GEO & AEO Industry Statistics: 2026 Report

TGA's research team surveyed 486 marketing leaders across North America and Western Europe and analyzed anonymized analytics data from 1,140 brand websites to measure the size and shape of the generative engine optimization and answer engine optimization market.

First, some disambiguation. Generative engine optimization, or GEO, is the practice of positioning a brand so that generative assistants such as OpenAI's ChatGPT, Google's Gemini, Anthropic's Claude, and Perplexity recommend and cite it inside their answers. Answer engine optimization, or AEO, is the older and narrower practice of structuring content so that it can be lifted directly into an answer surface, a category Google established with featured snippets and expanded with AI Overviews. In practice, most of the vendors serving the category sell them as one program, so we measured them together and flagged the differences where our data showed them.

Our spend figures combine agency services revenue with software and platform license revenue, converted to U.S. dollars at the average rate for each period and normalized to exclude traditional SEO retainers that carry incidental AI-search work. Survey responses were weighted by company revenue band so that the results reflect the market rather than the sample. In the sections below, we break down market size, spend trajectory, budget allocation by company size, platform-level referral and citation benchmarks, and adoption by industry.

GEO and AEO Industry Benchmarks

In the table below, we present the headline figures from the study: market size, growth, adoption, budget share, and the performance benchmarks most often requested by the marketing teams we surveyed.

• We found that adoption is running well ahead of spend maturity: 37.4% of enterprise teams have a formal program, but the median retainer of $7,400 per month is roughly half what the same companies spend on traditional SEO.
• Our data showed AI assistant referral traffic converting at 3.8 times the rate of traditional organic search, which is the single figure most often cited by the teams in our sample when they justify budget.
• We found that the 3.9% median session share understates the channel's importance, because the assistants influence a far larger share of purchases than they refer clicks for.

GEO and AEO Spend by Category, 2023 to 2028

The spend figures above sit on a short but steep history. In the table below, we show annual GEO and AEO spend split between agency services and software platforms, with 2027 and 2028 modeled from current contract growth and announced platform pricing. The line graph beneath the table plots the same series.

The dip in growth during 2026 is the part of this series worth dwelling on. Spend roughly tripled in 2024 and doubled again in 2025 as brands funded first-time audits and pilot programs, most of which were one-time purchases. The 2026 slowdown to 48.4% reflects the end of that pilot wave rather than a loss of interest, and our model shows growth reaccelerating in 2027 as pilots convert to retained programs and platform license renewals compound. Software spend is growing faster than services spend off a smaller base, and we expect the two categories to converge in size around 2029.

GEO and AEO Budget Allocation by Company Size

Budget behavior varies sharply by company size, and not in a straight line. In the table below, we break down allocation, retainer size, and program ownership across five revenue bands.

• We found the heaviest relative commitment in the $250M to $1B band, where companies allocate 12.7% of digital budget, more than twice the share committed by companies under $10M.
• Our data showed agency use peaking in the middle of the market and falling off above $1B, where 81.3% of companies have hired a dedicated in-house owner and increasingly split the work between internal staff and specialist vendors.
• We found that absolute retainers scale faster than budget share, with companies over $1B paying 7.5 times what companies under $10M pay while allocating a smaller proportion of their budgets.

AI Assistant Referral and Citation Benchmarks by Platform

Practitioners generally want platform-level numbers rather than a blended average, since the assistants differ in how often they cite sources at all. In the table below, we break down referral share, citation behavior, and conversion performance across the five assistants that accounted for measurable traffic in our sample.

The gap between referral share and citation rate is the central finding here. ChatGPT sends more than half of all AI referral traffic while citing a source in only 7.4% of its responses, a combination that follows from its scale rather than its linking behavior. Perplexity cites a source in 92.4% of responses and still accounts for 6.3% of referrals, because its audience is a fraction of ChatGPT's. For measurement purposes this means citation counts and referral counts are not interchangeable, and a program judged only on sessions will systematically undervalue the assistants that mention a brand without linking to it. We recommend tracking both, and weighting citation share more heavily in categories where buyers research inside the assistant and then navigate to the brand directly.

GEO and AEO Adoption by Industry

Adoption is uneven across industries, and the industries that adopted earliest are not always the ones seeing the strongest returns. In the table below, we break down program adoption, traffic share, retainer size, and conversion performance across seven sectors.

• We found professional services firms converting AI referral traffic at 11.4%, the highest rate in the study, despite ranking third in adoption and fifth in traffic share.
• Our data showed travel and hospitality receiving the largest share of sessions from AI assistants at 7.8%, a consequence of how often itinerary and destination questions are asked conversationally.
• We found the highest retainers in financial services and healthcare, where compliance review adds roughly six to nine weeks to content production and pushes program costs above the market median.

Requesting a Copy of This Report

If you would like a PDF copy of this report, including the full methodology and the unweighted survey tables, you can reach out here.

Sources

• GEO and AEO Industry Research Study, 2026. TGA Research. September 2026. New York, New York.
• Gartner 2026 CMO Spend Survey. Gartner, Inc. May 11, 2026. Stamford, Connecticut.
• AI Search Stats: Market Share, Referral, and Citation Data. Similarweb. 2026. Tel Aviv, Israel.
• AI Platform Citation Patterns: How ChatGPT, Google AI Overviews, and Perplexity Source Information. Profound. 2026. New York, New York.
• Generative Engine Optimization Market Report. Dimension Market Research. 2026. Pune, India.
• Generative Engine Optimization Customer Acquisition Cost (CAC): 2026 Benchmarks. First Page Sage. 2026. San Francisco, California.