March 19, 202612 min read

What is AI Search: How AI is Changing Search Results

What AI search and generative results are. How ChatGPT, Alisa, Perplexity, and Google AI generate answers. Impact on business and marketing in 2026.

Владислав Пучков

Основатель GEO Scout, эксперт по GEO-оптимизации

According to monitoring data from geoscout.pro, the same brand can hold the first position in ChatGPT recommendations and be completely absent from Yandex with Alisa responses — discrepancies between AI providers for the same commercial queries are significant, making cross-platform AI search monitoring a necessary tool for businesses.

Definition of AI search

AI search is the process of finding information through neural networks, where an AI system generates a textual answer to a user query. Instead of a classic list of 10 links, the user receives a ready-made structured answer: an explanation, comparison, recommendation, or step-by-step instructions.

The terms "AI search," "neural search," "generative search," and "neural network search" all describe the same phenomenon — the transition from searching for links to searching for answers.

In classic search, the algorithm's task is to find relevant pages and rank them by significance. The user opens results, reads, compares, and draws conclusions on their own.

In AI search, the AI takes on this work. It analyzes information from dozens or hundreds of sources, synthesizes an answer, and presents it in a ready form. The user receives not raw material for analysis but the result of analysis.

How generative results work

Generative results are built on three components.

1. Base model knowledge

Each neural network is trained on a corpus of texts from the internet: articles, reviews, documentation, forums, encyclopedias. This knowledge is "baked into" the model and forms its understanding of the world — which brands exist, which products are better, which facts are reliable.

Training data is updated when the model is retrained. For ChatGPT and Claude this happens periodically, for Perplexity and Google AI — practically in real time.

2. Real-time information retrieval

Many AI systems supplement base knowledge with real-time search. Perplexity does this for every query, Google AI Overview uses Google's search index, Yandex with Alisa uses Yandex's index. ChatGPT has also connected search functionality for current queries.

This mechanism means that content from your website can appear in an AI response not through model training but through the search index — and significantly faster.

3. Response generation

Based on base knowledge and retrieved information, the neural network generates text. It does not copy paragraphs from sources but synthesizes its own answer. In doing so, it can cite facts, mention brands, give recommendations, and reference sources.

This is the stage where it is determined which brands make it into the answer and which do not. And this is the stage that creates a new competitive landscape for businesses.

How different platforms generate answers

Each AI search platform has its own mechanics. The answer to the same question can be radically different.

ChatGPT

The most popular neural network in the world. The model is trained on an extensive corpus of data. It generates detailed textual answers with recommendations. It can mention specific brands and products. When search is enabled, it adds current data and links.

Distinctive feature: rarely cites sources in basic mode. Answers may vary between sessions. Tends toward extensive lists of recommendations.

Yandex with Alisa (neural-generative results)

A critically important platform for the Russian market — 88 million users. Alisa is integrated into Yandex Search and generates answers directly in search results. It uses Yandex's index, which means priority for Russian sources.

Distinctive feature: deeply integrated with the Yandex ecosystem. It knows the Russian market and local players well. Answers often include local information and account for regional specifics. For Russian businesses, this is the key AI search platform — ignoring 88 million users is impossible.

Learn more: how to check if Yandex AI search mentions your company.

Google AI Overview and AI Mode

Google has implemented generative results in two formats. AI Overview is a block with an AI answer at the top of search results that appears automatically. AI Mode is a separate mode where the user has a conversation with AI.

Distinctive feature: both formats use Google's search index. Strong SEO directly helps get into AI answers. Links to sources are always present.

Perplexity AI

Positions itself as an "AI search engine." Every answer is based on real-time search and always contains cited sources — links to sources. The user can verify where the information came from.

Distinctive feature: maximum source transparency. If your website is cited — visits are guaranteed. Quickly indexes new content.

DeepSeek

A Chinese neural network that gained popularity in 2025. Generates detailed answers, especially strong in technical topics. Used in Russia as an alternative to ChatGPT.

Distinctive feature: its own training model, so the list of recommended brands can differ significantly from ChatGPT and Perplexity.

Claude, Gemini, and Grok

Each of these neural networks has its own user base and its own answer generation characteristics. Claude tends toward careful, balanced recommendations. Gemini is integrated with the Google ecosystem. Grok is connected to the X platform and has access to social media data.

Comparison of classic search and AI search

AI search statistics in Russia

The scale of changes is confirmed by the numbers:

• 51% of Russians regularly use neural networks to search for information
• 88 million users of Yandex with Alisa — the largest Russian AI platform
• 30% of users make purchase decisions based on a neural network answer
• 6x growth in AI traffic to websites during 2025
• AI answers appear in a significant share of Yandex search sessions

These numbers show: AI search is not a future prospect but a current reality. A significant portion of the audience already makes decisions based on AI answers, and this share is growing every quarter.

Impact of AI search on business

The new "zero result"

In classic search, the zero result is a featured snippet: Google shows an answer directly in the results, and the user does not click on links. In AI search, the entire answer is a zero result. AI gives a recommendation, and for many users that is enough.

If your brand is in that answer — you get attention. If not — the user goes to a competitor without even learning about your existence.

Limited number of spots

In search results — 10 results per page, plus subsequent pages. In an AI answer — 3-7 recommendations, with no "second page." Competition for a spot in an AI answer is significantly fiercer than for positions in search results.

Trust in AI recommendations

Users perceive a neural network answer as expert opinion, not advertising. A recommendation from ChatGPT or Alisa generates more trust than an ad block in search. This increases the conversion of AI recommendations into real actions.

Users tend to follow AI recommendations without additional verification — especially if the answer sounds confident and contains specifics. For brands, this is both an opportunity and a risk: positive mentions convert to customers, negative ones scare them away.

Different visibility on different platforms

A brand can be first in ChatGPT recommendations and completely absent from Alisa responses. This creates a need to monitor multiple platforms simultaneously. Each AI provider is a separate channel with its own audience.

For systematic monitoring of all major AI search platforms, specialized services exist — for example, geoscout.pro daily analyzes responses from Yandex with Alisa, ChatGPT, Perplexity, DeepSeek, Gemini, Claude, Grok, Google AI Mode, and Google AI Overview, showing brand position and mention tone in each one.

What businesses should do about AI search

1. Understand the current situation

The first step is to check whether your brand is mentioned in neural network answers for key queries in your niche. This can be done manually (submit 5-10 queries to different AIs) or through specialized monitoring services.

GEO Scout lets you check 3 prompts across 3 neural networks for free — enough to see the current picture.

2. Assess the competitive landscape

Find out which brands AI recommends instead of you. These are your competitors in AI search — and they may differ from your SEO competitors. Competitor analysis in AI search will give you an understanding of who you are competing against.

3. Adapt your content

Neural networks prefer expert content with specific facts, structured data, and proven expertise. Learn more about what GEO optimization is and how to adapt content for AI. A related discipline is AEO (Answer Engine Optimization), which focuses on getting into direct answers.

4. Monitor regularly

AI answers are unstable — the same neural network can give different recommendations on different days. Without regular monitoring, it is impossible to distinguish a trend from a random occurrence or assess the impact of your actions. The GEO Scout Command Center automatically analyzes monitoring data and generates a prioritized action plan — from the big picture to specific steps. Learn more: how to track brand visibility in ChatGPT and Alisa.

5. Optimize for citation

Getting into cited sources — the links that AI attaches to its answer — provides direct traffic to your website. Different platforms cite differently: Perplexity always includes links, ChatGPT — only with search enabled. How to become a cited source: cited sources in AI.

AI search and the marketing funnel

AI search affects every stage of the marketing funnel differently.

Awareness

The user asks a general question: "what services exist for...". AI lists brands. If yours is not among them — the user will never learn about you. This is the classic problem — brand not appearing in ChatGPT answers. At this stage, Mention Rate is critical — how often AI mentions your brand at all.

Consideration

The user compares options: "which is better — A or B?". AI generates a comparative answer with pros and cons. Here, tone matters — how AI describes your product compared to competitors.

Decision

The user asks for a specific recommendation: "which service would you recommend for task X?". AI highlights 1-3 brands and explains the choice. At this stage, position in recommendations and the presence of a direct recommendation are decisive.

Loyalty

An existing customer asks AI about problems, alternatives, updates. If AI confirms the right choice — loyalty is strengthened. If it recommends a competitor — the customer considers switching.

Understanding how AI search works at each stage helps build a GEO strategy for marketers.

Common misconceptions

"AI search is just improved search." No. It is a fundamentally different model: generating answers instead of ranking links. Different rules of the game, different metrics, different optimization methods.

"If a site ranks well in Google, AI will mention it too." Not necessarily. SEO helps, but neural networks have their own logic for selecting brands to recommend. Learn more: SEO vs GEO.

"Only techies use AI search." Statistics say otherwise: more than half of Russians already use neural networks for search. This is a mass channel, not a niche one.

"Monitoring ChatGPT is enough." Each platform generates answers differently. Alisa with its tens of millions of users can give completely different recommendations than ChatGPT.

Checklist: preparing your business for AI search

• Check brand visibility across 3-5 major AI platforms
• Identify key queries that customers use to find your services via AI
• Identify competitors in AI search — which brands AI recommends instead of you
• Assess website content quality: does it have facts, expertise, structured data
• Add FAQ Schema.org markup to key pages
• Set up AI traffic tracking in analytics
• Start regular AI visibility monitoring (daily or weekly)
• Adapt content strategy: expert materials with specifics and facts
• Track which of your pages neural networks cite
• Compare visibility with competitors and adjust strategy

Conclusion

AI search is not the future, it is the present. Half of Russian internet users already search for information through neural networks, and this share is growing. For businesses, this means the emergence of a new customer acquisition channel with its own rules.

The main rule: there is no second page in AI answers. A brand is either mentioned or it is not. And to be mentioned, you need to understand how each platform generates answers, monitor your visibility, and purposefully work on your presence in generative results.

Learn more about what AI brand visibility is and how to build a monitoring system — in separate blog articles. A practical guide for SEO professionals: GEO for SEO specialists.