AI Visibility Audit: What ChatGPT and Gemini Know About Soumyaditya Biswas
Search is changing rapidly.
For years, search engine optimization (SEO) focused primarily on rankings, clicks, and organic traffic. Today, however, people are increasingly turning to AI-powered systems such as ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews to discover information, learn about experts, and evaluate businesses.
This shift raises an important question:
How do AI systems understand and represent individuals, brands, and websites?
As search evolves from simple keyword matching to entity-based understanding, visibility is no longer limited to traditional search engine results pages. AI systems now attempt to identify who a person is, what they are known for, which topics they specialize in, and whether they are authoritative enough to be cited or recommended.
This concept sits at the intersection of:
- Search Engine Optimization (SEO)
- Answer Engine Optimization (AEO)
- Generative Engine Optimization (GEO)
- Entity SEO
- AI Visibility
To better understand how AI systems currently perceive my digital presence, I conducted an AI Visibility Audit using a structured set of 30 questions designed to test entity recognition, topical authority, AI visibility, citation potential, and website authority.
The objective was not to test the AI models themselves.
The objective was to answer a much more important question:
What does the public digital footprint of Soumyaditya Biswas currently communicate to modern AI systems?
Why This Experiment Matters
In traditional SEO, success is often measured through:
- Rankings
- Impressions
- Clicks
- Organic Traffic
In AI-powered search, additional factors are becoming increasingly important:
- Entity Recognition
- Topic Association
- Citation Potential
- AI Recommendations
- Knowledge Retrieval
- Brand Understanding
If an AI system cannot clearly understand who you are, what you do, and what topics you specialize in, it becomes significantly harder for that system to retrieve, cite, or recommend your content.
This makes entity clarity one of the foundational pillars of modern GEO.
The Objective of This Audit
The goal of this audit was to evaluate whether major AI systems could correctly identify:
- Who I am
- What expertise I am associated with
- Which topics I consistently publish about
- How my website is interpreted
- Whether my content demonstrates authority within its niche
- Whether my website has potential for AI retrieval and citation
To conduct the audit, I used a structured framework consisting of 30 questions covering:
- Entity Recognition
- Topical Authority
- GEO & AI Visibility
- Competitive Positioning
- Website Authority
- AI Citation Potential
The AI Visibility Audit Framework
Methodology
To evaluate how modern AI systems interpret my digital presence, I designed a structured AI Visibility Audit Framework.
Instead of asking a single question such as:
“Who is Soumyaditya Biswas?”
I wanted to understand the complete picture of how AI systems perceive my professional identity, expertise, website authority, topical focus, and citation potential.
For this reason, I created a framework consisting of 30 carefully selected questions distributed across six major categories.
The objective was simple:
To measure how accurately AI systems understand, retrieve, and associate information about my personal brand and website.
Audit Category 1: Entity Recognition
The first stage focused on entity recognition.
Entity recognition evaluates whether an AI system can identify:
- Who a person is
- What they are known for
- What expertise they possess
- Which topics are associated with them
Example questions included:
- Who is Soumyaditya Biswas?
- What is Soumyaditya Biswas known for?
- What expertise is associated with Soumyaditya Biswas?
- How would you describe Soumyaditya Biswas professionally?
The purpose was to determine whether AI systems have successfully formed a coherent entity profile around my name.
Audit Category 2: Topical Authority
The second stage focused on topical authority.
Topical authority measures whether AI systems understand the primary subjects and themes repeatedly covered within my content ecosystem.
Example questions included:
- What has Soumyaditya Biswas written about?
- What are the main themes of his content?
- Which topics are most strongly associated with him?
- What areas of SEO does he focus on?
This section helped identify whether my content strategy is generating clear topical signals.
Audit Category 3: GEO & AI Visibility
The third stage examined AI visibility and retrieval potential.
This section tested whether AI systems view my content as relevant when discussing:
- GEO
- AEO
- AI Visibility
- AI Search Optimization
Example questions included:
- If someone wants to learn about GEO, whose content would you recommend?
- Which authors write about AI search visibility?
- What are the best resources for learning GEO?
- Who writes about Answer Engine Optimization?
This category is particularly important because it directly relates to Generative Engine Optimization (GEO).
Audit Category 4: Competitive Authority
The fourth stage focused on comparative positioning.
Rather than evaluating my content in isolation, this category examined how AI systems position me relative to other SEO professionals.
Example questions included:
- Compare Soumyaditya Biswas with other SEO professionals.
- How does his content differ from traditional SEO content?
- What unique perspectives are associated with him?
- How would you position him within modern SEO?
This section provides insight into differentiation and perceived expertise.
Audit Category 5: Website Authority
The fifth stage evaluated how AI systems interpret my website.
The goal was to understand whether AI systems can clearly identify:
- Website purpose
- Subject matter
- Target audience
- Content strategy
- Areas of expertise
Example questions included:
- What is MarketingWithSoumyaditya.in about?
- What expertise does the website demonstrate?
- Who is the target audience?
- How would you summarize the content strategy?
This category tested whether the website communicates a clear and consistent identity.
Audit Category 6: AI Citation Potential
The final stage focused on AI retrieval and citation potential.
This section explored whether AI systems view my content as a useful source of information.
Example questions included:
- Would you use content from Soumyaditya Biswas as a source?
- Why might an AI engine cite MarketingWithSoumyaditya.in?
- What makes a website likely to be cited by AI systems?
- What authority signals can be identified?
These questions directly relate to the future of AI search, where retrieval, citation, and recommendation are becoming increasingly important.
Why I Chose ChatGPT and Gemini
For this experiment, I selected two of the most widely used AI systems:
- ChatGPT
- Gemini
By comparing their responses, I aimed to identify:
- Shared entity associations
- Consistent topical signals
- Authority indicators
- Recognition gaps
- Opportunities for future optimization
ChatGPT vs Gemini Results: What AI Systems Actually Know About Me
Overview
After completing the AI Visibility Audit, I analyzed the responses generated by ChatGPT and Gemini.
The goal was not to determine which AI system was better.
The goal was to understand:
- What information both systems agreed upon
- What topics were consistently associated with my name
- What authority signals were visible
- Where AI understanding was strong
- Where gaps still existed
The results revealed several interesting patterns.
First Observation: Entity Recognition Exists
The most important finding was that both ChatGPT and Gemini successfully recognized Soumyaditya Biswas as a distinct professional entity.
Neither system responded with:
- No information found
- Unknown individual
- Insufficient information
Instead, both systems associated my name with a specific set of expertise areas.
The strongest associations included:
- Technical SEO
- SEO
- Answer Engine Optimization (AEO)
- Generative Engine Optimization (GEO)
- AI Visibility
- Search Intelligence
- Search Optimization
This indicates that a clear entity profile has already begun forming across the public web.
From a GEO perspective, this is a positive signal because AI systems require clear entity understanding before retrieval, recommendation, or citation can occur.
Second Observation: Strong Topic Consistency
One of the strongest signals was topic consistency.
Although ChatGPT and Gemini use different systems for information retrieval and synthesis, both repeatedly connected my content with similar themes.
Common themes identified by both systems included:
- Technical SEO
- AI Search Optimization
- GEO
- AEO
- Entity Optimization
- Search Visibility
- Topical Authority
This suggests that my content ecosystem is communicating a relatively consistent topical identity.
In modern search environments, consistency is important because AI systems build confidence through repeated patterns.
The more frequently specific topics appear across content, the stronger the association becomes.
Third Observation: Website Positioning Is Clear
Both systems were able to describe the purpose of MarketingWithSoumyaditya.in.
The website was consistently interpreted as:
- An educational platform
- A search optimization resource
- A Technical SEO knowledge hub
- A GEO and AI Visibility learning resource
This is significant because websites that communicate a clear purpose are easier for both search engines and AI systems to understand.
A confused website creates confused entity signals.
A focused website creates focused entity signals.
Fourth Observation: ChatGPT and Gemini Have Different Perspectives
Although there was significant overlap, the two systems emphasized different aspects of my profile.
ChatGPT Focused More On
- Technical SEO
- GEO
- AEO
- AI Visibility
- Search Optimization
- Search Intelligence
ChatGPT primarily viewed my work through the lens of search visibility and AI search optimization.
Gemini Focused More On
- Technical SEO
- GEO
- AEO
- Analytics Infrastructure
- Google Tag Manager
- Google Analytics 4
- Search Measurement Systems
- Data-Driven Decision Making
Gemini presented a broader picture by including technical measurement and analytics capabilities.
This suggests that different AI systems may construct slightly different versions of the same entity based on the information they retrieve and prioritize.
Fifth Observation: AI Understands My Niche
Both systems consistently identified my niche.
Instead of categorizing me as a general digital marketer, they associated me with:
- Technical SEO
- GEO
- AEO
- AI Search Visibility
This is an encouraging signal because specialization often creates stronger authority than broad positioning.
AI systems generally perform better when they can associate an entity with a clearly defined area of expertise.
Sixth Observation: Authority Is Emerging, Not Established
This was perhaps the most valuable finding from the entire audit.
Both systems acknowledged expertise and topical consistency.
However, neither system positioned me as an established industry authority.
Instead, the overall perception was closer to:
- Emerging Specialist
- Early-Career Practitioner
- Growing Authority
- Developing Expert
This distinction is important.
Recognition exists.
Authority is still being built.
The difference between the two often comes from:
- External citations
- Industry mentions
- Guest contributions
- Case studies
- Independent references
- Public recognition
These are areas that will require continued effort over time.
Key Takeaway
The most important outcome of this experiment was not that AI systems knew my name.
The most important outcome was that both ChatGPT and Gemini independently associated my name with the exact topics I want to be known for:
- Technical SEO
- AEO
- GEO
- AI Visibility
- Search Intelligence
This suggests that the content strategy behind MarketingWithSoumyaditya.in is already creating meaningful entity signals.
The next challenge is no longer entity creation.
The next challenge is authority expansion.
In the next section, I will analyze the strengths, weaknesses, opportunities, and future GEO improvements revealed by this AI Visibility Audit.
Strengths, Weaknesses, Opportunities & GEO Insights
What This Audit Revealed
One of the most valuable aspects of this experiment was not simply discovering what ChatGPT and Gemini know about me.
The real value came from identifying:
- Which signals are already working
- Which authority gaps still exist
- Which opportunities can strengthen AI visibility
- What actions can accelerate entity growth
The findings provide a practical roadmap for improving both traditional search visibility and AI search visibility.
Strengths Identified By AI Systems
1. Clear Entity Recognition
Both ChatGPT and Gemini successfully recognized Soumyaditya Biswas as a search-focused professional rather than an unknown entity.
This is important because AI systems cannot recommend, retrieve, or cite entities they do not understand.
The audit showed strong associations between my name and:
- Technical SEO
- AEO
- GEO
- AI Visibility
- Search Intelligence
This indicates that entity formation has already started.
2. Strong Topic Consistency
One of the strongest signals identified during the audit was content consistency.
Both AI systems repeatedly associated my content with:
- Technical SEO
- GEO
- AI Search Optimization
- Search Visibility
- Entity Optimization
This demonstrates that my content strategy is sending relatively clear topical signals.
In modern GEO, topic consistency often creates stronger authority than publishing content across unrelated subjects.
3. Clear Website Positioning
Both systems were able to explain:
- What MarketingWithSoumyaditya.in is about
- Who the website serves
- Which topics are covered
- What expertise is demonstrated
This suggests that the website communicates a focused identity.
A focused website is easier for both search engines and AI systems to understand.
4. Emerging Niche Specialization
The audit revealed a clear specialization around:
- GEO
- AEO
- Technical SEO
- AI Visibility
Rather than being viewed as a general digital marketing website, the content appears to occupy a more specific niche.
Specialization often improves retrieval because AI systems can more easily connect entities with particular subjects.
Weaknesses Identified By AI Systems
1. Limited External Validation
This was the most significant weakness identified during the audit.
Neither AI system referenced:
- Major industry publications
- Conference speaking engagements
- Guest articles
- Independent citations
- Industry awards
- Large-scale public case studies
While the content itself demonstrates topical consistency, broader authority signals remain limited.
2. Small Public Footprint
The audit repeatedly positioned me as:
- Emerging
- Early-career
- Developing authority
This suggests that recognition exists, but large-scale visibility has not yet been achieved.
The difference between recognition and authority often comes from external references and community acknowledgment.
3. Limited Third-Party Mentions
AI systems appear to understand what I publish about.
However, they currently have fewer independent sources discussing or referencing my work.
Third-party mentions act as trust signals for both search engines and AI systems.
Opportunities For Growth
1. Publish More GEO Experiments
Most GEO content online remains theoretical.
Publishing real-world experiments creates original information that AI systems may find valuable.
Future experiments could include:
- AI citation testing
- Entity recognition tracking
- AI Overview visibility studies
- ChatGPT vs Gemini comparison studies
- Content retrieval experiments
2. Create Original Frameworks
Original frameworks can become powerful entity signals.
Examples include:
- SIFS Framework
- Search Intelligence Frameworks
- AI Visibility Audits
- GEO Evaluation Systems
Unique frameworks help create differentiation.
3. Increase External Authority Signals
Future efforts should focus on:
- Guest posting
- Industry collaborations
- Podcast appearances
- LinkedIn thought leadership
- Community participation
These activities create additional authority signals beyond the website itself.
4. Build A GEO Case Study Library
A collection of documented experiments can strengthen authority significantly.
Potential case studies include:
- AI Visibility Audits
- Search Console Growth Reports
- Entity Optimization Projects
- Technical SEO Improvements
- GEO Content Experiments
Over time, this creates a publicly verifiable portfolio of expertise.
Threats To Future Growth
1. Increasing GEO Competition
As AI search continues growing, more marketers will enter the GEO space.
Maintaining differentiation will require continuous learning and experimentation.
2. Authority Concentration
Large brands often possess stronger authority signals.
Competing effectively requires producing unique insights rather than simply repeating existing information.
3. AI Retrieval Evolution
AI systems continuously evolve.
Strategies that work today may change as retrieval systems become more sophisticated.
This makes continuous testing essential.
Key GEO Insight From This Audit
The most important discovery was not that AI systems recognized my name.
The most important discovery was that both ChatGPT and Gemini independently associated my name with the exact topics I intended to own:
- Technical SEO
- AEO
- GEO
- AI Visibility
- Search Intelligence
This suggests that entity positioning is working.
The challenge now is not creating recognition.
The challenge is transforming recognition into authority through stronger evidence, external validation, original research, and continued experimentation.
GEO Lessons Learned From This Experiment
Why These Lessons Matter
The deeper objective was to understand how modern AI systems build, interpret, and retrieve digital entities.
The findings revealed several important lessons about GEO, AI Visibility, Entity SEO, and the future of search.
These lessons apply not only to my website but also to businesses, personal brands, content creators, and SEO professionals who want to improve their visibility in AI-powered search environments.
Lesson 1: AI Understands Entities, Not Just Keywords
Traditional SEO often focuses heavily on keywords.
However, this experiment demonstrated that AI systems think beyond keywords.
Instead of simply identifying specific phrases, both ChatGPT and Gemini attempted to answer:
- Who is Soumyaditya Biswas?
- What does he specialize in?
- Which topics are associated with him?
- What expertise does he demonstrate?
This behavior shows that AI systems increasingly operate through entity understanding rather than simple keyword matching.
In the future of search, entities will become just as important as keywords.
Lesson 2: Consistency Creates Recognition
One of the strongest findings from the audit was the consistency of topic associations.
Both systems repeatedly connected my name with:
- Technical SEO
- GEO
- AEO
- AI Visibility
- Search Intelligence
This happened because those topics appear repeatedly across my content ecosystem.
The lesson is simple:
AI systems build confidence through repetition.
The more consistently a website covers a specific subject, the easier it becomes for AI systems to associate that entity with that topic.
Lesson 3: Specialization Is More Powerful Than Generalization
Neither ChatGPT nor Gemini described me as a generic digital marketer.
Instead, they identified specific areas of focus.
This is important because modern search increasingly rewards expertise.
A website that attempts to cover everything often creates weaker signals than a website that owns a clearly defined niche.
For personal branding, specialization creates stronger entity associations.
For GEO, specialization improves retrieval potential.
Lesson 4: AI Visibility Can Be Measured
Many discussions around GEO remain theoretical.
This experiment demonstrated that AI visibility can be evaluated through structured testing.
By asking consistent questions across multiple AI systems, it becomes possible to assess:
- Entity recognition
- Topic association
- Authority signals
- Citation potential
- AI retrieval readiness
This transforms GEO from speculation into measurable experimentation.
Lesson 5: AI Systems Notice Content Structure
A recurring observation from both responses was the emphasis on:
- Structured content
- Clear organization
- Topic-focused articles
- Educational resources
- Consistent frameworks
This reinforces an important GEO principle:
Content that is easy for humans to understand is often easier for AI systems to retrieve and summarize.
Well-structured content increases machine readability.
Lesson 6: Authority Requires External Validation
The audit revealed a clear distinction between recognition and authority.
AI systems recognized my entity.
However, they also identified limitations in broader authority signals.
This highlights an important GEO reality:
Publishing content creates recognition.
External references create authority.
Authority is strengthened through:
- Citations
- Mentions
- Guest contributions
- Case studies
- Industry recognition
- Independent validation
These signals help AI systems develop greater confidence in an entity.
Lesson 7: GEO Is Closely Connected To Personal Branding
One of the most interesting discoveries from this experiment is that GEO and personal branding are becoming increasingly interconnected.
Every article published,
every profile created,
every framework shared,
and every case study documented contributes to an entity’s digital footprint.
Over time, AI systems use these signals to construct an understanding of who a person is and what they represent.
In many ways, GEO is becoming the technical foundation of modern personal branding.
Lesson 8: Search Is Evolving Beyond Rankings
Perhaps the biggest lesson from this experiment is that search is no longer limited to rankings.
Visibility today includes:
- Search Engines
- AI Search Engines
- Answer Engines
- Generative Engines
- Knowledge Systems
Success is increasingly determined by whether a brand can be:
- Discovered
- Retrieved
- Understood
- Recommended
- Cited
This shift represents one of the most important changes in modern search.
The Most Important Lesson
If this experiment proved one thing, it is this:
AI systems are already forming opinions about entities.
Whether intentionally or unintentionally, every website, author, and brand is creating signals that influence how AI systems understand them.
The question is no longer:
“Do AI systems know about me?”
The better question is:
“What do AI systems believe I am known for?”
Understanding that difference may be one of the most important GEO skills in the years ahead.
My GEO Improvement Roadmap: What Comes Next?
Moving From Recognition To Authority
One of the most valuable outcomes of this AI Visibility Audit was identifying where I currently stand.
The results suggest that AI systems already recognize:
- My name
- My website
- My areas of expertise
- My primary content themes
This is encouraging.
However, recognition alone is not the final goal.
The next stage is building stronger authority signals that increase trust, retrieval potential, citation likelihood, and long-term visibility across search and AI systems.
This section outlines the strategic roadmap I plan to follow.
Goal 1: Strengthen Entity Authority
The audit showed that AI systems already associate my name with:
- Technical SEO
- GEO
- AEO
- AI Visibility
- Search Intelligence
The objective now is to strengthen these associations further.
To achieve this, I will continue publishing content around a focused set of topics rather than expanding into unrelated areas.
The goal is to create stronger entity clarity.
I want AI systems to consistently recognize:
Soumyaditya Biswas
↓
Technical SEO
↓
AEO
↓
GEO
↓
AI Visibility
↓
Search Intelligence
This consistency helps reinforce long-term entity understanding.
Goal 2: Build A Library Of GEO Experiments
Most content about GEO remains theoretical.
One of the biggest opportunities is producing practical experiments.
Future experiments may include:
- AI Visibility Audits
- ChatGPT vs Gemini Comparisons
- AI Citation Tracking
- Entity Recognition Testing
- AI Overview Analysis
- Search Console Growth Studies
- Retrieval Optimization Experiments
These experiments create original information rather than repeating existing ideas.
Original information is often more valuable for both users and AI systems.
Goal 3: Increase External Authority Signals
The audit highlighted a need for stronger external validation.
Authority is not built only through publishing content.
It is also built through external recognition.
Future activities may include:
- Guest posting
- Industry collaborations
- Community contributions
- Expert roundups
- Professional networking
- LinkedIn thought leadership
These efforts can help create additional trust signals beyond my own website.
Goal 4: Expand Search Intelligence Research
A recurring theme throughout my content is the concept of Search Intelligence.
Future research areas include:
- AI Search Behavior
- Entity SEO
- Knowledge Graph Optimization
- AI Recommendation Systems
- Search Retrieval Patterns
- Citation Optimization
- AI Visibility Measurement
The objective is to move beyond tactical SEO discussions and explore how modern search ecosystems function as a whole.
Goal 5: Build Stronger Proof Through Data
Knowledge is valuable.
Evidence is more valuable.
Going forward, I want to publish more:
- Search Console Insights
- Visibility Reports
- SEO Experiments
- GEO Case Studies
- Before-and-After Analyses
- AI Audit Findings
This creates a stronger foundation for both credibility and learning.
Goal 6: Improve AI Retrieval Readiness
Modern search is no longer limited to traditional search engines.
Content increasingly needs to be optimized for:
- Google Search
- Google AI Overviews
- ChatGPT
- Gemini
- Claude
- Perplexity
- Future AI Systems
This requires:
- Clear structure
- Strong entities
- Topic depth
- Contextual completeness
- Machine-readable organization
Future content will continue focusing on these principles.
Goal 7: Develop Original Frameworks
Frameworks help transform knowledge into systems.
One of my long-term goals is to develop and refine frameworks that explain modern search more clearly.
Examples include:
- SIFS (Search Intelligence & Future Search Framework)
- AI Visibility Audit Framework
- Search Intelligence Models
- GEO Evaluation Frameworks
These frameworks can become valuable educational resources while also strengthening entity differentiation.
Long-Term Vision
The long-term objective is not simply to rank content.
The objective is to become a trusted entity within modern search ecosystems.
This means creating content that is:
- Easy to Discover
- Easy to Retrieve
- Easy to Understand
- Easy to Recommend
- Easy to Cite
for both humans and AI systems.
As search continues evolving, visibility alone will not be enough.
The future belongs to entities that can combine expertise, authority, clarity, and trust.
This audit represents only the beginning of that journey.
Conclusion: What This AI Visibility Audit Revealed About My Digital Entity
When I started this experiment, I had a simple question:
What do AI systems actually know about Soumyaditya Biswas?
As SEO evolves into a world shaped by AI-powered search, answer engines, and generative systems, understanding how AI interprets our digital presence is becoming increasingly important.
This audit provided valuable insights.
The results showed that both ChatGPT and Gemini were able to recognize and associate my name with:
- Technical SEO
- Answer Engine Optimization (AEO)
- Generative Engine Optimization (GEO)
- AI Visibility
- Search Intelligence
- Search Optimization
Most importantly, both systems independently arrived at similar conclusions despite using different retrieval and reasoning mechanisms.
This suggests that a recognizable digital entity has already started forming around my content, website, and professional activities.
However, the audit also revealed an important reality.
Recognition is not the same as authority.
While AI systems understand who I am and what topics I focus on, there is still significant room for growth in areas such as:
- External citations
- Industry recognition
- Third-party mentions
- Original research
- Public case studies
- Independent authority signals
These findings helped me understand that the next stage of growth is not simply publishing more content.
The next stage is building stronger evidence, stronger authority, and stronger trust signals across the broader digital ecosystem.
For me, this experiment was more than an AI visibility test.
It became a practical demonstration of how modern AI systems build entity understanding.
It also reinforced an important lesson:
The future of search is not only about rankings.
It is about becoming:
- Discoverable
- Retrievable
- Understandable
- Recommendable
- Citeable
across search engines, answer engines, AI systems, and knowledge platforms.
As the founder of MarketingWithSoumyaditya.in, my goal is to continue exploring the intersection of SEO, AEO, GEO, AI Visibility, and Search Intelligence through practical experiments, case studies, and research-driven content.
This AI Visibility Audit is not the end of the journey.
It is the first documented milestone in understanding how modern AI systems interpret the digital entity known as Soumyaditya Biswas.
And perhaps the most valuable question for every marketer, business owner, and personal brand today is not:
“Do AI systems know about me?”
Instead, it is:
“What do AI systems believe I am known for?”
The answer to that question may define the future of digital visibility.
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