My content is comprehensive but AI never cites it. Is readability the issue? How do you structure content for AI?

You’ve identified the problem but drawn the wrong conclusion. AI doesn’t prefer “dumbed down” content - it prefers extractable content.

Here’s how AI systems actually process your content:

1. They break it into chunks (roughly 800 tokens per chunk)
2. They create embeddings (mathematical representations of meaning)
3. When a user asks a question, they retrieve the most relevant chunks
4. They synthesize an answer from those chunks

The problem with comprehensive, nuanced content:

If your answer to a specific question is spread across 5 paragraphs with context, caveats, and nuance, AI has to:

• Retrieve multiple chunks
• Figure out which parts are the core answer
• Synthesize them coherently

That’s hard. It often fails.

The advantage of “simpler” content:

Each section provides a complete, standalone answer. AI retrieves one chunk, extracts the answer, done.

The fix isn’t dumbing down - it’s restructuring:

Keep your depth, but make each section self-contained. Lead with the direct answer, then add nuance. AI will extract the direct answer; curious users will read the nuance.

I did an experiment that might help you.

The test:

Took a comprehensive guide (similar to yours) and created two versions:

• Version A: Original comprehensive format
• Version B: Same content, restructured with answer-first format

Published both on different subdomains, waited 6 weeks, tested in ChatGPT and Perplexity.

Results:

Version B was cited 4x more often despite having identical information.

What I changed:

1. First 50 words of each section became a direct answer to the section heading
2. Paragraphs shortened from 5-6 sentences to 2-3
3. Key terms bolded to help AI identify important concepts
4. Comparison table added summarizing key points
5. FAQ section added at the end restating main points as Q&A

The content quality didn’t change. The extractability did.

Nobody’s mentioned Flesch-Kincaid reading level yet.

Research shows AI citations correlate with content at Grade 6-8 reading level. Grade 11+ content sees noticeably fewer citations.

This doesn’t mean dumbed down - it means:

• Shorter sentences (under 20 words)
• Active voice instead of passive
• Clear subject-verb-object structure
• Technical terms defined when introduced

AI systems trained on vast internet data are essentially calibrated to “average” readability. Content significantly above that level is harder to parse accurately.

Check your readability score. If it’s Grade 12+, that might be part of your problem.

From a technical perspective, here’s why your comprehensive content might be losing:

Embedding similarity problem:

When a user asks “How do I do X?”, the AI creates an embedding of that question and searches for content with similar embeddings.

Your comprehensive content talks about X in context of Y and Z, with caveats about A, B, and C. The embedding represents this rich, contextual meaning.

Your competitor’s content says “Here’s how to do X: [direct steps].” The embedding is a closer match to the question.

The solution:

Keep your comprehensive coverage, but add a section that’s a direct match for the common question. Think of it as the “TL;DR” that AI can extract while your full content remains for human readers.

Many successful sites now have both: a 40-60 word answer-first summary, followed by comprehensive depth.

Practical formatting tips that increased our citation rate:

Structure changes:

• H2 headings phrased as questions matching user queries
• Answer in first 2 sentences under each heading
• Paragraphs never exceed 3 sentences
• Bullet points for any list of 3+ items

Semantic helpers:

• Bold key terms on first use
• Define technical terms in parentheses immediately after
• Use consistent terminology (don’t say “tool” in one place and “software” in another)

Tables are gold:

• AI loves extracting table data
• Any comparison should be a table
• Feature lists as tables
• Statistics as tables

What to avoid:

• Information hidden in tabs or accordions
• Key points only in images
• Passive voice
• Long sentences with multiple clauses

We didn’t dumb down our content - we made it machine-readable.

This is incredibly helpful. I think I finally understand the disconnect.

My mental model was wrong:

I was thinking “comprehensive content = better for AI because more information.”

Reality: “Extractable content = better for AI because easier to process.”

What I’m going to do:

1. Keep the comprehensive depth but restructure for modularity
2. Add answer-first summaries (40-60 words) at the start of each major section
3. Check and improve reading level (targeting Grade 7-8)
4. Convert comparison paragraphs to tables
5. Make sure each H2 section works standalone

The key insight: I’m not dumbing down, I’m making each piece independently valuable while keeping the whole comprehensive.

Question for the group: any tools you use to test how AI “sees” your content structure?

To test how AI sees your content:

Manual testing:

1. Take your content and paste it into ChatGPT
2. Ask it to summarize each section in one sentence
3. If it struggles or combines sections incorrectly, your structure isn’t clear

Technical testing:

1. View page with JavaScript disabled - is key content visible?
2. Check your HTML source - is content in semantic tags or buried in divs?
3. Run through a readability checker for grade level

AI-specific testing:

1. Ask ChatGPT/Perplexity your target questions
2. If they cite competitors, paste competitor content and yours side by side
3. Ask AI: “Which content more directly answers the question [X]?”

The AI will often tell you exactly why it prefers one over the other.

For ongoing monitoring, Am I Cited tracks which specific content gets cited so you can identify patterns in what works.

Content design perspective that might help:

The web taught us to write for scanners. AI takes this further - it’s the ultimate scanner.

Progressive disclosure for AI:

• Level 1: The headline (what’s this about)
• Level 2: First sentence (the answer)
• Level 3: First paragraph (the context)
• Level 4: Full section (the depth)

AI typically extracts Level 1-3. Human readers who want depth get Level 4.

Design each section so that extracting just the first sentence still provides value. Then the rest adds richness without being required.

This is basically good web writing principles, just executed more rigorously.

One more technical consideration: schema markup.

If you have FAQ sections, HowTo guides, or other structured content, proper schema tells AI exactly what’s there.

FAQPage schema is particularly powerful because it explicitly marks what’s a question and what’s an answer. AI doesn’t have to infer this from your content structure.

We saw a 23% increase in AI citations after implementing proper schema across our guide content. The content didn’t change - just the machine-readable signals about what it contained.

Don’t rely on AI to figure out your structure. Tell it explicitly through schema.