How is "usage share" defined in this report?

Usage share in this report specifically refers to the proportion of product research, service discovery, and brand evaluation queries — the types of queries that are relevant for AEO strategy. This is a narrower definition than overall AI engine usage, which includes non-search activities.

Why do the market share numbers differ from other reports?

Most published reports measure overall AI engine usage or monthly active users. Our figures specifically measure product and service research query share, which has a different distribution. Engines like Perplexity command a higher share of research queries than their overall user numbers might suggest.

Which engine should my brand prioritise?

The right priority depends on your audience. Track which engines your brand currently appears on and which engines your competitors dominate, for example with a regular manual prompt check. Generally, ChatGPT should be included in any AEO strategy due to its overall volume, supplemented by the engines most popular with your specific audience.

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Research

AI Engine Market Share 2026

Usage share and growth trends across ChatGPT, Perplexity, Gemini, Claude, Copilot, and more.

Last updated: 2026-10-02

Quick answer

The AI engine landscape is fragmented and fast-moving. Our 2026 study suggested that no single engine dominates all use cases — ChatGPT leads in general product research, Perplexity excels for real-time information needs, Gemini captures Google ecosystem users, and Claude attracts technical and enterprise audiences.

Key findings

Data at a glance

~38%

ChatGPT usage share

Our 2026 study suggested that ChatGPT accounts for approximately 38% of AI engine usage for product and service research queries.

~19%

Gemini usage share

Based on data collected in our 2026 study, Gemini captures roughly 19% of AI search usage, driven by deep Google ecosystem integration.

~14%

Perplexity usage share

Our 2026 study suggested that Perplexity holds approximately 14% usage share, with particularly strong adoption among researchers and professionals.

~11%

Claude usage share

Based on data collected in our 2026 study, Claude captures roughly 11% of AI search usage, with a concentration in enterprise and technical audiences.

~9%

Copilot usage share

Our 2026 study suggested that Microsoft Copilot accounts for approximately 9% of AI search usage, boosted by Microsoft 365 integration.

~9%

Other engines combined

Based on data collected in our 2026 study, emerging engines including Meta AI, Mistral, and vertical-specific tools account for the remaining ~9% of usage.

~67%

Multi-engine users

Our 2026 study suggested that approximately 67% of regular AI search users query more than one engine, reinforcing the need for multi-engine optimisation.

~4.2x

Perplexity growth rate

Based on data collected in our 2026 study, Perplexity is the fastest-growing major engine with approximately 4.2x year-over-year usage growth.

The fragmented AI search landscape

Unlike traditional search where Google commanded 90%+ market share, the AI engine landscape is genuinely fragmented. Our 2026 study suggested that no single engine exceeds 40% usage share for product research queries, and the top 3 engines combined still leave more than a third of usage to other platforms.

This fragmentation is structural rather than transitional. Based on data collected in our 2026 study, each major engine has developed distinct strengths that attract different user segments. ChatGPT's conversational depth, Perplexity's real-time sourcing, Gemini's Google integration, and Claude's analytical rigour all create durable differentiation.

For brands, fragmentation means that optimising for a single engine is insufficient. Our 2026 study suggested that brands need to monitor and optimise across at least the top 4-5 engines to capture a representative share of their audience's AI search activity.

Engine-specific audience profiles

Each AI engine attracts a distinct audience, and understanding these profiles is essential for targeting. Our 2026 study suggested that ChatGPT users skew toward general consumers and mid-market businesses, while Claude users tend toward enterprise, technical, and research-oriented roles.

Based on data collected in our 2026 study, Perplexity users are disproportionately likely to be making purchasing decisions for technology products and professional services. Gemini users tend to be deeply embedded in the Google ecosystem, making it particularly important for brands with strong Google Business and YouTube presence.

Copilot usage is concentrated in enterprise environments where Microsoft 365 is the default productivity suite. Our 2026 study suggested that B2B brands targeting enterprise buyers should prioritise Copilot optimisation alongside ChatGPT and Claude, as these three engines collectively represent the majority of enterprise AI search activity.

Emerging engines and new entrants

The AI engine market continues to attract new entrants. Our 2026 study suggested that vertical-specific AI search tools — focused on categories like travel, finance, or developer tools — are capturing meaningful usage share within their niches, even as general-purpose engines dominate overall volume.

Based on data collected in our 2026 study, Meta AI's integration across Facebook, Instagram, and WhatsApp gives it significant distribution potential, though its current share of product research queries remains modest. Open-source models deployed in enterprise settings represent another growing segment that is difficult to monitor but increasingly important for B2B visibility.

The strategic takeaway is that the engine landscape will continue to fragment rather than consolidate. Our 2026 study suggested that brands should build flexible AEO frameworks that can accommodate new engines as they emerge, rather than building engine-specific strategies that become obsolete as the market evolves.

Implications for multi-engine AEO strategy

Market share data should directly inform resource allocation. Our 2026 study suggested that brands should weight their AEO efforts roughly in proportion to each engine's share among their target audience — not the overall market. A developer tools company, for example, should likely over-index on Claude and Perplexity relative to their overall market share.

Based on data collected in our 2026 study, multi-engine monitoring reveals important discrepancies. A brand might be well-cited on ChatGPT but invisible on Perplexity, or vice versa. These discrepancies often reflect engine-specific content preferences that can be addressed with targeted optimisation.

Our 2026 study suggested that the most effective multi-engine strategies focus on a common foundation of authoritative content and structured data, supplemented by engine-specific tactics. This approach ensures baseline visibility across all engines while capturing incremental gains on priority platforms.

Methodology

How this research was conducted

Engine market share estimates are derived from our referral traffic analysis, survey data, and publicly available usage statistics from engine providers. Usage share specifically refers to the proportion of product and service research queries — not overall AI engine usage, which includes code generation, creative writing, and other non-search activities.

All market share figures are our estimates and should be treated as directional indicators. The AI engine market is evolving rapidly, and share figures can shift meaningfully quarter to quarter.

FAQ