Gennadiy Vorobyov is the Co-founder & CEO of Netpeak Bulgaria, leading a team of 80+ specialists across three cities and 180+ projects. With 14+ years of experience in SEM and PPC, he has developed strategies for 2000+ projects across Europe and CEE. He is a certified Google specialist, Google Partners trainer, co-founder of Ringostat Bulgaria, and Besarabski Front. At Netpeak, he’s in charge of developing business processes and implementing marketing strategies for key and potential clients.
Beyond Google & Bing: 7 Steps to Stay Visible When AI Decides What Customers See
Gennadiy Vorobyov
Netpeak
Recap:
At Balkan eCommerce Summit 2026, Gennadiy Vorobyov explored how search visibility is rapidly evolving from traditional SEO toward what he described as “GEO” – Generative Engine Optimization. The lecture focused on how brands can remain visible in an era where AI systems such as ChatGPT, Gemini, Perplexity, and AI Overviews increasingly decide which companies, products, and sources users see first. Rather than replacing classic SEO, the session argued that AI visibility is built on many of the same foundations: high-quality content, authority, technical optimization, and trust.
Search Is Moving from Rankings to AI Answers
The presentation opened with the idea that:
businesses no longer compete only for Google rankings.
Today, brands increasingly want to appear:
- in Chat GPT answers
- inside AI Overviews
- in Gemini responses
- and in AI-generated citations and recommendations.
According to Vorobyov:
the biggest shift is that users are no longer browsing through “10 blue links.”
Instead:
AI systems now deliver direct answers to specific questions.
This fundamentally changes how visibility works online.
GEO Is the Evolution of SEO
Vorobyov introduced the concept of:
GEO – Generative Engine Optimization.
He explained that:
GEO is not a replacement for SEO,
but rather:
the next stage of SEO adapted for AI-powered discovery.
Many of the core principles remain the same:
- good technical SEO
- structured content
- link building
- authority
- and strong user intent matching.
The lecture repeatedly emphasized that:
the fundamentals of SEO still matter in AI search environments.
AI Understands Meaning Through Intent and Context
A key part of the presentation explained how AI systems interpret language differently from traditional keyword-based search.
Vorobyov demonstrated how AI models use:
vectors, semantic relationships, and intent recognition
to distinguish between different meanings of the same word.
For example:
AI understands the difference between:
- Apple as a fruit
- and Apple as a technology company
through contextual signals and semantic relationships.
This means:
user intent has become more important than exact keywords.
The focus is shifting toward:
- informational intent
- transactional intent
- and context understanding.
AI-Friendly Content Still Follows Classic SEO Principles
One of the strongest themes of the lecture was:
AI systems still rely heavily on well-structured website content.
To appear in AI-generated results,
brands still need:
- indexable landing pages
- headings and subheadings
- proper H2/H3 structures
- bullet points
- tables
- images
- and structured schema markup.
Vorobyov stressed that:
the “ideal AI-friendly page” looks very similar to a well-optimized SEO page from years ago.
Machines still need:
- clarity
- hierarchy
- and understandable structure.
Pure AI-Generated Content Is Dangerous Without Human Editing
A major warning in the presentation concerned:
mass AI-generated content production.
Vorobyov showed examples where websites rapidly scaled AI-written articles without human involvement. Initially:
- traffic increased
- impressions grew
- and monetization improved.
However,
after several months:
traffic collapsed.
According to the lecture,
Google increasingly penalizes:
- generic
- repetitive
- and low-quality AI-generated content.
The key takeaway was:
AI-generated content works only when combined with strong human editing and expertise.
Authority Matters More Than Ever
The lecture emphasized that:
AI systems prioritize authority over simple relevance.
Being technically optimized is no longer enough.
Brands must also build:
- reputation
- expertise
- trust
- and third-party validation.
This includes:
- interviews
- podcast appearances
- PR articles
- expert commentary
- YouTube content
- and mentions on trusted websites.
Vorobyov described modern link building as:
“digital PR.”
Digital PR Helps Brands Appear in AI Results
A practical case study showed how a Bulgarian fashion brand built visibility inside AI systems through:
strategic digital PR campaigns.
The strategy included:
- publishing articles
- building backlinks
- and increasing brand mentions across trusted media sources.
As a result:
the brand started appearing:
- in AI Overviews
- and in ChatGPT recommendations.
One example prompt was:
“What are the best Bulgarian streetwear brands?”
The client brand appeared:
as the first recommendation in ChatGPT results.
The lecture used this example to demonstrate that:
classic authority-building strategies can directly influence AI visibility.
AI Systems Analyze Reviews and Brand Reputation
Another important topic was:
AI sentiment analysis.
Vorobyov explained that:
AI systems evaluate:
- reviews
- Trustpilot scores
- customer feedback
- and online reputation
when deciding whether to recommend a business.
A case study involving a German tire retailer showed that:
ChatGPT described the brand as “not recommended” due to:
- delivery complaints
- support issues
- and poor Trustpilot ratings.
This highlighted a major shift:
AI visibility is increasingly tied to brand reputation and customer trust signals.
Structured Entities Matter for AI Visibility
The lecture also covered:
entity optimization.
Vorobyov explained that:
brands should structure content differently depending on whether the page represents:
- a business
- a person
- a product
- or a category.
Structured schema and semantic clarity help AI systems better understand:
- who the entity is
- what expertise it has
- and how it should appear in search responses.
Key Takeaways
The lecture demonstrated that:
search visibility is increasingly shifting from traditional rankings to AI-generated answers
Generative Engine Optimization (GEO) is emerging as the next evolution of SEO
AI systems prioritize direct answers, mentions, and citations over classic search listings
classic SEO fundamentals still remain highly important in AI search environments
AI systems rely heavily on user intent and semantic understanding rather than exact keywords
well-structured content with headings, schema, tables, and hierarchy improves AI visibility
mass AI-generated content without human editing can eventually lead to traffic loss and penalties
authority and expertise are becoming more important than simple keyword relevance
digital PR, interviews, podcasts, and expert mentions strengthen AI visibility
AI systems increasingly analyze brand reputation, reviews, and Trustpilot signals
poor customer feedback can negatively impact how AI systems recommend brands
structured entity optimization helps AI systems better understand businesses and products
brands must combine technical SEO, authority building, reputation management, and high-quality content to remain visible in AI-driven search experiences.

