences. For a deeper dive into this topic, check out my complete guide to Answer Engine Optimization.
Traditional SEO:
- Focuses on ranking in Google's positions 1-10
- Metrics: ranking position, CTR, impressions
- Goal: appear on the first page
- Direct competition for keywords
AI-SEO:
- Focuses on being cited in AI responses
- Metrics: citation rate, market share per Q&A, performance per LLM
- Goal: be the AI's information source
- Multiple sources can be cited simultaneously
I discovered that you don't need to be #1 on Google to be cited by AIs. Small sites I'd never heard of appeared alongside Reuters and The Verge in citation lists. What they had in common wasn't domain authority—it was tactical specificity, clear structure, and data-backed insights. This is the game-changer: you can compete with major publishers if you go deeper on specific tactics.
This insight led me to develop what I call the differentiation strategy, which I detail in my guide on why differentiation beats optimization for ranking in AI results. The principle is simple: being different beats being better.
The AI-SEO Checker: 11 Essential Checks I Discovered
Based on analyzing 60+ citations, I developed an automated checker that examines 11 critical aspects of content for AI-SEO. Each check is worth 10 points, totaling 100 possible points.
These aren't theoretical—these are the exact patterns I observed in cited content versus content that was ignored.
Let me walk you through each verification, explaining:
- What I'm checking for
- Why I found it matters for AI-SEO
- How the algorithm works technically
- How you can optimize your content based on my findings
Check 1: Recent Date (Current Year and Last 6 Months)
Scoring: All or nothing - 10 points if found, 0 if not found
What I Check For
This was my first major discovery. I look for dates in your content that are:
- From the current year (2025)
- Within the last 6 months
Why I Found This Matters
In my experiments, adding "2025" to a query transformed the response from generic advice to fully cited, sourced information. AI systems like ChatGPT and Perplexity prioritize recent content, especially when:
- The user includes the year in the question (e.g., "best CRMs in 2025")
- The topic is prone to change (technology, policies, trends)
- The search requires updated information
A visible and recent date functions as an immediate freshness signal for AI algorithms.
How My Algorithm Works
My checker searches for dates in multiple formats:
- DD/MM/YYYY or MM/DD/YYYY: 25/11/2025, 11/25/2025
- YYYY-MM-DD: 2025-11-25 (ISO format)
- "Month DD, YYYY": November 25, 2025
- "DD Month YYYY": 25 November 2025
The algorithm:
- Extracts all dates found in HTML and text
- Validates if they are real dates
- Checks if they are from the current year (2025)
- Verifies if they are within the last 6 months
- Returns the most recent date found
How to Optimize Based on My Research
Add a prominent date at the top of your article:
<p class="publication-date">Published: November 25, 2025</p>
<p class="last-updated">Last Updated: November 25, 2025</p>
Best practices I recommend:
- Place the date near the main title
- Use clear and readable formats
- Update the date when you revise the content
- Even for evergreen content, add a publication/update date
Check 2: Heading Structure (H1, H2, H3 Tags)
Scoring: 10 points if passes (≥1 H1 AND ≥2 H2/H3), 0 points if doesn't pass
What I Check For
My checker analyzes the hierarchy of titles in your content:
- At least 1 H1 tag (main title)
- At least 2 H2 or H3 tags combined (subheadings)
Why I Found This Matters
In my citation analysis, I noticed that well-structured content with clear headings appeared far more frequently. Heading structure is fundamental for AI-SEO because:
- Semantic Hierarchy: AIs use headings to understand content organization
- Efficient Parsing: Headings facilitate the extraction of specific information
- Context: They help the AI understand which sections answer which questions
- Precise Citation: AIs can reference specific sections based on headings
How to Optimize Based on My Research
Good Headings (Descriptive):
<h1>How to Treat Scalp Psoriasis at Home: 2025 Guide</h1>
<h2>Why Steroid Treatments Don't Work for Everyone</h2>
<h2>5 Evidence-Based Home Remedies</h2>
<h3>Tea Tree Oil: How to Use It Correctly</h3>
Bad Headings (Generic):
<h1>Psoriasis</h1>
<h2>Introduction</h2>
<h2>Methods</h2>
<h2>More Information</h2>
Best practices I recommend:
- H1 should contain the main question or theme
- H2/H3 should be descriptive, not generic
- Use logical hierarchy (don't skip from H1 to H3)
- Include keywords naturally in headings
Check 3: Bulleted Content (Lists)
Scoring: 1 point for every 2.5% of content in lists, maximum 10 points at 25%
What I Check For
This check calculates what percentage of your content is organized in lists (<ul>, <ol>, <li> tags).
Why I Found This Matters
In my analysis, I noticed that cited content frequently used lists to organize information. Lists are crucial for AI-SEO because:
- Scannability: List content is easier to scan for humans and AIs
- Structure: AIs can easily extract structured information
- Citation: It's simpler to cite a specific item from a list
- Clarity: Lists convey information in a concise and organized way
Ideal Target I Recommend
25% or more of your content should be in lists to obtain maximum score.
How to Optimize Based on My Research
Use lists for:
- Steps in a process
- Features or characteristics
- Pros and cons
- Options or alternatives
- Symptoms, causes, solutions
- Recommendations
Check 4: FAQ Section
Scoring: All or nothing - 10 points if found, 0 if not found
What I Check For
My checker detects whether the content has a Frequently Asked Questions (FAQ) section through multiple indicators.
Why I Found This Matters
FAQ sections are extremely valuable for AI-SEO based on my research:
- Q&A Format: AIs are trained to understand questions and answers
- Long-tail Keywords: FAQ captures variations of questions users ask
- Direct Citation: AIs can easily extract specific answers
- Rich Context: FAQ shows you anticipated common doubts
How to Optimize Based on My Research
Option 1: FAQ with Schema.org (Best for AI-SEO)
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "How to treat scalp psoriasis?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Treatments include..."
}
}]
}
</script>
Tips I recommend for effective FAQ:
- Include 5-10 relevant questions
- Use real questions that users ask
- Answers should be concise (2-4 paragraphs)
- Combine with Schema.org for maximum impact
Different AI platforms have different preferences for FAQ content. In my testing, I found that Perplexity particularly loves FAQ sections and question-based headings. If you're specifically optimizing for Perplexity, check out my complete guide to getting cited in Perplexity, which includes platform-specific tactics for FAQ optimization.
Check 5: Tables
Scoring: All or nothing - 10 points if found, 0 if not found
What I Check For
My checker detects the presence of HTML tables (<table> tags) in the content.
Why I Found This Matters
Tables are valuable for AI-SEO based on my observations:
- Structured Data: AIs can easily extract tabular data
- Comparisons: They facilitate direct comparisons between options
- Searchable: HTML text is indexable, unlike table images
- Accessible: Screen readers and AIs can read the content
Never use screenshots or images of tables. AIs cannot read text in images. Always use HTML tables so the content is searchable and indexable.
How to Optimize Based on My Research
Use tables for:
- Product or service comparisons
- Pricing tables
- Feature matrices
- Technical specifications
- Statistical data
Check 6: Direct Answer at the Beginning
Scoring: 10 points if title is not a question OR if direct answer found, 0 if not
What I Check For
This check verifies if:
- The title (H1 or <title>) is a question
- If yes, there is a direct answer in the first 500 characters
- If the title is not a question, automatically passes (10 points)
Why I Found This Matters
Direct answers at the beginning are crucial for AI-SEO based on my testing:
- Search Intent: Users want immediate answers
- Featured Snippets: AIs prefer content that answers directly
- Citability: A clear and concise answer is easier to cite
- User Experience: Improves user experience
How to Optimize Based on My Research
Recommended Structure I Use:
- Direct and concise answer (1-3 sentences)
- Brief context or justification
- Promise of what the article will detail
Check 7: Keyword Consistency (TF-IDF + Coherence)
Scoring: 10 points if coherence ≥ 0.25, proportional below that
What I Check For
This check analyzes how consistent and cohesive keyword usage is in your content, using TF-IDF algorithms and co-occurrence analysis.
Why I Found This Matters
Keyword consistency is important based on my research:
- Topic Focus: AIs value content focused on a specific topic
- Semantic Understanding: Consistent use of related terms helps AIs understand context
- Authority Signal: Specialized and consistent vocabulary signals expertise
How to Optimize Based on My Research
Strategies I recommend to improve coherence:
- Focus on a specific topic: Don't try to cover everything. If you're struggling with topic selection and keyword prioritization, I've created a step-by-step practical framework for GEO that walks you through the entire keyword research and content planning process.
- Use specialized vocabulary consistently: Repeat relevant technical terms
- Distribute keywords throughout the text: Spread naturally
- Use related terms together: Group semantically related concepts
Check 8: Paragraph Segmentation
Scoring: Varies from 0-10 based on average words per paragraph
What I Check For
This check analyzes the size of your paragraphs, measuring how many words on average each paragraph contains.
Why I Found This Matters
Short paragraphs are essential for AI-SEO based on my observations:
- Readability: Easier to read and process
- Mobile-Friendly: Better experience on mobile devices
- Parsing: AIs can extract information more easily
- Scannability: Makes scanning content quickly easier
Ideal Target I Recommend
Less than 120 words per paragraph on average to obtain 10 points.
How to Optimize Based on My Research
Strategies I recommend for shorter paragraphs:
- One idea per paragraph: Each paragraph should develop only one thought
- Break naturally: Break at logical transition points
- 3-5 sentences maximum: General rule for paragraph length
Check 9: Absence of Filler Content (Type-Token Ratio)
Scoring: Based on TTR - 10 points if ≥ 0.20, proportional below
What I Check For
This check calculates the Type-Token Ratio (TTR), a linguistic metric that measures vocabulary diversity.
TTR = Unique Words / Total Words
Why I Found This Matters
High TTR indicates quality content based on my analysis:
- Rich Vocabulary: Use of varied and specific terms
- Substantial Content: Not just repetition or "filler"
- Expertise: Specialized vocabulary signals knowledge
Ideal Target I Recommend
TTR ≥ 0.20 (20% unique words) to obtain 10 points.
How to Optimize Based on My Research
Strategies I recommend to increase TTR:
- Use synonyms: Vary vocabulary instead of repeating the same words
- Be specific: Use technical terms when appropriate
- Avoid unnecessary repetition: Restructure sentences
Check 10: External Links (Sources)
Scoring: Varies according to quantity and diversity of linked domains
What I Check For
This check counts how many external links (to other domains) your content has and how many unique domains are linked.
Why I Found This Matters
External links are valuable for AI-SEO based on my research:
- Credibility: Show your content is well-researched
- Authority: Citing reputable sources increases your own authority
- Context: Provide additional context for readers and AIs
- Trust Signal: Well-referenced content is more trustworthy
Ideal Target I Recommend
5 or more external links to 3 or more different domains to obtain 10 points.
How to Optimize Based on My Research
Types of sources I recommend linking:
- Scientific studies and research (arxiv.org appeared more than any other source in my analysis)
- Government sources and official organizations
- Recognized experts and institutions
- Statistical data and reports
While external links show you're well-researched, don't forget about internal linking strategy. I've developed several advanced ChatGPT SEO tactics that include using AI to map internal linking opportunities across your site—a technique that can dramatically boost your content's authority distribution and help AI systems better understand your topical expertise.
Check 11: Structured Data (Schema.org, JSON-LD)
Scoring: Varies according to types of structured data found
What I Check For
This check detects if the site uses structured data formats:
- JSON-LD (JavaScript Object Notation for Linked Data)
- Microdata (itemscope, itemtype, itemprop attributes)
- RDFa (Resource Description Framework in Attributes)
Why I Found This Matters
Structured data is crucial for AI-SEO based on my observations:
- Semantic Understanding: AIs understand exactly what each element means
- Context: Provide rich context about entities and relationships
- Machine-Readable: Standardized format that AIs process easily
- Knowledge Graphs: Feed AI knowledge graphs
How to Optimize Based on My Research
JSON-LD is the preferred format I recommend because:
- Doesn't interfere with visual HTML
- Easy to add and maintain
- Google and AIs prefer this format
Example - Article Schema:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "Your Article Title",
"author": {
"@type": "Person",
"name": "Author Name"
},
"datePublished": "2025-11-25"
}
</script>
Interpreting Your AI-SEO Score
Now that you understand each of the 11 checks I discovered, let me explain how to interpret your total score.
Score Ranges
90-100 points Excellent
Your content is highly optimized for AI-SEO based on my research. You have great chances of being cited by AI systems.
70-89 points Good
Your content is well optimized, but there's room for improvement. Identify the checks where you lost points and prioritize optimizing them.
50-69 points Moderate
Your content needs significant optimizations. I recommend focusing first on checks worth full 10 points. These are the "quick wins".
0-49 points Needs Work
Your content is not optimized for AI-SEO based on my criteria. I recommend following the checklist systematically, starting with fundamentals.
How I Recommend Prioritizing Optimizations
If you have limited resources, I recommend prioritizing in this order:
- Quick Wins (Low Effort, High Impact):
- Add recent date (5 minutes)
- Add JSON-LD structured data (15-30 minutes)
- Create FAQ section (1-2 hours)
- Add external links (30 minutes)
- Structural Optimizations (Medium Effort, High Impact):
- Improve headings (1 hour)
- Add HTML tables (2-3 hours)
- Add direct answer at beginning (30 minutes)
- Quality Refinements (High Effort, Medium Impact):
- Convert content to lists (2-4 hours)
- Break long paragraphs (2-3 hours)
- Improve keyword consistency (3-5 hours)
What I Learned: You Don't Need to Be HubSpot to Get Cited
This is perhaps the most important insight from my research: You don't need massive domain authority to be cited by AI systems.
In my analysis, I found small sites I'd never heard of appearing alongside Reuters, The Verge, and major tech publishers. What they had in common wasn't brand recognition or domain authority—it was:
- Tactical Specificity: They went deep on specific implementations
- Clear Structure: Well-organized with descriptive headings
- Data-Backed Insights: They provided evidence and examples
- Temporal Relevance: They included year-specific information
This is the game-changer I discovered: You can compete with major publishers if you go deeper on specific tactics and structure your content for AI parsing.
The Pattern I Observed in Most-Cited Content
The most-cited content followed this formula:
"[Number] [Action/Insight] [Topic] [Year]"
Examples of cited titles from my analysis:
- "7 Schema Markup Patterns That Get You Cited by AI in 2025"
- "5 AI-Friendly Content Structures for 2025"
- "11 Essential Checks for AI-SEO Optimization"
Why this works based on my research:
- Numbers signal tactical, actionable content
- Action words indicate implementation value
- Year specificity triggers AI citation behavior
Going Deeper: Advanced AI-SEO Resources
The 11 checks I've outlined in this guide provide a solid foundation for AI-SEO optimization. However, there are several advanced strategies and platform-specific tactics that can take your results even further.
Based on my ongoing research at Savannabay, I've created specialized guides that dive deeper into specific aspects of AI optimization:
Platform-Specific Optimization
Each AI platform has unique citation behaviors and preferences. My research showed that what works for ChatGPT doesn't necessarily work for Perplexity or other platforms:
- Perplexity SEO: Complete Guide to Getting Cited in 2025 - Perplexity actively diversifies its citations and favors fresh, tactically-specific content over comprehensive authority. This guide shows you exactly how Perplexity's citation behavior differs from ChatGPT and how to optimize for it.
Strategic Frameworks
Beyond technical optimization, success in AI-SEO requires strategic thinking about positioning and differentiation:
- Answer Engine Optimization (AEO): The Complete Guide - A comprehensive overview of optimizing for AI-powered answer engines including ChatGPT, Perplexity, and Google AI Overviews. This guide covers the fundamental shift from ranking for clicks to being cited as the answer source.
- How to Do Generative Engine Optimization: A Step-by-Step Practical Framework - A practical, actionable framework that walks you through the entire process from keyword research to content creation and monitoring. Particularly useful if you're just starting with AI optimization.
- Why Differentiation Beats Optimization for Ranking in AI Results - My strategic playbook explaining why creating unique, differentiated content is more effective than trying to out-optimize established players. Includes the ATLAS method for finding and owning your unique position in AI results.
Advanced Tactics
For those ready to take their AI-SEO to the next level:
- Advanced ChatGPT SEO Tactics That Actually Work - Five advanced techniques including the SERP Gap Analyzer, Internal Link Mapper, and GSC Optimizer. These tactics use ChatGPT itself to accelerate your optimization process and find opportunities competitors miss.
Research & Analysis
Understanding the underlying patterns helps you make better strategic decisions:
- I Analyzed 60+ AI Citations - Here's What Actually Gets Cited in 2025 - The original research that formed the foundation for these 11 checks. This analysis reveals the specific patterns I observed across platforms and explains why certain content gets cited while similar content gets ignored.
Each of these guides complements the 11 checks framework with deeper dives into specific platforms, strategies, and tactics. Together, they form a complete system for AI-SEO success.
Conclusion: What I Discovered About AI Citations
After analyzing 60+ AI citations, I can tell you this: The way people search for information is changing radically, and the strategies that worked for traditional SEO don't necessarily apply to AI-SEO.
The sites that got cited in my research weren't gaming algorithms—they were creating genuinely useful, specific, tactical content with clear structure and authoritative backing.
That's my strategy, and I'm sharing it with you: Own a specific answer that nobody else is answering as clearly, as recently, or as tactically.
Your Next Steps Based on My Research
- Use my checker: Analyze your most important content with these 11 checks
- Start with quick wins: Add dates, structured data, FAQ sections
- Go tactical and specific: Focus on implementation details, not generic advice
- Include the year: Make your content temporally specific
- Structure for parsing: Use clear headings, lists, and tables
AI-SEO doesn't replace quality content—it amplifies quality content. Focus first on creating real value for your audience, then optimize so AIs can find and cite that value. You don't need to be a major publisher to compete. You need to be the best answer to a specific question.
"The best time to start with AI-SEO was 6 months ago. The second best time is now."
About This Research
This methodology is based on my analysis of 60+ AI citations collected in October 2025 using Savannabay's AI comparison platform. I analyzed responses from multiple AI platforms with full citation tracking, examining 4 queries × 3 responses each = 12 total responses. I tracked and categorized 60+ distinct source citations by source type, citation context, and content characteristics.
These 11 checks represent the patterns I observed in content that successfully gets cited by AI systems versus content that gets ignored.
Ready to optimize your content for AI-SEO using my methodology?
Last Updated: November 25, 2025