Google says my content is fine but AI never cites it. How do I fix 'thin content' for AI systems specifically?

You’ve identified something important: AI thin content is different from Google thin content.

Here’s the technical explanation:

Google thin content:

• Evaluated at page level
• Compared against query intent
• Ranking factor among many

AI thin content:

• Evaluated at passage level
• Selected for retrieval and synthesis
• Binary: either extracted or not

A 700-word post might satisfy Google’s query intent evaluation while having zero passages that AI systems find worth extracting.

The minimum threshold question:

There isn’t a word count minimum. There’s a completeness minimum.

Can an AI extract a single passage from your content that completely answers a user question without needing synthesis from other sources?

If yes: thick enough for AI If no: thin for AI purposes

Your 600-800 word posts probably spread answers across paragraphs rather than providing complete answers in single passages.

Dealt with a similar 200+ post audit. Here’s my prioritization framework:

Step 1: Identify high-potential pages

• Filter to pages ranking top 20 for target keywords
• These already have Google authority, just need AI optimization
• Usually about 20-30% of posts qualify

Step 2: Categorize by fix type

Type A (Expand): Good topic, needs depth

• Add 500-1000 words
• Include original data/examples
• Create modular sections

Type B (Restructure): Good depth, needs format

• Already long enough
• Add answer-first summaries
• Break into clear sections

Type C (Consolidate): Thin but duplicative

• Multiple posts on similar topics
• Merge into comprehensive resource
• Redirect old URLs

Type D (Retire): Not worth fixing

• Low traffic, low potential
• No unique angle
• Consider removing or noindexing

For 200 posts: Expect roughly 40 Type A, 30 Type B, 50 Type C, and 80 Type D.

The biggest thin content signal for AI: you’re citing others instead of being cited.

Look at your posts. How many contain original:

• Data from surveys or research?
• Case studies with specific results?
• Frameworks you created?
• Examples from direct experience?

If the answer is “very few,” that’s your thin content problem.

AI systems prefer sources. When your content says “According to [other source], the best practice is…” AI will cite that other source, not you.

When your content says “Based on our analysis of 500 companies, the best practice is…” AI will cite YOU.

The fix isn’t just adding words. It’s adding original value that makes you the source rather than the messenger.

ROI calculation for thin content improvement:

Current state:

• 200 posts
• 5% AI citation rate
• Estimated 10 AI citations total

Target state (realistic):

• Fix top 70 posts (Type A + B + C consolidation)
• 40% AI citation rate for fixed posts
• Estimated 28 AI citations from fixed content

Cost:

• 70 posts x 4 hours average = 280 hours
• At $100/hour = $28,000

Value: Depends on your niche and conversion rates. If each AI citation drives $500 in customer lifetime value, that’s $14,000 initial value with compounding as AI search grows.

The real calculation: AI search traffic is growing 30%+ annually. Content you fix now compounds. Content you leave thin becomes increasingly invisible.

Don’t ROI calculate it as a one-time project. Calculate it as an investment in an appreciating asset.

Quick wins for thin content that don’t require full rewrites:

1. Add answer-first summaries (30 min per post)

• 40-60 word summary at top
• Direct answer to the implicit question
• Even thin posts become more extractable

2. Add FAQ section (20 min per post)

• 3-5 questions answered briefly
• Perfect for AI extraction
• Doesn’t require expanding main content

3. Add comparison table (15 min per post)

• Summarize key points in table format
• Highly extractable by AI
• Adds value without lengthy prose

4. Add schema markup (10 min per post)

• FAQPage schema for FAQ sections
• Article schema with proper author
• Tells AI exactly what content you have

These quick fixes can improve citation potential by 30-40% even without comprehensive rewrites. Good way to improve ROI when you have 200 posts to address.

This is exactly what I needed. Let me synthesize the action plan:

Phase 1: Audit & Prioritize (Week 1)

• Run Am I Cited to identify current citation patterns
• Categorize all 200 posts (Expand, Restructure, Consolidate, Retire)
• Filter by commercial intent for prioritization

Phase 2: Quick Wins (Weeks 2-3)

• Add answer-first summaries to top 50 posts
• Add FAQ sections to posts targeting question queries
• Implement schema markup across all salvageable posts

Phase 3: Deep Fixes (Weeks 4-12)

• Expand Type A posts with original data/examples
• Restructure Type B posts for modularity
• Consolidate Type C posts into comprehensive resources

Phase 4: Retire & Redirect (Week 13)

• Noindex or remove Type D content
• Set up redirects from consolidated pages

Key insight I’m taking away:

The problem isn’t word count, it’s extractability and originality. I need to make each post a source that AI wants to cite, not a summary of other sources.

Going to track citation rate improvements with Am I Cited monthly to measure impact.

One more consideration for agencies handling this:

Client education matters.

Clients often measure content by quantity. “We published 50 posts this year!” But thin quantity produces thin results.

Frame the conversation around AI-ready content inventory rather than post count. Show them that 200 thin posts producing 10 AI citations is worse than 50 comprehensive posts producing 50 citations.

The metric shift: from posts published to citations earned.

This also helps with ongoing content strategy. Better to publish 2 comprehensive, AI-ready posts per month than 8 thin ones.

Technical check for thin content that people miss:

Is your content even visible to AI crawlers?

Run these checks:

1. View source with JavaScript disabled - is main content there?
2. Check robots.txt - are AI crawlers allowed?
3. Look at server logs - are AI bots (GPTBot, PerplexityBot, ClaudeBot) crawling?

I’ve seen cases where content was “thin” simply because AI systems couldn’t access it properly. JavaScript rendering issues, crawler blocks, or slow page loads that cause timeouts.

Before investing in content expansion, make sure the technical foundation allows AI to see what you already have.

Final thought on thin content strategy:

Not all thin content is worth fixing.

AI citations matter most for:

• Consideration-stage queries
• Brand-building informational content
• Comparison and “best of” queries

AI citations matter less for:

• Pure transactional pages (product pages, pricing, etc.)
• Very niche queries with low AI search volume
• Time-sensitive content that will be outdated

Focus thin content fixes on the categories where AI citations actually drive business outcomes. Don’t waste resources optimizing content that wouldn’t convert even if it got cited.