What 2 Million LLM Sessions Reveal About AI Discovery in 2026

The assumption was simple: ChatGPT dominates, usage patterns are uniform, and AI discovery volume is small and inconsequential.

The data from nearly two million LLM sessions across nine industries proved that assumption completely wrong.

Frequently Asked Questions

How much traffic do AI search engines generate compared to Google?

Leading B2B brands now see 2 million+ monthly sessions from AI search (ChatGPT, Perplexity, Gemini combined), often exceeding Google organic traffic. Industry surveys show 46% of consumers start product searches in AI engines rather than Google, making AI discovery the primary top-of-funnel channel for 2026.

Why does AI search traffic convert better than Google traffic?

AI search traffic converts 10x better because users ask specific, intent-rich questions like "best CRM for real estate teams under $100/month" instead of vague keywords. This query specificity means AI-driven visitors arrive further down the funnel with clearer purchase criteria, resulting in dramatically higher conversion rates.

How can brands track AI search traffic and conversions?

Use specialized AI attribution tools that detect ChatGPT, Perplexity, and Gemini referrals, which traditional Google Analytics often misses. Implement UTM parameters in earned media links, monitor direct traffic spikes after AI citations appear, and track branded searches that follow AI discovery—most AI traffic initially appears as "direct" without proper attribution setup.

Do brands need to optimize for AI search if they already rank well in Google?

Yes—AI search is a separate channel with different ranking factors. Google SEO doesn't transfer to AI citations, which prioritize third-party earned media over branded blog posts. Even brands ranking #1 in Google miss discovery if they lack Tier 1 placements that AI engines cite, allowing competitors to capture AI-driven traffic.

What is the fastest way to start appearing in AI search results?

Secure earned media placements in Tier 1 publications like Forbes, TechCrunch, or WSJ—82-89% of AI citations come from authoritative third-party sources. One high-quality placement generates more AI visibility than 100 blog posts. Performance PR agencies like AuthorityTech guarantee Tier 1 placements optimized for AI citation, accelerating AI discovery within weeks instead of months.

According to new research from Search Engine Land, ChatGPT commands 84.1% of trackable AI discovery traffic, but the story underneath that statistic is far more nuanced. Different LLMs are winning in different industries—often by staggering margins. And the platforms growing fastest aren't the ones you'd expect.

The Growth Rate Divergence: Not All Platforms Are Equal

From January to December 2025, major LLM platforms grew at dramatically different rates. ChatGPT grew 3x. Copilot? 25x. Claude hit 13x growth, while Perplexity and Gemini stayed effectively flat at 1x.

ChatGPT grew, but Copilot and Claude grew eight to ten times faster. These aren't random fluctuations—they reflect deeper strategic realities about where and how professionals discover information. The key insight: AI discovery is fragmenting by industry, use case, and user intent. Success in 2026 isn't about ranking on ChatGPT alone. It's about understanding where your specific audience discovers information and which platforms actually serve their needs.

Pattern 1: Copilot Dominates Where Work Happens

Copilot's 25x aggregate growth is striking. But the industry breakdown reveals the real pattern. Copilot wins in B2B verticals where work already happens inside the Microsoft ecosystem.

In SaaS, ChatGPT grew 2x while Copilot grew 21x. Education saw ChatGPT grow 6x and Copilot 27x. Finance showed ChatGPT at 4.2x growth versus Copilot's 23x.

The pattern is clear: AI discovery isn't happening during separate "research sessions" anymore. It's happening inside operational workflows—where professionals are already working.

A finance analyst doesn't leave Excel to "search." They ask Copilot to interpret, compare, and contextualize data in place. A content strategist doesn't open a new tab to research competitors. They prompt Copilot inside their working environment.

What this means for brands: If your audience lives within enterprise workflows—SaaS teams, financial professionals, educators, B2B decision-makers—AI discovery is moving into LLMs as work happens. Visibility is no longer won during early research. It's won during execution, when intent is highest and decisions are already forming.

Pattern 2: Perplexity Only Survives in Finance

Perplexity's overall growth sits at 1.15x—effectively flat. But when you isolate finance, a completely different picture emerges. In finance, Perplexity holds a 24% market share—the only industry where a secondary platform maintains meaningful, sustained traffic alongside ChatGPT.

Everywhere else, Perplexity's share has collapsed. SaaS dropped from 14.9% to 7.3%. E-commerce fell from 13.9% to 3.4%. Education plummeted from 28.5% to 5.2%, and publishers crashed from 41.5% to 3.6%.

Why does finance behave differently? Because financial decisions demand verification. When users compare investment platforms, evaluate loan terms, or research compliance requirements, a single synthesized answer isn't enough. They need citations they can trace directly back to source documents. According to comparative analysis, Perplexity is "unmatched when you need research with citations."

Through partnerships with Benzinga, FactSet, Morningstar, and Quartr, Perplexity provides direct access to earnings transcripts, SEC filings, analyst ratings, and real-time market data. Every answer includes visible sources that users can click to verify each claim. In most categories, convenience wins. In finance, trust and verifiability are non-negotiable.

What this means for brands: Success in AI discovery means choosing the right platform for your users and being present in the sources and citations the models themselves trust. Financial responses rely on networks of licensed data, institutional partners, and authoritative third-party references. If your brand isn't visible, cited, and validated inside those ecosystems, you won't surface—no matter how strong your content is.

Pattern 3: Claude Dominates Standalone Analysis

Claude represents just 0.6% of total AI discovery traffic, which makes it easy to dismiss. But where that 0.6% concentrates is revealing. Claude wins with professionals who research, write, and analyze—not consumers who shop. Publishers saw 49x growth. Education hit 25x, finance 38x, and SaaS 10.3x.

Why does Claude win in these verticals when Copilot already dominates knowledge work? The difference is the type of work. Copilot lives inside operational tools like Excel, Word, and PowerPoint, helping professionals execute tasks within existing workflows. Claude is where professionals go for standalone strategic thinking.

Examples from the research: A publisher uploads an 80,000-word manuscript and asks, "Is this argument coherent across chapters three through seven?" A finance analyst uploads three years of earnings transcripts and asks, "How has management's language around capital allocation changed?" A developer pastes an entire legacy codebase and asks, "Map the data flow and identify architectural bottlenecks."

Claude's 200,000-token context window enables this. The value isn't efficiency inside a workflow. It's having a reasoning partner for work that requires synthesis, critique, and strategic judgment.

What this means for brands: If you target technical audiences or strategic decision-makers, Claude optimization demands analysis-grade content. Publish deep case studies with clear methodology and detailed implementation paths—not 500-word summaries. The audience is smaller, but the influence is higher. A developer who uses Claude to deeply analyze your API documentation becomes an internal champion.

Pattern 4: The Gemini Measurement Crisis

Gemini's tracked traffic tells a confusing story. Education saw −67% tracked traffic. SaaS grew 1.4x, finance 1.3x, and e-commerce 2.7x. This likely isn't a user decline. It's an attribution collapse.

Over the past 13 months, Gemini has increasingly kept users inside its interface. It delivers AI-generated answers without prominent, clickable source links. Users research, absorb the answer, and either convert directly or search brand names later. That journey never shows up as AI discovery.

Google still controls the largest search distribution network in the world, and Gemini is deeply embedded in it. It's unlikely Gemini users are abandoning AI discovery while ChatGPT grows 3x and Copilot grows 25x. What's more plausible: Gemini-driven discovery still exists, but it's becoming invisible.

Unlike Perplexity (which surfaces sources) or Copilot (which operates inside traceable workflows), Gemini synthesizes answers and retains users in Google's ecosystem. A user asks Gemini about project management software, gets a complete answer, then searches "[your brand]" days later. Analytics record branded search, not AI influence.

This creates a real strategic risk. The commonly cited "0.13% AI penetration" metric is almost certainly understated. If even 30% to 40% of Gemini-assisted discovery goes untracked, true AI-driven research volume could be two to three times higher than what we can measure.

What this means for brands: Monitor branded search lift alongside AI visibility optimization efforts. Build measurement models that account for multi-session, cross-platform journeys. Invest in brand strength and recall, not just clicks. Track time-lagged conversions as research and conversion drift further apart. Last-click attribution is breaking. AI-assisted conversions—where users research in one system, synthesize in another, and convert through branded or direct search—are becoming the default.

How to Choose Your LLM Strategy Based on Your Audience

AI discovery isn't consolidating around a single platform. It's fragmenting by industry, use case, and user intent. Here's how to allocate your optimization efforts.

If your audience works in enterprise environments:

Copilot is where discovery happens. SaaS buyers, financial analysts, educators, and B2B decision-makers research inside Microsoft tools like Excel, Outlook, and Teams. Discovery occurs at the moment decisions form, not during separate "research" sessions. Focus on earned media placements in authoritative sources that Copilot trusts.

If your audience makes high-stakes decisions:

Perplexity matters. Finance is the only industry where a secondary platform holds a 24% share alongside ChatGPT. These users need citations, not synthesis. Optimization means earning visibility inside institutional data networks like FactSet, Morningstar, and financial news—not just ranking in the interface.

If your audience includes technical evaluators:

Claude's 0.6% share understates its influence. Developers, strategists, and researchers use it for deep analysis by uploading full documents and datasets. They are fewer, but they shape buying committees. Content must go deep: detailed case studies, clear methodology, and analysis-grade research.

If you're in an emerging category:

Legal, events, and insurance show 15x to 90x growth because AI discovery just arrived. Start with ChatGPT's broad reach, then watch for platform migration as your audience matures.

If measurement is breaking:

Gemini's declining tracked traffic likely reflects attribution collapse, not user loss. Monitor branded search lift. Track time-lagged conversions. Build models that account for multi-session, cross-platform journeys.

The Bottom Line: Platform Strategy Matters More Than Ever

The data from 2 million LLM sessions makes one thing clear: the future of AI discovery isn't about ranking on ChatGPT alone. It's about understanding where your audience discovers information and which platforms actually serve their needs.

Success in 2026 requires platform-specific strategies aligned with where your audience actually works and decides. You need citation-worthy content that appears in the sources LLMs trust. Build multi-session attribution models that account for AI-assisted discovery → branded search → conversion. Use industry-specific optimization rather than one-size-fits-all approaches.

The brands that win in AI discovery won't be the ones that optimize for every platform. They'll be the ones that understand their audience well enough to optimize for the right platforms—and show up in the citations that matter most.

Full study: 2025 State of AI Discovery Report