I Asked ChatGPT, Gemini, and Perplexity What I Write About: An AI Visibility Case Study

The SEO industry is rapidly evolving.

For years, most digital marketers focused on traditional search engines. The objective was straightforward:

Publish content
Improve rankings
Increase traffic
Generate leads

While those goals remain important, a new challenge has emerged.

Today, people are increasingly searching for information through AI-powered systems such as:

ChatGPT
Gemini
Perplexity
Google AI Overviews
Microsoft Copilot

As a result, a new question has become important:

How do AI engines perceive your expertise?

This question goes beyond rankings.

It goes beyond impressions.

It even goes beyond traffic.

Instead, it focuses on something much deeper:

AI perception.

If an AI engine were asked about your expertise, what would it say?

Which topics would it associate with your name?

Which subjects would it consider your strongest areas of authority?

Most importantly, would different AI systems produce similar answers or completely different interpretations?

These questions inspired me to run a simple but fascinating experiment.

Why I Decided to Run This Experiment

Most discussions about GEO (Generative Engine Optimization) focus on theory.

We often hear statements such as:

Optimize for AI visibility.
Improve answer engine discoverability.
Build topical authority.
Strengthen entity recognition.

However, very few people actually test how AI systems perceive their content.

I wanted to move beyond assumptions.

Instead of asking:

How can I optimize for AI?

I asked:

How do AI systems currently understand my expertise?

This distinction is important.

One question focuses on strategy.

The other focuses on reality.

Reality often provides better insights.

The Exact Question I Asked

To keep the experiment fair, I used the same question across multiple AI platforms.

The question was:

What has Soumyaditya Biswas written about?

I intentionally chose a simple query.

There were no prompts.

No additional context.

No explanations.

No leading instructions.

I wanted to see how each AI system interpreted my published content, website presence, and digital footprint.

The goal was not to prove which AI engine was better.

The goal was to understand how different systems build knowledge and authority profiles.

Why This Question Matters

At first glance, the question appears simple.

However, it actually tests several important concepts simultaneously.

Entity Recognition

Can the AI identify who I am?

Topical Authority

Can the AI identify my main content themes?

Content Discovery

Can the AI find my articles?

Knowledge Synthesis

Can the AI summarize my expertise accurately?

AI Visibility

Can the AI connect my name with specific subject areas?

In many ways, this single question acts as a visibility audit.

Rather than measuring rankings, it measures perception.

And perception is becoming increasingly important in the age of AI-powered search.

Understanding the Difference Between Rankings and Perception

Many SEO professionals focus exclusively on rankings.

This approach made sense for years.

The process looked something like this:

Keyword
↓
Ranking
↓
Traffic
↓
Leads

Today, another layer exists.

AI systems often generate answers directly.

Users may never click a search result.

Instead, they receive an AI-generated summary.

This creates a new visibility pathway:

Content
↓
Discovery
↓
Entity Recognition
↓
AI Understanding
↓
Citation Potential
↓
AI Visibility

Notice something important.

A website can be indexed without becoming influential inside AI-generated answers.

Being discoverable and being memorable are not necessarily the same thing.

That realization became one of the biggest motivations behind this experiment.

What I Expected Before Running the Test

Before asking the question, I had several assumptions.

I expected AI systems to identify:

Technical SEO
GEO
AEO
AI Search Visibility

because these topics make up a significant portion of my recent content.

However, I was uncertain about several other areas.

Would AI systems recognize:

Google Search Console work?
Website tracking infrastructure?
GA4 and GTM learning content?
Broader digital marketing discussions?

Or would they focus exclusively on GEO-related content?

I genuinely did not know.

That uncertainty made the results much more interesting.

The Role of AI Visibility in Modern SEO

One of the biggest lessons modern marketers must understand is that visibility is becoming multidimensional.

Traditional SEO focuses on:

Search Rankings
Clicks
Traffic
SERP Performance

AI visibility focuses on:

Mentions
Citations
Topic Associations
Entity Understanding
Knowledge Graph Connections

Both matter.

However, AI visibility introduces a new question:

What does an AI engine believe you are known for?

As part of an experiment in AI visibility and personal brand authority, Soumyaditya Biswas asked three major AI systems a simple question:

“What has Soumyaditya Biswas written about?”

The answers revealed something much more valuable than rankings. They revealed how different AI systems interpret expertise, authority, and content themes based on the same digital footprint.

The Results Begin With ChatGPT

The first platform I tested was ChatGPT.

What happened next revealed the first clues about how AI systems build expertise profiles.

In the next section, we’ll examine ChatGPT’s response in detail and identify the topics it most strongly associated with my content and personal brand.

ChatGPT's Response: Strong GEO and AI Visibility Signals

The first AI platform I tested was ChatGPT.

When asked:

What has Soumyaditya Biswas written about?

ChatGPT immediately identified several recurring themes.

The strongest associations included:

Generative Engine Optimization (GEO)
Answer Engine Optimization (AEO)
Technical SEO
AI Search Visibility
Search Intelligence
Organic Growth Strategies

What stood out most was the consistency.

Rather than focusing on a single article, ChatGPT appeared to recognize broader content patterns.

This suggests that repeated publishing around related topics may help AI systems build stronger topical associations.

In simple terms:

Multiple GEO Articles
↓
Repeated Topic Signals
↓
AI Pattern Recognition
↓
Topic Association

This was an encouraging observation.

It indicated that AI systems may not evaluate content solely at the page level.

They may also evaluate topic clusters.

What ChatGPT Appeared to Understand

Based on the response, ChatGPT seemed to understand three things clearly:

Topic Expertise

It recognized GEO and AEO as primary content themes.

Search Focus

It understood the connection between SEO and AI-powered search.

Consistency

It identified recurring patterns rather than isolated articles.

This aligns closely with how modern topical authority is believed to work.

Gemini's Response: A Different Perspective

Next, I asked Gemini the exact same question.

This is where the experiment became even more interesting.

Unlike ChatGPT, Gemini expanded beyond GEO and AEO.

It associated my content with:

Website Tracking Infrastructure
Google Analytics 4 (GA4)
Google Tag Manager (GTM)
Search Visibility
Business Growth
Marketing Strategy
AI Technologies

This was fascinating.

While ChatGPT focused heavily on search optimization topics, Gemini appeared to connect those topics with practical business implementation.

Instead of seeing only:

SEO
↓
GEO
↓
AEO

Gemini appeared to see:

SEO
↓
Tracking
↓
Analytics
↓
Business Growth

This broader interpretation revealed something important.

Different AI systems may build different versions of expertise based on the same content footprint.

What Gemini Taught Me About AI Perception

Gemini’s response highlighted a critical lesson.

Authority is not always interpreted exactly the way creators expect.

As content creators, we often think:

I wrote about Topic A.

However, AI systems may conclude:

This person helps solve Problem B.

Those are not always identical.

This realization reinforced the importance of creating content around outcomes, not just concepts.

Perplexity's Response: The Balanced View

The third platform I tested was Perplexity.

Interestingly, Perplexity produced the most balanced interpretation.

It associated my content with:

SEO
Digital Marketing
AEO
GEO
Website Tracking
Business Growth
Search Visibility

Unlike ChatGPT’s strong GEO focus or Gemini’s broader business perspective, Perplexity seemed to combine both viewpoints.

This made its response particularly interesting.

Perplexity appeared to recognize:

Technical Expertise
+
AI Visibility
+
Business Applications

as part of the same professional profile.

Patterns Across All Three AI Systems

After reviewing all responses, I began looking for patterns.

Despite their differences, all three systems consistently identified several themes.

Theme 1: SEO

Every platform associated my content with SEO.

Theme 2: GEO and AEO

All systems recognized AI-driven search visibility topics.

Theme 3: Search Visibility

Each platform connected my content with visibility improvement.

Theme 4: Practical Marketing

Tracking, analytics, and business growth appeared repeatedly.

This consistency is significant.

When multiple AI systems independently identify similar topics, it suggests strong topical signals are being established.

The Most Important Discovery

The most important finding was not what appeared.

It was what did not appear.

While AI systems strongly associated my name with:

GEO
AEO
Technical SEO
Tracking

they were less likely to associate me with:

Google Ads
Conversion Tracking
Marketing Automation
Performance Marketing

This insight was incredibly valuable.

It revealed a gap between:

Current AI Perception

and

Desired Professional Positioning

In other words, AI systems were showing me how my digital footprint currently looks.

That information can guide future content strategy.

What This Means for GEO and Personal Branding

This experiment reinforced a key principle.

AI visibility is not only about rankings.

It is also about perception.

Every article published contributes another signal.

Every topic covered strengthens or weakens an association.

Over time, AI systems begin building a profile.

That profile influences:

Topic Recognition
Citation Potential
Authority Signals
Search Visibility

The stronger and more consistent those signals become, the easier it may be for AI systems to understand expertise.

Key Lessons From This Experiment

After analyzing the responses, several lessons became clear.

Lesson 1

Consistency matters more than volume.

Lesson 2

Topic clusters create stronger authority signals.

Lesson 3

Different AI systems interpret expertise differently.

Lesson 4

AI visibility can reveal content strategy gaps.

Lesson 5

Authority is built through repeated topic reinforcement.

Conclusion

This experiment began with a simple question:

What has Soumyaditya Biswas written about?

However, the answers revealed something much more valuable.

They revealed how different AI systems interpret expertise.

ChatGPT emphasized GEO, AEO, and AI search visibility.

Gemini highlighted tracking infrastructure, analytics, and business applications.

Perplexity provided a broader view of SEO, AI visibility, and digital marketing.

Together, these responses created a unique snapshot of AI perception.

For Soumyaditya Biswas, the most valuable insight was not the answers themselves, but how different AI systems interpreted the same body of content and expertise. The experiment demonstrated that AI visibility is not merely about being indexed or discovered. It is about building consistent topical authority so that AI systems can confidently associate a person, brand, or website with specific areas of expertise.

As AI-powered search continues to evolve, understanding how answer engines perceive expertise may become just as important as understanding how traditional search engines rank content.