Generative Engine Optimization Costs: What Agencies Do and What Results to Expect

There is no established rate card for generative engine optimization in 2026. Published pricing runs from low four-figure monthly retainers to bespoke enterprise programmes, the deliverables are inconsistent between vendors, and the evidence behind individual tactics varies enormously.

That makes the useful question less "what should GEO cost" and more "which part of this proposal am I actually paying for". This guide covers what the market currently charges, what a substantive programme contains, which tactics the evidence does not support, and how to judge results in a discipline too young to have benchmarks.

Key takeaways:

• GEO pricing is unsettled. Treat any quoted range, including the ones below, as indicative rather than a benchmark.
• Ahrefs tracked 1,885 pages adding schema markup and found no meaningful citation uplift, so schema should not be sold as a proven AI-citation lever.
• Roughly two thirds of ChatGPT's most-cited pages sit in categories a brand cannot straightforwardly pitch, which caps what any agency can engineer.
• A 2026 survey of GEO research found no technique with a stable, longitudinal, cross-platform causal effect on discoverability. Distrust guaranteed timelines.

How much does generative engine optimization cost?

Published GEO pricing in 2026 spans from a few thousand dollars a month to custom enterprise engagements. The table reflects where the rates we see quoted across the market tend to sit, and should be read as indicative rather than as an industry benchmark, because no independent pricing survey exists yet.

Price alone tells you almost nothing about quality here, because rates are currently set by agency positioning rather than by any established benchmark. A $12,000 retainer and a $4,000 retainer frequently contain the same five activities. If the terminology in a proposal is unfamiliar, our plain-English guide to GEO, SEO and AEO is worth reading before the next call.

What do GEO agencies actually do?

We would expect a substantive GEO programme to cover five broad workstreams. There is no established industry benchmark for how a retainer should be split between them, so the allocation below is our own planning model rather than market data. As a practical starting point, most execution spend should sit in content and off-site authority work rather than in dashboards or technical hygiene.

Whatever split an agency proposes, ask them to write it down. The proportions are the tell. A proposal weighted toward technical work and reporting is selling you dashboards, and one that is 90% content production is selling you a blog with new branding. A competitor gap analysis for AI search is usually where a good engagement starts, because it determines whether the other four workstreams are aimed at anything.

What GEO spend does not work?

Some line items have been tested and found wanting, and schema markup is the clearest case. Agencies still sell it as a headline AI visibility deliverable.

Ahrefs tracked 1,885 pages that added JSON-LD schema between August 2025 and March 2026, matched them against 4,000 control pages, and measured citation changes across AI Overviews, AI Mode and ChatGPT. The result was no meaningful citation uplift on any platform: a small decline in AI Overviews, and changes in AI Mode and ChatGPT statistically indistinguishable from zero. Schema remains worth having for rich results in classic search, so keep it as hygiene inside the technical slice. Be sceptical of any proposal positioning it as a major GEO growth lever.

The second issue is scope. Ahrefs analysed ChatGPT's 1,000 most-cited pages and found that roughly two thirds fell into categories a brand cannot straightforwardly pitch or reproduce, with Wikipedia at 29.7%, homepages at 23.8% and app stores at 6.6%. Ahrefs notes the categorisation was performed with an AI model and is directional rather than definitive, and it reflects one snapshot rather than a permanent structure.

Read carefully, it still reframes the proposal in front of you. There is a practical ceiling on how much citation share any agency can directly engineer. The useful response is to concentrate effort on source types a brand can realistically influence, including educational content, reviews, earned media and relevant third-party coverage, rather than promising control over the citation ecosystem as a whole. Our breakdown of the content signals that make AI tools cite a brand covers what sits inside that.

How should GEO results be staged?

Stage them as evidence checkpoints rather than a performance curve. There is not yet enough industry data to attach reliable month-by-month citation benchmarks to GEO, and a 2026 survey of the research literature found that across 45 reviewed studies, no technique demonstrated a stable, longitudinal, cross-platform causal effect on organic discoverability or downstream behaviour.

Use that honestly. The staging below is an evaluation framework you can write into a contract, not a guaranteed timetable:

1. Establish a baseline. A repeatable measurement across named prompts and named engines, owned by you.
2. Early programme. Test whether target prompts begin producing new mentions or citations at all.
3. Middle programme. Determine whether those gains persist across repeated runs, prompt variants and more than one engine.
4. Mature programme. Assess whether visibility is broadening beyond branded prompts, and whether AI-assisted discovery is contributing to commercial outcomes.

Step three carries most of the weight, because AI answers are non-deterministic. The same prompt can return different sources across runs, users, models and dates, so a single citation is not a ranking position. Credible measurement means repeated runs, prompt variants and multiple engines, and any agency reporting one screenshot as proof has not measured anything.

Treat guaranteed citation timelines cautiously, particularly where an agency does not separate branded prompts from genuinely competitive category queries.

One measurement warning. Ahrefs found that 28.3% of ChatGPT's most-cited pages have zero organic keywords and no traditional search visibility, so a conventional rank tracker can miss AI citation gains entirely. AI visibility needs its own measurement layer, agreed before the contract starts rather than in month four when somebody asks why the traffic graph is flat.

Traffic will also flatter you less than it used to. Ahrefs estimated that the presence of an AI Overview is associated with roughly a 58% lower click-through rate for the top-ranking result, so citation without a click is now a normal outcome rather than a failure.

How does in-house compare on cost?

In-house GEO costs more than most teams estimate, because the capability spans content strategy, technical SEO, measurement and digital PR. The true comparison is rarely one agency retainer against one employee salary, which is how the business case usually gets built and why it usually gets built wrong.

A single hire covers one person's capacity across four disciplines, plus tooling, plus the time to build measurement from nothing. In-house wins on product knowledge and responsiveness. Agencies win on breadth and on having seen the same problem across twenty other accounts.

A practical hybrid model is to keep strategy and subject-matter expertise in-house while buying specialist execution and measurement capacity.

The contract clauses that protect your budget

Four clauses separate a GEO contract you can hold someone to from one you cannot. None are controversial, and all four are easier to agree before signing than after.

• A baseline report as a paid first deliverable, owned by you, before the retainer starts.
• Named prompts and named engines in the scope, rather than "AI visibility" as a category.
• The workstream split in writing, using the five categories above, with the right to rebalance quarterly.
• Data portability on exit, covering prompt sets, tracked citations, and historical reporting.

That fourth clause matters more than it sounds. Without a data-portability clause, teams risk losing their historical citation data when they change vendors, and in a discipline where the measurement layer is the asset, that history is expensive to rebuild. If a proposal fails several of these tests at once, our guide to spotting old SEO in new packaging covers the rest of the warning signs.

FAQs

The ranges are easy to find and, on their own, they will not tell you whether a proposal is any good. Ask for the workstream split, check the schema line is priced as hygiene rather than strategy, insist the baseline report is yours, and make the agency say how many runs sit behind every citation number they show you.

If you want a GEO programme scoped against named prompts with the measurement agreed up front, that is the work we do at Tenpoint Labs.