Executive Summary
The way people find brands has changed. Not in theory -- in practice, at scale, across every industry.
In 2024, AI search was a novelty. By 2025, it became a habit. In 2026, it is infrastructure. Hundreds of millions of people now ask AI platforms for product recommendations, service comparisons, and brand evaluations before they ever type a query into a traditional search engine. Some never visit a search engine at all.
This report examines what that shift looks like in practice. We draw on publicly reported platform data, published surveys, and patterns observed through monitoring brand-related queries across seven major AI platforms: ChatGPT, Perplexity, Gemini, Claude, DeepSeek, Grok, and Google AI Overviews.
The picture is clear. AI search is not replacing traditional search. It is layering on top of it, capturing the queries where users want answers -- not links. And the brands that show up in those answers are winning a disproportionate share of attention and trust.
What follows is a platform-by-platform look at where AI search stands today and what it means for any brand that depends on being found.
See also: What Is GEO (Generative Engine Optimization)? The Definitive Guide for 2026
AI Search Growth: The Numbers That Matter
The growth of AI search is no longer speculative. The major platforms have published enough data to draw a clear picture.
ChatGPT: 400 Million Weekly Active Users
OpenAI announced in February 2025 that ChatGPT had reached 400 million weekly active users. That figure represented a doubling from the 200 million reported in mid-2024. By early 2026, industry estimates based on app download data, API usage, and public statements from OpenAI suggest the platform has continued growing, though the company has not released an updated weekly active user figure since that February announcement.
What matters more than the headline number is the type of usage. ChatGPT is no longer primarily a novelty or a coding assistant. A growing share of sessions involve product research, brand comparisons, and recommendation requests. When a user asks "What is the best CRM for a 10-person team?" and gets a detailed answer naming specific brands, that is brand discovery happening outside of Google entirely.
Perplexity: 100 Million+ Queries Per Week
Perplexity reported surpassing 100 million search queries per week in late 2024, positioning itself as the AI-native alternative to traditional search. Unlike ChatGPT, Perplexity is built specifically as a search tool. Every query retrieves live web data and cites its sources with clickable links.
For brands, Perplexity represents something unusual: an AI platform that actually sends traffic back to your site. If your content gets cited, users can click through. This makes Perplexity citation rate one of the most actionable metrics in AI visibility monitoring.
Google AI Overviews: Over 100 Countries, Billions of Users
Google began rolling out AI Overviews in the United States in mid-2024 and expanded to over 100 countries by the end of 2025. Because AI Overviews appear within Google Search itself -- not as a separate product -- their reach is enormous. They sit at the top of results pages, above the traditional blue links, for a significant and growing share of queries.
Google stated at I/O 2025 that AI Overviews were appearing for a meaningful percentage of search queries. Industry analyses from multiple SEO research firms estimate that somewhere between 20% and 40% of informational queries now trigger an AI Overview, though the exact figure varies by vertical and geography.
The implication is direct: even if you rank on page one of Google, an AI Overview can push your organic listing below the fold. Being cited within the AI Overview becomes as important as the ranking itself.
Gemini, Claude, DeepSeek, Grok
The remaining platforms contribute growing but harder-to-quantify volume. Gemini is integrated across Google's product ecosystem -- Android, Workspace, Search -- giving it distribution that other standalone AI apps cannot match. Claude has built a loyal user base among professionals who value detailed, careful responses. DeepSeek gained rapid adoption in technical and research communities, particularly in Asia. Grok, integrated into X (formerly Twitter), has unique access to real-time social data.
None of these platforms have published user numbers with the specificity of OpenAI or Perplexity. But their collective impact is visible in monitoring data: brands that are mentioned across all seven platforms have meaningfully different visibility profiles than brands that appear on only one or two.
The takeaway is not about any single platform. It is about the aggregate. AI search, across all platforms combined, has become a primary information channel for hundreds of millions of people. Any brand strategy that ignores this channel is operating with a serious blind spot.
How User Behavior Is Shifting
Platform growth tells you how many people use AI search. Behavioral data tells you how they use it. The behavioral patterns are where the real implications live.
The Research-First Shift
Multiple published surveys from 2025 and early 2026 point to a consistent pattern: users are starting their research on AI platforms before visiting a search engine. This is most pronounced for complex, multi-factor decisions -- choosing software, comparing service providers, evaluating products with many variables.
The reasoning is intuitive. Traditional search returns ten links and asks the user to click, read, and synthesize. AI search returns a synthesized answer. For a user trying to decide between four project management tools, getting a side-by-side comparison from ChatGPT in 30 seconds is more efficient than opening five tabs from Google results and reading each review separately.
This does not mean users have abandoned Google. Most still use it, especially for navigational queries, transactional queries, and local searches. But the informational and comparative layer -- the part where opinions are formed and shortlists are made -- is migrating to AI.
The Trust Factor
There is an uncomfortable reality in this data. Users trust AI answers more than they probably should. Published surveys consistently show that a significant share of AI users accept AI-generated recommendations without verifying them through additional sources.
For brands, this cuts both ways. If an AI platform recommends you, the user is likely to act on it. If it recommends a competitor, the user may never evaluate you. The AI response is not the beginning of a research process for many users. It is the entire process.
Query Types Moving to AI
Not all queries are migrating equally. Based on publicly available data and observed patterns, here is where AI search is strongest:
- Comparison queries ("X vs Y," "best X for Y") -- AI excels at synthesizing multi-factor comparisons
- Recommendation queries ("What should I use for...") -- AI provides opinionated, specific answers
- Explanation queries ("How does X work?") -- AI delivers structured, readable explanations
- Research queries ("What are the options for...") -- AI aggregates and summarizes faster than manual search
Traditional search retains dominance for:
- Navigational queries ("login to [brand]") -- users want a specific URL
- Transactional queries ("buy [product]") -- users want to complete a purchase
- Local queries ("restaurants near me") -- traditional search has richer local data
- Breaking news -- traditional search indexes news faster than most AI platforms
The queries moving to AI are the ones where brand discovery occurs. Someone asking "best CRM for small businesses" is forming a shortlist. Someone asking "top running shoes under $150" is narrowing choices. These are the moments that determine which brands get considered. And increasingly, these moments happen inside an AI conversation.
See also: AI Brand Monitoring: How to Track What AI Platforms Say About Your Brand
Impact on Brand Discovery
The shift from search-result discovery to AI-answer discovery changes three dynamics about how brands get found.
From Ten Options to Two or Three
A Google results page shows ten organic listings plus ads. A user scanning that page evaluates multiple options. An AI-generated answer typically names two to four brands. Sometimes just one. The narrowing effect is dramatic.
Being "in the conversation" matters more than it ever has. On Google, ranking eighth still gets you some visibility. In an AI-generated answer, there is no eighth position. You are either mentioned or you are absent. The competition is for inclusion, not ranking.
From Click-Through to Trust-Through
Traditional brand discovery follows a path: search, click, evaluate, decide. AI brand discovery often compresses that sequence. The user asks, the AI answers, the user trusts the answer. There may be no click at all. The brand was "discovered" inside a conversation, not on a website.
This changes what counts as visibility. If your brand was mentioned favorably in 500 AI conversations today but none of those users visited your website, did your visibility increase? Yes, it did. Even though your analytics dashboard shows nothing.
The brands winning in AI search are not always the ones with the best websites, the most backlinks, or the highest domain authority. They are the ones the AI knows about, trusts, and recommends. Entity authority, structured data, and content quotability drive this -- not traditional SEO signals alone.
From Stable Rankings to Volatile Mentions
Google rankings are relatively stable. A page that ranks third today will probably rank third tomorrow. AI answers are volatile. The same query asked on Monday and Thursday may produce different brand mentions. A model update can shift recommendations overnight. A competitor publishing strong new content can displace you within days.
This volatility makes monitoring non-negotiable. Without daily tracking, you have no idea whether last week's visibility is still intact. The brands that monitor daily catch shifts early. The brands that check monthly discover problems after weeks of invisible losses.
Platform-by-Platform Visibility Landscape
Each AI platform generates brand recommendations differently. Understanding these differences matters for where you invest your optimization efforts.
ChatGPT
The largest platform by user volume. ChatGPT draws from its training data and, when browsing is enabled, live web retrieval. Brands with broad web presence -- mentions across authoritative sites, strong knowledge base entries, well-documented products -- perform best. ChatGPT tends to recommend established brands for general queries and can surface niche brands when the query is specific enough.
Perplexity
The most transparent platform for brand discovery. Perplexity cites every source it uses, so you can trace exactly why a brand was mentioned. It favors original research, primary data, and content from sites that update frequently. Brands that publish unique data or in-depth guides are disproportionately cited on Perplexity compared to brands with only marketing pages.
Google AI Overviews
Tied to the Google Search ecosystem. AI Overviews pull primarily from pages that already rank well organically, but they also weight structured data, content format, and how directly a page answers the query. A page ranking number one that does not directly answer the question may be skipped in favor of a lower-ranking page that does.
Gemini
Google's standalone AI assistant shares data sources with AI Overviews but generates longer, more conversational responses. Its integration into Android and Google Workspace gives it broad reach across devices and use cases. Strong Google search presence helps, but Gemini also considers structured data and entity clarity independently.
Claude
Built by Anthropic, Claude relies on training data more than live web retrieval for most interactions. Visibility on Claude depends on your brand's presence in publicly available datasets as of the training cutoff. Strong Wikipedia entries, well-known documentation, and mentions in widely-indexed publications drive Claude visibility. Popular among professionals and researchers, making it important for B2B brands.
DeepSeek
A technical user base that values depth and accuracy. Brands in technology, developer tools, and research benefit most. The platform favors content with technical detail: benchmarks, methodology, documentation. Marketing-forward content without substance does not perform well here.
Grok
Integrated with X (formerly Twitter), Grok draws on real-time social media data alongside its training data. Brands with active, engaged X presences are more likely to be mentioned. Social media strategy directly translates into Grok visibility -- one of the few AI platforms where that connection is this direct.
What Brands Should Do Now
The data points in one direction: AI search is a major and growing channel for brand discovery, and brands without AI visibility are losing ground they cannot measure with traditional analytics.
Here is a practical framework.
1. Audit Your Current AI Visibility
Before you optimize, know where you stand. Query your brand name and your key product categories across all seven AI platforms. Note where you appear, where you do not, what the AI says about you, and how competitors compare in the same responses. Do this systematically. AI responses change frequently, so a daily or weekly cadence is necessary for actionable data.
2. Fix Technical Barriers
Check your robots.txt for AI crawler access (GPTBot, PerplexityBot, ClaudeBot, Google-Extended). Add an llms.txt file to your domain root. Implement structured data: Organization, Product, FAQ, and Article schemas. Ensure your site loads quickly and renders without JavaScript. These fixes remove the barriers that prevent AI platforms from even seeing your content.
3. Build Entity Authority
AI models think in entities, not keywords. Your brand needs to be a well-defined entity across the web: consistent name, description, and product information on your site, directory listings, review platforms, and knowledge bases. Strong entity signals make AI platforms more confident in mentioning and recommending you.
4. Create Content AI Can Cite
Restructure key content for AI retrieval. Start sections with direct answers. Include specific data and concrete claims. Write self-contained paragraphs that make sense if pulled out of context. Add FAQ sections with structured data markup. This is not a different content strategy -- it is a structural layer on top of good content.
5. Monitor Continuously
AI visibility is not a set-and-forget metric. Responses change as models update, competitors optimize, and platforms evolve. Daily monitoring across all seven platforms gives you the feedback loop needed to maintain and grow your visibility over time.
See also: What Is GEO (Generative Engine Optimization)? The Definitive Guide for 2026