AI Search Optimization Pricing: What B2B Should Budget

The short answer

Most B2B tech companies should budget $4,500 to $11,000 a month for an agency-run AI search optimization program, plus $100 to $700 a month for tracking tools. First Page Sage's October 2026 study of 1,146 quotes puts the market median at $6,850 a month, and B2B SaaS and cybersecurity firms pay above that.

That is the headline range. The rest of this guide explains where those numbers come from, what each budget level should buy, which pricing models carry hidden risk, and how to size the budget against your own deal values instead of against an agency's rate card.

It's written for founders, CEOs, and marketing leads at software development companies, B2B SaaS vendors, IT outsourcing and staff augmentation firms, cybersecurity companies, and Salesforce, HubSpot, and ERP consultancies. These businesses sell high-value contracts to technical buyers who now ask ChatGPT, Perplexity, Claude, or Gemini for a shortlist before they ever talk to sales. If you need the basics of the discipline first, start with our guide to AI search optimization for B2B tech.

How much does AI search optimization cost in 2026?

AI search optimization costs between $1,800 and $60,000 or more a month, depending on company size and scope. The median retainer is $6,850 a month, according to First Page Sage's 2026 pricing report, which normalized 1,146 GEO and AEO price quotes from 214 agencies collected between July 6 and October 2, 2026.

One caveat before the numbers. First Page Sage is itself a GEO agency, and its own published range of $6,000 to $12,000 a month sits inside the tier it calls Growth. The dataset is the largest public one we know of, and it lines up with what we see in proposals across the market, but read it as an agency's study, not a neutral census.

The report groups agency pricing into four tiers by client size and scope:

Most software development companies, IT services firms, and Series A to C SaaS vendors land in the Growth tier. A 50 to 300 person dev shop competing for 'best custom software development company for fintech' prompts rarely needs an Enterprise program. A cybersecurity vendor competing against public companies for 'best XDR platform' prompts may need Advanced from the start.

Price does not scale evenly with output. In the same data, Enterprise clients pay 10.7 times the Starter median for 4.2 times the monthly deliverables. The extra money buys digital PR, original research, multi-market coverage, and senior staff, which are exactly the things that move AI recommendations in crowded categories.

Why has AI search pricing risen faster than SEO pricing?

AI search pricing rose because demand grew faster than the supply of agencies that can show results. First Page Sage tracked the median GEO and AEO retainer climbing 66% from Q1 2024 to Q3 2026, from $4,120 to $6,850 a month, while the median traditional SEO retainer rose only 6%, to $4,740.

GEO and AEO retainers passed SEO retainers in Q4 2024, and the gap has widened every year since. AI search work now costs about 45% more than SEO at the median. The report also notes three small dips in the series, each one following a wave of new agencies launching GEO services at entry prices.

Two things explain the premium in our experience. The work is broader than SEO, because a model's recommendation depends on what third-party sites say about you, so programs include PR, review generation, and listicle placement on top of on-site content. And the buyer behavior shift is real. Ahrefs found in April 2025 that an AI Overview on the results page correlated with a 34.5% lower click-through rate for the top-ranking page, and its re-run on December 2025 data put that drop at 58%. When clicks move into the answer, being named in the answer is worth paying for.

What do B2B tech companies pay compared with other industries?

B2B tech pays more than most industries. First Page Sage's 2026 data puts the median B2B SaaS engagement at $8,640 a month and cybersecurity at $9,420, both above the $6,850 all-industry median. Only financial services pays more, at $9,850.

The report doesn't break out software development services, IT outsourcing, or CRM consultancies as separate industries. From what we see, those categories price closer to B2B SaaS than to manufacturing, for one reason: contract values are high and AI answers in those categories are crowded. Ask ChatGPT for the best Salesforce consulting partner in the US or the best nearshore development company in Poland and you get a short list of names. The firms on that list win meetings, and everyone else competes on price.

The upside is that the math works better for you than for a home services company. A $60,000 software project or a $200,000 annual staff augmentation contract pays for a year of AI search work with a single deal.

How do agencies structure AI search optimization pricing?

Most agencies sell AI search work as a monthly retainer. In First Page Sage's dataset, 41% of agencies use a custom monthly retainer and 27% use tiered packages, so 68% of the market is on some form of retainer. The rest sell projects, one-time audits, hourly consulting, or performance-based deals.

When does a monthly retainer make sense?

A retainer makes sense when you want the agency to run the program end to end: tracking, content, entity fixes, PR, and reporting. AI answers drift as models update and competitors publish, so the work is ongoing by nature. The trade-off is commitment. Growth-tier retainers usually carry a six-month minimum, which is reasonable given how long authority building takes, but you should know the exit terms before you sign.

When does a one-time audit or sprint make sense?

An audit or sprint makes sense when you don't yet know whether AI search is a real channel for your category, or when you have an in-house team that can execute once someone maps the gaps. A good audit baselines where you and your competitors appear across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews for your commercial prompts, then hands you a prioritized plan. The report found project and sprint pricing carries the largest single ticket, a median of $14,500, and that buyers often use it to test an agency before signing a retainer.

Is performance-based pricing a good deal?

Performance-based pricing is rare, at 5% of agencies, and it is harder to run than it sounds. These deals tie fees to tracked AI recommendations or mentions, and buyers in First Page Sage's survey reported difficulty agreeing on how those results are counted. AI answers change from one session to the next and differ by engine, location, and phrasing. If you go this route, define the prompt set, the engines, the sampling method, and the counting rule in the contract before work starts.

What about hourly consulting?

Hourly advisory, at a median of $205 an hour in the 2026 data, fits teams that already have writers and a PR function and need a senior person to set direction once a month. It rarely fits a 40-person dev shop with one marketer, because the bottleneck there is execution, not advice.

What do published agency prices look like?

Few agencies publish GEO or AEO prices. First Page Sage found that only 23% of the 214 agencies in its dataset publish any pricing, and the figures they do publish tend to lead with entry tiers. Here is what a handful of established agencies list, as reported in First Page Sage's October 2026 study and, for Optimist, on its own site.

Two notes on reading this table. Published prices are starting points, and the median published starting price among the agencies First Page Sage reviewed was $4,500, below the $6,850 market median. Also, pages change. During our research, Optimist's own site listed different one-time strategy prices on different pages, so confirm the current number on the agency's pricing page or in a written proposal before you budget around it.

For a wider look at the agencies themselves, including what each one specializes in, see our ranking of the best AEO and GEO agencies for B2B tech.

What should each budget level buy?

Each budget level should buy a defined scope tied to a defined prompt set. Two engagements at the same price can contain very different work, so compare scopes line by line. Below is what we think a B2B tech company should expect at each level, informed by the scope data in the 2026 report and by the programs we run.

Under $3,000 a month: tracking and a few fixes

At this level, expect monthly visibility reporting on a small prompt set, a technical and entity audit, and three or four content pieces a month. That's useful for a small firm in a niche category with little competition in AI answers. It rarely moves recommendations in a crowded category, because it doesn't fund the third-party work that models weigh most.

$4,500 to $11,000 a month: a full program for most B2B tech firms

This is where most software development companies, IT services firms, and mid-market SaaS vendors should sit. The scope should include:

• A commercial prompt set of 20 to 50 'best vendor for', 'top alternatives to', and 'who should we hire for' questions, prioritized by deal influence.
• A baseline across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews, re-measured monthly.
• Entity and structured data cleanup, so models can place you in the right category and service line.
• Comparison pages, category explainers, and proof assets written to be cited.
• Placement work on the third-party listicles, directories, and review sites (Clutch, G2, and niche lists) that models already cite for your prompts.
• CRM attribution, so AI-sourced leads show up as a named source.

If a proposal in this range doesn't include third-party placement or review work, ask why. On-site content alone rarely changes who a model recommends. We cover the mechanics in our piece on how entity SEO and citations decide who AI engines recommend.

$11,000 to $22,000 a month: authority building at scale

The jump to the Advanced tier mostly buys digital PR and original research. In First Page Sage's scope data, the share of agencies including digital PR rises from 33% at Growth to 71% at Advanced, and original research rises from 29% to 64%. For a cybersecurity vendor or a SaaS company fighting well-funded competitors, that's often the work that finally shifts the answer. For a dev shop selling into a niche, it may be more than you need.

$22,000 a month and up: enterprise and multi-market

Enterprise programs add multi-market and multilingual coverage (67% of Enterprise-tier agencies include it, against 24% at Advanced), dedicated senior teams, and larger PR budgets. They suit public software companies and large IT services groups with several regional brands. They also come with the longest terms, typically 12 months.

How much do AI visibility tracking tools cost?

AI visibility tools cost from about $29 a month for a starter tracker to $700 a month or more for broad coverage, and enterprise platforms are custom-priced. Most agencies include tool costs in the retainer. If you run tracking in-house, budget for it separately.

Pick the tool after you've written the prompt set, not before. A tool is only as good as the prompts it tracks, and most of the value comes from choosing the 20 to 50 questions that actually precede a purchase in your category. Our guide on how to measure AI search visibility walks through the metrics and how to sample answers so the numbers mean something.

Is it cheaper to build AI search in-house?

For most B2B tech companies, no. First Page Sage modeled the full cost of five approaches using salaries from a survey of 362 marketing leaders. A Growth-tier agency came to $98,400 a year including internal management time. One in-house GEO specialist came to $146,028, and a three-person in-house team to $363,512.

Those are US salary figures. A software company headquartered in Poland, Ukraine, or Portugal can hire a specialist for less, which narrows the gap. The speed difference doesn't narrow, though. In-house approaches took 13.6 to 17.9 weeks to publish a first deliverable, mostly recruiting time, against three to four weeks for an agency.

Hiring in-house also assumes you can find someone who has done this before. AI search is a young discipline. Most candidates have SEO backgrounds and are learning the citation and entity side on the job, so you pay for their learning curve. The hybrid model in the table, one internal owner plus an agency, is often the right answer for a company with 200 or more people that wants to own the channel long term.

How should a B2B tech company set its AI search budget?

Set the budget from your deal economics, not from the agency's rate card. Work out what one AI-sourced deal is worth, estimate how many deals a realistic program could influence in a year, and cap annual spend at a fraction of that value. Then pick the tier that fits under the cap.

Annual budget ceiling = (Average first-year deal value x Gross margin) x Deals you expect AI search to influence per year x 0.3

Example: $120,000 first-year contract x 40% margin = $48,000 gross profit per deal
$48,000 x 4 influenced deals = $192,000 annual gross profit
$192,000 x 0.3 = $57,600 ceiling, or about $4,800 a month

The numbers in that example are illustrative, not a client's. The 0.3 multiplier is a judgment call: it leaves room for the program to miss its forecast in year one and still pay back. A firm with $500,000 enterprise contracts can justify an Advanced-tier program on a single deal. A firm with $25,000 projects should start with an audit and a small retainer and grow spend as the channel proves itself.

Then sanity-check the forecast. How many 'best vendor' and 'top alternatives' prompts exist in your category, and how often do buyers ask them? How many competitors are already named in those answers? If ChatGPT already recommends five well-known firms for your main prompt, you will need more authority work, which means a higher tier or a longer runway. If the answer names one firm or none, a smaller program can win the slot.

What about companies with several service lines?

Budget per service line, then prioritize. A dev shop that sells custom software, staff augmentation, and data engineering has three different prompt sets, three sets of competitors, and three citation landscapes. Funding all three at once at the Starter level usually wins none of them. Funding the highest-margin line at the Growth level for two quarters, then expanding, usually works better.

What results should the spend produce, and how fast?

A well-scoped program should produce measurable movement on the prompt set within one to three months and AI-sourced pipeline within one or two quarters. Speed depends on your starting authority and how crowded the answers are, so treat any agency that promises a fixed date for a recommendation with caution.

Here is what that has looked like for B2B tech companies we've worked with, taken from our published case studies:

• Computools, a software development company: two $1M enterprise deals closed from ChatGPT, $2M in total, in a three-month engagement.
• Baytech Consulting, a software development company: recommended by every major AI assistant for three commercial keywords, a 100% AI-search placement success rate.
• Opsworks, a DevOps company: positioned for an important commercial keyword and recommended by the major AI assistants within a single month.
• Intelvision, a staff augmentation company: 2 to 4 SQLs a month from ChatGPT, on top of a paid program that returned 28.88x ROAS.
• Gapsy Studio, a design agency: AI-assistant traffic grew from 10 to 154 visits a month in three months, about 15x, after six months of zero results from another agency.
• SolarSpark, a game development studio: recommended by LLMs for two commercial keywords and landed a big client in one month.

Across our AI search work, we see an 80% recommendation success rate on targeted commercial prompts. Not every prompt converts, and that's why the prompt set gets revised monthly against what the sales team actually closes. These results also explain why we're skeptical of programs measured only in mentions. Computools' result was two signed contracts, which is a number a CFO can read.

What hidden costs do AI search budgets miss?

The retainer is rarely the whole cost. Budgets that look fine on paper often miss internal time, approval cycles, and third-party fees that the agency passes through. Plan for these before you sign:

• Subject matter expert time. Comparison pages and category explainers for technical buyers need input from your engineers or solution architects, usually two to four hours a month.
• Review generation. Clutch and G2 reviews come from your clients, and someone on your side has to ask for them.
• Paid placements. Some directories and listicles charge for inclusion or premium profiles. Ask whether the retainer covers these or whether they are billed on top.
• PR fees. Some agencies pass through costs for wire distribution or paid contributor slots.
• CRM setup. Tagging AI-sourced leads needs a lead-source field, a 'how did you hear about us' question, and sales discipline. If your CRM is a mess, budget a few days to fix it.
• Website changes. Entity and schema fixes often need a developer, which is one more reason to check who owns implementation.

First Page Sage's agency cost model includes internal management time for exactly this reason. An agency program that needs no time from you is either very expensive or not doing much.

Which pricing red flags should B2B buyers watch for?

Watch for guarantees, vague units, and lock-ins without an exit. AI answers are probabilistic and change with model updates, so any pricing that assumes certainty is pricing a promise the agency can't control.

• Guaranteed placement in ChatGPT by a fixed date. No one controls a model's answer. An agency can show its track record and method, and that's what you should ask for.
• Pricing by mention count with no prompt set. A mention on an irrelevant prompt is worth nothing. Ask which prompts are tracked and why.
• A 12-month minimum at the Growth tier with no performance exit. Six months is normal for authority work. Longer terms should come with a defined review point.
• No CRM attribution in scope. If the agency can't tell you how AI-sourced leads will show up in your pipeline, you'll be judging the program on screenshots.
• On-site content only. If the scope never touches third-party sources, reviews, or listicles, it's an SEO retainer with a new label.
• Generic B2B case studies. Ask for results from companies that sell what you sell to the buyers you sell to.

What questions should you ask before signing?

Ask questions that force the agency to show its scope, its measurement, and its relevant proof. The answers tell you more about the real price than the rate card does.

• Which 20 to 50 prompts would you track for us, and how did you choose them?
• Where do we and our top three competitors appear today, engine by engine?
• What share of the budget goes to third-party placement and reviews versus our own site?
• How will AI-sourced leads be tagged in our CRM, and who sets that up?
• What is the minimum term, and what happens if the prompt set shows no movement after 90 days?
• Which clients in software development, SaaS, IT services, or our specific niche have you worked with, and what changed for them?
• Which costs sit outside the retainer?

The same diligence applies to fractional marketing leadership. If you are weighing an AI search program against hiring a senior marketing lead first, our breakdown of what a fractional CMO costs covers the other side of that decision.

Should you buy AI search optimization and SEO separately?

Usually not. Much of the authority and content that ranks you in Google is also what models read when they build an answer, and AI Overviews sit on top of the search results page. Buying them from two agencies means two reporting systems, two content calendars, and two teams pitching the same third-party sites. If you already have a strong SEO partner, ask whether they can add the AI search layer, and compare that quote with a combined program from an AI search specialist.

The price difference matters here. First Page Sage's data puts the median SEO retainer at $4,740 and the median GEO and AEO retainer at $6,850. A combined program priced near the GEO median that covers both is usually better value than paying for two.

How does XQL Group price AI search optimization?

XQL Group scopes AI search work from a baseline, not a rate card. We start by building your commercial prompt set and measuring where you and your competitors appear across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. The program tier follows from what that baseline shows: how many prompts matter, how crowded the answers are, and how much third-party authority you need to earn.

We work with B2B tech companies, more than 60 of them over nine years, and we report AI search as a revenue channel tied to your CRM. That's the same discipline behind the $30M+ in CRM-tracked marketing-led revenue we've recorded for clients. You can see what the program includes on our AI search optimization service page.

The bottom line

For most B2B tech companies, a realistic AI search budget is $4,500 to $11,000 a month for an agency program, plus tools if you track in-house. B2B SaaS and cybersecurity firms should expect to pay toward the upper half of that range, since their categories are crowded and their deals are large. Start from your deal value, fund one service line properly before spreading thin, insist on a written prompt set and CRM attribution, and judge the program on pipeline, not mentions.

If you want to know where your company stands in AI answers today and what it would take to change that, we'll baseline your prompt set and give you a number. Book a 30-minute intro call.