The Elephant Test: Does AI Know You Exist?

Before we go further, let’s find out where you stand right now.

Open ChatGPT, Claude, or Perplexity and ask:

“Who is [Your Name] [Your Specialty]?”

Example: “Who is Sue Bell digital marketer?” or “Who is Sue Bell SEO?”

What you’ll discover falls into one of four categories:

Category 1: AI knows exactly who you are

• Cites your frameworks
• References your work
• Mentions your company
• Gets your positioning right

If this is you: You’re already building authority (keep going)

Category 2: AI knows you exist but vaguely

• Generic bio information
• Maybe mentions your company
• No specific frameworks or IP
• Could be you or 50 other people

If this is you: You have presence but not authority (fixable)

Category 3: AI confuses you with someone else

• Wrong person entirely, or
• Pulls information from multiple people with your name
• No clear entity recognition

If this is you: Entity recognition problem (technical fix needed)

Category 4: AI has no idea who you are

• “I don’t have specific information about…”
• Offers to search the web
• Generic “there are many professionals named…”

If this is you: You’re invisible (START HERE, urgent)

I tested this with dozens of marketers.

Some names AI knew immediately. Complete bios. Framework citations. Research mentioned.

Others—people with decades of experience, multiple businesses, thousands of social followers—were completely unknown to AI.

Same industry. Same expertise level. Completely different AI visibility.

The difference?

It’s not credentials. Not experience. Not even social following.

It’s semantic authority.

The people AI knows have:

• Documented frameworks with clear attribution
• Schema markup establishing entity recognition
• Published research that gets cited
• Structured content AI can understand and reference

The people AI doesn’t know have:

• Published 500 generic blog posts
• Built impressive traffic numbers
• Optimized for algorithms
• No original IP AI can cite

Now you know where you stand.

Here’s what determines which category you’re in…

The Training Data Economy

When you publish a blog post, create a framework, or share research, that content doesn’t just sit on your website waiting for Google to rank it.

It gets scraped.

Crawled by AI training systems. Ingested into massive language models. Analyzed for patterns, relationships, and authority signals.

Your content becomes part of the corpus that trains ChatGPT, Claude, Perplexity, Gemini, and every AI answer engine that’s coming next.

This is already happening. Right now. To everything you’ve published.

And here’s the fork in the road:

Path 1: Your content gets absorbed as “training data” but you’re never cited. AI learns from your work, synthesizes your insights, and answers questions in your domain—without ever mentioning your name.

You trained the machine to replace you.

Path 2: Your content gets absorbed as “authoritative source material.” AI learns from your work AND cites you as THE expert. When someone asks about your domain, AI says: “According to [Your Name], creator of [Your Framework]…”

You trained the machine to amplify you.

Same content. Completely different outcomes.

The difference? Semantic authority.

What AI Actually Looks For (And Why Most Content Fails)

Here’s what most people think matters:

• Keyword optimization
• Word count
• Publishing frequency
• Social shares
• Backlink count

Here’s what actually determines if AI cites you:

1. Entity Recognition

Can AI understand that YOU are a distinct, recognizable entity—not just another website spitting out content?

This requires:

• Proper schema markup (Person or Organization schema)
• Consistent attribution across platforms
• Clear credentials and expertise signals
• Knowledge graph presence

Most websites: Zero entity markup. AI sees words, not people.

Result: Generic information source. Citeable? No. Replaceable? Absolutely.

2. Original IP That Can’t Be Synthesized

AI can synthesize information that exists across 100 blog posts into one coherent answer.

But AI can’t create your framework. Can’t conduct your research. Can’t coin your terminology.

If your content is:

• “10 tips for email marketing” → Synthesizable (AI can pull from 500 sources)
• “The Email Velocity Framework for behavioral segmentation” → Uncopyable (only YOU created this)

If your content is:

• “Here are some important statistics about our industry” → Commoditized (AI has access to same data)
• “Our proprietary research surveying 1,000 companies reveals…” → Citeable (unique data source)

Original IP = Must cite the source (you) Generic tips = Can synthesize without attribution

The content that trains AI to cite you is content AI cannot create without you.

3. Semantic Structure (Not Just Keywords)

Keywords told Google: “This page is about email marketing.”

Semantic structure tells AI: “This page documents a methodology called the Email Velocity Framework, created by Sue Bell in 2023, which segments email recipients based on behavioral patterns rather than demographics.”

AI understands:

• Who created it (entity)
• When it was created (timestamp)
• What it’s called (named concept)
• How it works (structured methodology)
• Where to learn more (authoritative source)

This is why two blog posts with identical keyword optimization perform completely differently in AI citation:

Post A: “Email segmentation is important. Here are some ways to segment…”

• No structure
• No attribution
• No entity
• Generic claims

AI treatment: Synthesizes into answer without citation

Post B: “The Email Velocity Framework, developed by Sue Bell (2023), segments based on engagement velocity…”

• Clear structure (HowTo schema)
• Strong attribution (creator, date)
• Entity recognition (Sue Bell as expert)
• Unique concept (named framework)

AI treatment: “According to Sue Bell’s Email Velocity Framework…”

Same topic. One gets cited, one gets absorbed.

4. Citation History (The Compound Effect)

Here’s the brutal truth: Authority begets authority.

If you’ve been cited 100 times, you’re 10x more likely to be cited on the 101st query.

If you’ve never been cited, you probably won’t start now—unless you change your approach.

AI systems look at:

• How often you’re cited elsewhere (media, academic, other content)
• Whether other authoritative sources reference you
• If your frameworks or research are being discussed
• Whether you appear in knowledge graphs

This creates winner-take-most dynamics.

The expert who’s been cited 500 times dominates their domain. The expert who’s published 500 blog posts but never been cited is invisible.

Traffic was never this binary.

In the algorithm era, you could rank #5 and still get meaningful traffic.

In the AI era, #2 gets nothing. AI picks THE authority and cites them.

The Traffic Trap (And Why It Was Always Broken)

Let’s talk about what you’re actually giving up by chasing traffic.

The traffic model:

• Publish content
• Optimize for rankings
• Drive visitors to your site
• Convert some percentage
• Repeat endlessly

The problems:

• Traffic evaporates the moment you stop creating
• Algorithm changes destroy overnight (Google update, social platform pivot)
• Platform dependency (you’re renting attention)
• Linear relationship (2x effort = 2x traffic, maybe)
• Constant content treadmill
• Low conversion (1-3% typical)

The exhaustion is real.

You’ve published 500 blog posts. You’re posting daily on LinkedIn. You’re running ads. You’re optimizing constantly.

And the moment you stop, traffic drops to zero.

You’re not building an asset. You’re renting temporary attention.

The Authority Model (What Actually Compounds)

Here’s what happens when you optimize for citations instead of clicks:

Year 1:

• You publish your framework
• You conduct original research
• You document methodologies
• Schema markup everywhere
• Clear attribution on everything

Result: 20 citations (10 you created via guest posts, 10 organic)

Year 2:

• You update your research (longitudinal data now)
• You evolve framework to v2.0
• You speak at conferences
• You pitch media with fresh research angle

Result: 80 citations total (15 new from you, 45 organic from cross-pollination)

Year 3:

• Annual research update (3 years of trend data)
• Framework v3.0
• Book published
• Media reaching out to YOU now

Result: 240 citations (10 new from you, 150 organic)

Notice the pattern:

Your effort decreases while citations accelerate.

Why? Because citations persist and compound.

That blog post from Year 1? Still being cited in Year 3.

That research from Year 2? Referenced in Year 3 academic paper.

That framework you created? Being taught in Year 3 by certified practitioners.

Past work continues generating returns.

Compare to traffic:

Year 1: 10,000 monthly visitors (with constant publishing) Year 2: 10,000 monthly visitors (with constant publishing) Year 3: 10,000 monthly visitors (with constant publishing)

Stop publishing → Traffic drops to zero immediately

This is why traffic is a trap.

What This Means Practically (The Fork in the Road)

You’re at a decision point.

Option 1: Keep optimizing for traffic

Continue the treadmill:

• Daily social posts
• Weekly blog content
• Constant SEO optimization
• Chasing algorithm changes
• Competing on tactics

Where this leads:

• AI learns from your content (it’s training data)
• AI never cites you (you’re not structured as authority)
• You remain dependent on platforms
• Commoditization continues
• In 3 years, AI does what you do—for $20/month

Option 2: Start optimizing for authority

Different game entirely:

• Create frameworks (original IP)
• Conduct research (proprietary data)
• Coin terminology (ownable concepts)
• Document everything with schema markup
• Build entity recognition
• Focus on citations over clicks

Where this leads:

• AI cites you as THE source
• Past work compounds
• Platform independence
• Defensible differentiation
• In 3 years, you’re THE authority AI references—while competitors are commoditized

The Practical Questions You’re Probably Asking

“But I need traffic NOW for business…”

Fair. Here’s the thing: you can optimize for both.

Write the comprehensive framework documentation (authority). Create supporting blog posts that drive traffic to it (traffic).

The framework gets cited by AI. The blog posts drive some near-term traffic.

But the framework is what builds permanent value.

“How do I know if I’m being cited?”

Test it:

• Ask ChatGPT questions in your domain
• Ask Claude the same questions
• Try Perplexity
• Search Google (AI Overviews appearing?)

Are you being cited?

If not, why not? (Schema markup? Entity recognition? Original IP?)

“What if my domain is crowded?”

Then narrow until you can be THE authority.

“Marketing expert” → too broad, unciteable “Email marketing expert” → still too broad “Email deliverability for enterprise SaaS” → narrow enough to own

Own the narrow territory completely. Let authority cascade to adjacent domains later.

“Can I afford to ignore traffic?”

You can’t afford to ONLY chase traffic.

Because AI is training on your content right now.

And in 12-24 months, most searches in your domain will be answered by AI.

If you’re not the cited source, you’re invisible.

The Uncomfortable Timeline

Let me be direct about what’s coming:

2025-2026: AI capabilities expand rapidly. Zero-click becomes 70%+ of searches. Generic expertise further commoditized. Authority gap widens dramatically.

2027-2028: AI exceeds human expertise in most domains. Generic knowledge work automated. Only differentiated experts remain valuable.

2029-2030: New equilibrium. AI handles most execution. Human value concentrated in: original IP, will, judgment, relationships.

This is not science fiction. This is pattern recognition.

The question isn’t whether this happens.

The question is: Are you building authority NOW, while you still have a runway?

Or are you optimizing traffic tactics that will be obsolete in 18 months?

What To Do Monday Morning

Stop publishing content for content’s sake.

Ask instead:

• “Does this create citeable IP?”
• “Can AI replicate this from public information?”
• “Am I building authority or renting attention?”

If it doesn’t build authority, question why you’re creating it.

Start here:

1. Implement Person schema markup on your website (tell machines who you are)
2. Document one framework from your tacit knowledge (create original IP)
3. Plan one research project (generate proprietary data)
4. Audit existing content (can any be restructured as frameworks?)
5. Test AI citations (see if you’re being cited now)

These aren’t nice-to-haves.

These are the fundamentals of survival in an AI-dominated information economy.

The Choice

Every piece of content you create from this moment forward is training AI.

You’re either training it to cite you.

Or training it to replace you.

AI doesn’t want your traffic.

Your traffic was always just a proxy—a temporary way to measure attention and capture leads.

AI wants your brain.

Your frameworks. Your research. Your synthesis. Your original thinking.

The question is: Are you giving it away as free training data?

Or are you structuring it as citeable authority that positions you as THE source?

The marketing game changed.

Most people haven’t noticed yet.

That’s your window.

The Complete Roadmap

Everything in this post—entity recognition, framework development, research execution, semantic structure, citation building—is documented in complete detail in “No-Click Content Strategy: How to Build Unshakeable Authority When AI Can Copy Everything But You.”

The book includes:

• How to extract frameworks from your tacit knowledge (Chapter 7)
• How to conduct research that gets cited for years (Chapter 8)
• Complete technical implementation of schema markup (Chapter 11)
• The Authority Flywheel and compound mechanics (Chapter 16)
• 12-month implementation roadmap (Appendix E)
• Real case studies of 3-10x business transformation through authority

This isn’t theory. This is the exact playbook for building defensible authority in the age of AI commoditization.

Available now at Amazon

Or keep chasing traffic while AI trains on your content.

Your move.