How much does AI SEO cost in 2026?

Search has changed considerably over the past few years. 33.3% of the total users are using AI tools like ChatGPT, Gemini, Claude, and Perplexity to research products, compare solutions, and find information. At the same time, Google is introducing more AI-generated answers through AI Overviews and AI Mode.

In September 2026, Ahrefs analyzed 232.8 million US desktop Google search-result crawls and found that AI Overviews appeared in 73.3% of branded search results and 78.3% of the non-branded keywords. Users are exposed to AI answers 8x in Google compared to the usage of LLMs. 

Now your potential customers will discover and evaluate solutions through AI-generated recommendations, across Google and LLMs without necessarily visiting a company's website. This makes the attribution hard leaving CMOs and marketing leaders in a tight spot on how to budget for SEO. 

There are two practical approaches companies can take and are taking: 

• Companies can build an in-house team that manages both traditional SEO and AI SEO
• They can work with an agency that provides the required expertise and execution support.

In this article, we will examine the costs involved in both approaches, including software, employee salaries, content production, and agency retainers. 

We will also look at the operational differences and how B2B SaaS businesses can plan their SEO budgets as AI-driven discovery becomes more common.

What is AI SEO?

AI SEO is the process of optimizing a business's visibility in AI-generated answers across platforms such as ChatGPT, Gemini, Claude, Perplexity, Google's AI Overviews, and AI Mode. The objective is to increase the chances of the business being mentioned, cited, or recommended when users ask questions relevant to its products or services thereby influencing the buyer journey.  

For example, when someone asks an AI assistant to recommend software for a particular business requirement, the response may include several vendors, explanations of their capabilities, and links to supporting sources. AI SEO focuses on improving a company's chances of appearing in these recommendations.

At Scale Theory, we consider AI SEO to be the next step in traditional search engine optimization.

Our approach involves: 

• Optimizing for AI-generated answers wherever they appear, 
• Continuing to improve visibility in traditional search results.
• We also use AI to support SEO execution itself, including research, monitoring, and optimization workflows.

With proper human oversight and quality control, AI can help reduce the time spent on these activities without compromising the quality of the work. This allows us to combine established SEO practices with AI visibility optimization and more efficient execution workflows.

What is the difference between traditional SEO vs. AI SEO?

Traditional SEO focuses on improving search rankings and organic traffic, while AI SEO extends these efforts to improve visibility in AI-generated answers. Both approaches share many underlying practices, but differ in their optimization goals, workflows, and performance measurement.

Here's how they compare:

Google's official guidance for generative AI search states that existing SEO practices remain relevant for AI Overviews and AI Mode. There are no separate technical requirements or special markup needed to appear in these features.

This means businesses do not need to abandon their existing SEO operations. They need to expand how they research, optimize, and measure their visibility.

Why are businesses investing in AI SEO?

There are several developments driving interest in AI SEO. The most obvious is the growing adoption of LLMs, but AI-generated answers are also becoming more common within traditional search engines and other platforms.

1. LLM adoption has reached approximately half the scale of traditional search

We recently conducted research at Scale Theory to understand how large AI search has become compared to traditional search engines.

In our analysis, How big is AI Search?, we compared monthly sessions across leading LLM platforms and search engines using Q2 2026 data from Similarweb.

We found that AI tools received approximately 49.3 billion monthly sessions, compared with 97.3 billion sessions on traditional search engines.

This means that for approximately every two sessions happening on traditional search engines, one session happens on an LLM platform.

But when we looked into the actual number of searches happening in LLMs and search engines we found totally different numbers compared to the sessions split. 

Traditional search engines still account for more than 90% of search queries. AI has already developed a substantial user base, but it has not replaced traditional search. 

For businesses, AI is an additional discovery channel worth considering alongside Google and other search engines.

2. AI-generated answers are changing Google Search

Google AI Overviews provide AI-generated answers directly within search results. These responses can summarize information from different sources, answer questions, and direct users toward additional resources.

In Ahrefs' September 2026 US desktop keyword data:

• 73.3% of branded keywords triggered AI Overviews on average during September.
• 78.3% of non-branded keywords triggered AI Overviews on average during the same period.

Ahrefs also found that AI Overviews reduced clicks to the top-ranking page by approximately 58% in its click-through-rate research. Ranking on the first page may therefore provide a different amount of traffic than it did previously.

The approach here is to be present across all the touchpoints in search, not just be the top ranking result. 

3. Google's AI Mode is expanding AI-powered search

Google has also introduced AI Mode, which allows users to ask more complex questions and continue researching through conversational follow-ups.

This is relevant for software purchases, where buyers often need to compare multiple solutions and understand differences between products before making a decision.

In its June 2026 investor presentation, Google reported that:

• AI Overviews had more than 2.5 billion monthly users.
• AI Mode has surpassed 1 billion monthly users.

This is another reason to consider how your content is discovered and presented within AI-powered results.

4. AI-powered discovery is expanding beyond search engines

AI-generated answers are also appearing on platforms that people already use for research and purchasing decisions.

• Reddit introduced Reddit Answers, an AI-powered feature that summarizes relevant community discussions and allows users to ask questions. In May 2026, Reddit integrated Answers into its main search experience.
• Amazon has also introduced an AI shopping assistant that helps users research products, compare options, and get recommendations. Originally called Rufus, the assistant was renamed Alexa for Shopping in May 2026.
• Social media and other digital platforms are also adding AI-assisted discovery functionality.

These developments are important for B2B SaaS businesses because buyers already research software across multiple sources. They may ask ChatGPT for recommendations, read Reddit discussions, or encounter opinions about vendors on social media before visiting a company's website.

As AI becomes part of these experiences, businesses need to think about where their products are being discussed and recommended.

This increases the scope of SEO-related work, which brings us to the question of cost.

AI SEO pricing in 2026: In-house vs. agency at a glance

For B2B SaaS companies planning to invest in AI SEO, there are two main operating models.

• The first is building an internal team with the expertise and resources needed to manage traditional SEO and AI SEO. 
• The second is hiring an agency that can manage some or all of these activities.

Both approaches involve different costs and operational requirements.

Here is a comparison of the two models.

The agency range above is a planning estimate rather than an industry-wide average. For comparison, Clutch's September 2026 SEO agency pricing guide reports that SEO agencies typically charge between $2,000 and $20,000 per month, depending on experience, specialization, and scope.

The following sections break down the expenses involved in each approach.

How much does in-house AI SEO cost?

Building an in-house AI SEO operation requires hiring an SEO specialist and getting equipped with the right tools. 

You need the software to research and track performance, content resources to execute the strategy, and access to design and development support when website changes are required.

Some of these resources such as design and development can be shared with other departments. Others need dedicated ownership.

1. AI SEO tools alone can cost approximately $1,000 per month

An internal SEO team generally needs software for traditional SEO research, AI visibility monitoring, and technical or operational work.

For a B2B SaaS company managing both traditional and AI search optimization, the following is a preliminary monthly budget.

The first expense is a traditional SEO platform: 

• Tools such as Ahrefs and Semrush help teams conduct keyword research, analyze competitors, monitor rankings, audit websites, and understand existing search performance.
• The proposed $300 to $500 budget is a reasonable allowance for more advanced plans. For reference, Ahrefs lists its Standard and Advanced plans at $249 and $449 per month.

The second expense is an AI visibility tracking platform:

• These tools help businesses understand how frequently their brands appear in AI-generated responses and which competitors are being recommended.
• For our budgeting model, we are assuming that a B2B SaaS business needs to monitor approximately 200 relevant prompts. We have allocated $300 per month as an initial estimate.

Actual pricing depends on how many prompts are tracked, which AI platforms are monitored, and how frequently the prompts are checked.

Some traditional SEO platforms now include AI visibility features as well, so businesses should check for overlapping subscriptions before purchasing another tool.

The third expense covers technical SEO and workflow software:

• For example, Screaming Frog can support technical website crawling and auditing. Its SEO Spider license currently costs $279 annually.

The additional $500 in our model is a broader allowance for other software, reporting, and workflow requirements. It is not the cost of Screaming Frog alone.

Altogether, we would budget approximately 1,100–1,300 per month for the proposed tool stack.

This is an operating allowance, not a minimum subscription requirement. A smaller team may spend less by combining tools and limiting the number of prompts it tracks.

2. In-house SEO specialist salaries

The next major expense is hiring an experienced SEO professional.

Ideally, this person should understand traditional SEO and be capable of extending that work into AI visibility research and optimization.

Their responsibilities would include:

Keyword and competitor research

• SEO strategy
• Technical audits
• Content planning
• AI visibility monitoring
• Performance analysis

Salaries vary depending on the employee's location and experience.

In the United States, Salary.com's October 2026 data reports an average SEO specialist salary of approximately $96,565 per year.

The middle 50% salary range is approximately $87,333 – $108,622 annually.

This gives businesses a starting point for calculating the employee cost of an internal SEO operation.

3. Content writing, design, and development costs

An SEO specialist can manage the strategy and research, but content production still requires dedicated resources.

For B2B SaaS businesses, the content writer needs to understand the product, its target audience, and the problems the software is designed to solve.

This becomes particularly relevant when writing technical explanations, product comparisons, and content intended to influence software purchasing decisions.

• In the United States, Salary.com's October 2026 figures put the average content writer salary at approximately $74,207 annually, with a middle 50% range of 67,129–82,227. That represents approximately 5,594–6,852 per month.
• For an India-based team, our preliminary specialist-writer budget is ₹10–20 lakh annually. This should be treated as a hiring allowance and validated against the experience and subject expertise required.

Businesses also need to account for design and development support.

A full-time designer or developer may not be necessary within the SEO team. However, their involvement is often required for content assets, website changes, and technical SEO improvements.

These expenses should be calculated based on the hours allocated to SEO work.

4. Total monthly cost of running an in-house AI SEO team

For an in-house team consisting of one experienced SEO specialist and one content writer, here is the estimated monthly cost in the United States and India.

The main consideration with an in-house team is that most of these expenses are fixed. Salaries and software subscriptions remain payable regardless of how much organic traffic or AI visibility the company generates.

An in-house team provides greater control, closer collaboration, and the opportunity to build long-term SEO expertise within the business. However, companies need enough ongoing work to justify the investment and make effective use of the team's capacity.

How much does an AI SEO agency cost?

At the lower end, some providers advertise services for around $1000 per month. At the higher end, retainers can reach $30,000 or more, depending on the resources and services involved.

These are broad indicative price points, not a verified market-wide range.

Based on our initial pricing assessment, we believe B2B SaaS companies can investigate capable agency options within the $2,000 - $10,000 monthly range.

The major difference comes from the scope of work.

An agency providing strategy and recommendations will generally charge less than one responsible for research, content creation, design, technical SEO, and ongoing execution.

1. AI SEO strategy services cost approximately $2,000 - $3,000 per month

If a business primarily needs strategic guidance, it may be able to find an experienced agency charging around $2,000 - $3,000 per month.

At this level, the engagement would focus more heavily on research, analysis, strategy, and recommendations.

The precise deliverables depend on the agency's proposal.

This arrangement can work for businesses that already have

• Content writers
• Designers
• Developers
• Internal marketing resources 

available to implement the recommendations.

For example, an agency may provide the SEO and AI visibility strategy while the company's internal team handles the content and website updates.

The important distinction is between paying an agency to plan the work and paying it to execute the work.

Businesses should verify which responsibilities are included before comparing prices.

2. Full-service AI SEO agencies can cost up to $10,000 per month

Agency costs increase when the provider takes responsibility for execution.

A more extensive engagement may include SEO strategy, keyword and AI visibility research, content production, technical optimization, design, and development support.

Several factors affect the final price:

• The first is the amount of content being produced. An agency delivering a small number of articles every month will have different production costs from one managing a much larger content operation.
• The second is the level of design and development support required. Technical website changes and custom content assets add work beyond research and writing.

Product complexity also affects the amount of research and expertise needed.

For a B2B SaaS business with a highly technical product, an agency may need more time to understand the software, research the target market, and produce accurate content.

These differences can move the monthly fee toward the upper end of the proposed 2,000–10,000 range.

3. Content production costs: AI-assisted vs. human-written content

Content production is another expense that businesses should examine when comparing agency proposals.

There are two broad production approaches in our pricing model:

These figures are preliminary estimates from the article's pricing brief, not verified market averages.

• AI-assisted content typically uses generative AI during the drafting process, followed by human editing and quality control. The lower production cost is generally associated with reduced drafting time. However, the amount of human review included can differ substantially between providers.
• Human-written content involves a writer taking primary responsibility for researching and drafting the article. Prices may increase when the subject requires specialized technical knowledge.

For B2B SaaS businesses, the production process alone should not determine the decision.

Content accuracy, original research, product understanding, and the quality of the final output matter more than whether AI was involved in drafting.

Companies should also confirm whether content production is included in the agency's monthly retainer or charged separately.

4. Why the cheapest AI SEO agency may not be the best option

A low monthly retainer can be attractive, especially for businesses trying to control marketing expenses.

However, price alone does not tell you how much work an agency can deliver or whether the people involved have the necessary expertise.

An agency charging $500 per month may be offering a very limited service. It may also use a production model that does not provide enough research, human review, or specialist involvement for a complex B2B SaaS product.

That does not mean inexpensive agencies always produce poor work. It means businesses need to understand what the quoted price includes.

Before selecting an agency, compare its actual deliverables, relevant experience, work quality, and previous results.

A $2,000 engagement that provides useful strategic guidance may be a better investment than a $500 engagement with limited output. Equally, a $10,000 monthly retainer is difficult to justify if the agency cannot explain what additional work the business receives.

Which AI SEO approach is right for your business? In-house vs. agency

Both approaches can work for B2B SaaS companies. The decision depends on the complexity of the product, the company's internal resources, and how closely it wants to manage SEO operations.

1. Choose an in-house team for complex products and long-term needs

Building an internal team can make sense when a company sells a product that requires substantial technical or industry knowledge.

An in-house team is particularly useful when:

• The product requires deep technical knowledge: Understanding the product is a continuing part of the SEO process, and an internal team can develop this expertise over time.
• Close collaboration is required: An internal specialist can work directly with product managers, sales teams, and other employees to understand how the software works and what potential customers need to know.
• SEO is a long-term investment: Companies with enough ongoing SEO work can build dedicated internal capabilities and retain product and market knowledge within the business.

The trade-off is the continuing investment in salaries, tools, training, and team management.

2. Choose an agency when speed and execution capacity matter

An agency can be a practical option when a company wants to expand its SEO activities without hiring an entire team.

This approach is worth considering when:

• You want to start execution quickly: An established agency with the necessary experience and available resources can reduce the time needed to get started.
• You need access to different specialists: Instead of recruiting separate employees for strategy, content, and technical SEO, you can work with an agency that already has these capabilities.
• Your internal marketing team has limited capacity: An agency can provide additional execution support without requiring the business to build and manage a full internal SEO team.

However, the choice of agency matters. Relevant experience and credible case studies should carry more weight than promises of quick results.

3. Compare operational control and collaboration requirements

The level of control a business wants over its SEO operation is another consideration.

• With an internal team, marketing leaders can work directly with employees, change priorities, and coordinate work across departments. This can be particularly useful for companies that need frequent collaboration around complex product information.
• With an agency, businesses need more structured communication, onboarding, and clear agreements on responsibilities. This can work well for companies comfortable collaborating with an external partner without making the same internal staffing investment.

The best choice depends on how the company wants to operate and how much responsibility it is prepared to manage internally.

How to choose the right AI SEO agency for your business

If you decide to outsource AI SEO, the next step is finding an agency that can support your business requirements. We recommend evaluating agencies based on their industry experience, previous results, and the services included in their pricing.

1. Look for experience with businesses similar to yours

Start by examining whether the agency has worked with businesses that have similar products, target audiences, and marketing requirements.

For B2B SaaS companies, experience with software businesses is particularly relevant. 

The agency should understand:

• How potential customers research software solutions and compare vendors.
• How buyers evaluate product capabilities before making purchasing decisions.
• The technical knowledge required to produce accurate, relevant content.

An agency that understands your product and market will be better positioned to conduct research, develop an SEO strategy, and create content that meets your audience's needs.

2. Review case studies and evidence of results

Ask the agency to share case studies that explain the work they performed and the results they achieved.

Look for evidence across both traditional SEO and AI SEO:

• Traditional SEO: Improvements in relevant keyword rankings, organic traffic, and conversions.
• AI SEO: Experience tracking brand mentions, citations, and recommendations across AI platforms.

Pay attention to whether these results come from businesses similar to yours and whether they demonstrate the services you are planning to outsource.

3. Compare deliverables against the monthly fee

Two agencies quoting the same monthly price may offer very different services. One might focus primarily on research and strategy, while another includes content production and technical SEO execution.

Before comparing prices, review what each proposal includes:

• Content production: Does the retainer include content writing and design support?
• Technical implementation: Are development work and ongoing SEO improvements covered?
• Reporting and execution: Does the agency provide regular reporting and handle implementation, or does it primarily offer recommendations?
• Internal responsibilities: Which activities will your marketing team still need to manage?

Understanding these differences will help you evaluate whether the agency's monthly fee is reasonable for the actual work being delivered.

How to set your AI SEO budget in 2026

Traditional SEO budgets have largely been based on historical traffic, expected organic growth, and attributed revenue. While these metrics remain useful, they don't capture every interaction that influences a purchase.

Kevin Indig and Amanda Johnson discussed this challenge in their October 2026 Growth Memo article on SEO budgeting. Their recommendations for 2027 planning also provide a useful starting point for businesses reviewing their AI SEO investments.

Here are four considerations for setting your AI SEO budget:

Plan SEO capacity around future needs, not historical traffic

68.01% of US Google searches ended without a click, AI-generated answers can also influence buying decisions without generating a website visit.

This makes historical organic traffic an incomplete basis for budgeting. Meanwhile, expenses such as employee salaries, software subscriptions, and technical infrastructure remain largely fixed, even when traffic declines.

A more practical approach is to allocate resources based on the work your team needs to perform:

• Technical SEO: Website optimization and technical improvements.
• Content operations: Research, content creation, and updates.
• Off-site distribution: Content distribution and community engagement.
• AI visibility research: Tracking brand visibility and competitor recommendations across AI platforms.

The allocation should reflect your business priorities. Off-site distribution and community engagement should also receive dedicated time and resources rather than being treated as additional tasks.

Account for the buyer's research activity outside your website

B2B SaaS buyers often research products across multiple platforms before visiting a vendor's website. They may receive recommendations from ChatGPT, read Reddit discussions, or encounter opinions about a vendor on LinkedIn.

These interactions can influence purchasing decisions without appearing in traditional website attribution reports.

There are also differences in visibility across AI platforms. In Kevin Indig's analysis of ChatGPT, Perplexity, and Google AI Overviews, 91% of citations appeared on only one of the three platforms.

This means visibility on one AI platform does not necessarily indicate visibility across others.

When allocating budgets, businesses should consider which platforms their potential customers use and where competitors are being mentioned.

Tools such as Semrush's AI Visibility Index can help identify competitor visibility and citation sources. These findings can guide investments in content production, off-site distribution, and community participation.

Measure AI SEO performance across three levels

Traditional SEO reporting focuses on rankings, impressions, clicks, and organic traffic. For AI SEO, businesses also need to measure visibility that may influence buyers without generating a direct website visit.

We recommend tracking three levels of performance:

Review these metrics together in a monthly dashboard to identify where performance may be changing.

For example:

• If AI visibility increases but branded search remains unchanged, examine whether you're reaching the right audience.
• If branded searches and direct traffic increase but conversions remain flat, investigate potential conversion issues.
• If both AI visibility and branded searches decline, review competitor activity.

While these metrics cannot independently prove AI SEO's contribution, tracking them together provides a better understanding of performance than organic traffic alone.

Divide your AI SEO budget into proven work, experiments, and brand investments

Another consideration is how to distribute your budget across activities with different levels of certainty.

We recommend dividing the budget into three categories:

1. Proven work

Continue funding activities that already contribute to search performance, such as technical SEO, existing content updates, and digital PR.

2. Learning work

Allocate a controlled budget to experimenting with new AI search platforms and AI-assisted marketing workflows. Each experiment should have a clear owner and a defined point for deciding whether to continue, change, or stop.

3. Hard-to-measure investments

Reserve resources for community participation, events, and brand-building activities that may influence buyers without generating directly attributable traffic or conversions.

This approach allows marketing leaders to maintain investments that are already working while testing new opportunities and supporting activities whose returns are harder to measure.

Final observations

AI SEO is becoming an additional consideration for B2B SaaS companies planning their search marketing investments.

Our research found that LLMs generate approximately one session for every two traditional search engine sessions. At the same time, Google's AI Overviews and AI Mode are changing how users discover information within search itself.

Traditional search still accounts for most search demand, so businesses should focus on expanding their existing SEO capabilities rather than replacing them.

Whether to build an in-house team or hire an agency depends on product complexity, available resources, execution requirements, and long-term plans. Regardless of the approach, AI SEO investments should be measured against business outcomes alongside organic traffic and AI visibility.

At Scale Theory, we approach AI SEO as an extension of traditional search optimization. Our AI SEO services help B2B SaaS businesses address visibility across traditional search and AI-generated answers.

The focus is on understanding where potential customers discover software, how the business appears during their research, and what can be done to improve its visibility.

FAQs

1. How much does AI SEO cost per month in 2026?

AI SEO agencies typically cost $2,000 - $10,000 per month. Running an in-house team costs approximately $14,000 - $17,200 monthly in the US or ₹2.71–4.57 lakh in India, excluding design, development, and employment overhead.

2. What expenses should I consider when building an in-house AI SEO team?

The main expenses are an experienced SEO specialist, a content writer, and SEO tools. Software alone can cost around $1,,100 - $1,300 monthly. You should also account for design and development support when needed.

3. What services are included in an AI SEO agency's monthly fee?

It depends on the agency and its pricing. A $2,000 - $3,000 monthly engagement may focus on research, strategy, and recommendations. Higher retainers can include content production, technical SEO, design, development, and ongoing execution.

4. Is it better to manage AI SEO in-house or hire an agency?

An in-house team makes sense for complex B2B SaaS products that require close collaboration and long-term product knowledge. An agency may be better if you want to start quickly without hiring a full team.

5. How should businesses measure the return on their AI SEO investment?

Track AI mentions, citations, branded searches, direct traffic, conversions, and pipeline contribution. Organic traffic alone may not capture how AI-generated recommendations influence potential customers before they visit your website.