Every marketing leader is being asked some version of the same question in 2026: “How much should we spend on AI search?” The honest answer is that there is no reliable benchmark for an “AI search budget” as a separate line item — the discipline is too new, definitions vary, and most of the work overlaps with SEO, content and PR you may already fund.
That doesn't mean you should guess. You can size AI search investment sensibly by starting from what you already spend, identifying the gaps that matter for AI visibility, funding the foundations first and phasing the rest as evidence comes in.
This guide shows how to do that: how AI search relates to your existing SEO and content budgets, what to fund first, how to phase investment over a year, and how to avoid paying twice for the same work. It gives general guidance only; every business's numbers will differ.
Key Takeaways
- Treat AI search as an extension of SEO, content and digital PR budgets rather than a brand-new silo — most of the work overlaps.
- Fund measurement and technical foundations first; they are cheap relative to content and PR and tell you where to spend next.
- Phase investment: baseline (months 1–3), build (months 4–9), scale or cut (months 10–12), with clear decision points.
- Industry surveys show AI is already a significant share of marketing budgets, but definitions are loose — don't copy a percentage blindly.
- Tie the budget to measurable outcomes: AI mentions and citations, referral traffic, assisted conversions and branded search.
What the data says about AI and marketing budgets
Two recent surveys give useful context, with caveats. Gartner's 2026 CMO Spend Survey (401 marketing leaders in North America and Europe, mostly at companies with revenue above $1 billion) found marketing budgets averaged 7.8% of company revenue in 2026, and CMOs allocated an average of 15.3% of marketing budgets to “AI initiatives”. The release doesn't define what counts as AI spend, and it covers far more than search, so it is not an AI search benchmark.
“most marketing organizations are not yet built to capture that value”
— Ewan McIntyre, VP Analyst, Gartner, Gartner 2026 CMO Spend Survey press release
Semrush's June 2026 survey of 481 marketers asked where teams planned to invest. Content creation led (49%), followed by cross-channel brand visibility (46%), AI search optimisation (38%), traditional SEO (36%) and AI visibility tools (25%). Only 14% planned to invest in analytics and measurement — even though 49% said they struggled to measure AI's impact on pipeline or revenue. That mismatch is the most common budgeting error we see.
Size the budget relative to SEO and content
Rather than inventing a new number, map AI search activities onto the budget lines you already have and look for gaps:
| AI search activity | Existing budget line it overlaps | Usually new or extra? |
|---|---|---|
| Crawler access, rendering and technical fixes | Technical SEO / web development | Mostly existing; small extra |
| Answer-focused content and updates | Content / SEO content | Existing; shift in priorities |
| Brand facts, entity data, structured data | SEO / web | Small extra |
| Digital PR, reviews and third-party mentions | PR / reputation | Often extra effort |
| AI visibility tracking tools | SEO tools | New line |
| Prompt research and reporting time | Analytics / SEO | New time commitment |
If you already run a healthy SEO programme, the incremental cost of AI search is often mostly tracking, prompt research and extra PR or review work. If your SEO is under-funded, fix that first: Google says its AI features rely on the same foundations as Search.
“There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary.”
— Google Search Central, AI features and your website
For a view of how SEO costs are usually structured, see our SEO pricing guide and wider marketing budget guide.
What to fund first
- Measurement baseline. A tracked prompt set, AI referral tracking in analytics, and the free reports in Search Console (Generative AI performance) and Bing Webmaster Tools (AI Performance). See AI search KPIs.
- Technical access. Make sure search crawlers can reach and read your key pages; fix rendering and indexing issues.
- Brand and product facts. Accurate About, product, pricing-approach and location information on your own site and key listings.
- Content gaps on high-value prompts. Update or create pages that answer the questions where competitors are named and you are not.
- Off-site presence. Digital PR, reviews and community participation once you know which sources AI tools cite in your category.
- Tools at scale. Paid AI visibility platforms once manual tracking proves the value; our tool buying guide explains what to look for.
Phase the investment over 12 months
| Phase | Focus | Relative spend | Decision at the end |
|---|---|---|---|
| Months 1–3: Baseline | Tracking, audit, technical fixes, facts pages | Low | Which prompts and sources matter most? |
| Months 4–9: Build | Content updates, PR, reviews, structured data | Moderate to high | Are mentions, citations and AI referrals rising? |
| Months 10–12: Scale or cut | Expand what works, drop what doesn’t, add tools | Varies with results | Next year’s budget and ownership |
A phased plan also makes approval easier. Our 90-day AI search plan details the first phase, and building an AI search business case covers how to present it to leadership.
Measuring return on the budget
Return is still hard to prove, so agree in advance which metrics justify continued spend. Some early data is encouraging: Semrush's July 2025 traffic study reported that the average visitor from LLMs was worth 4.4 times the average traditional organic visitor, based on conversion rates. That is one vendor's analysis, and results vary widely by industry, so measure your own. Track:
- Mention rate and citation share across your prompt set.
- AI referral sessions and conversions (ChatGPT, Perplexity, Copilot, Gemini) in analytics.
- Generative AI impressions in Search Console for your key pages.
- Branded search trends and self-reported attribution (“How did you hear about us?”).
- Accuracy: the number of factual errors about your brand found and fixed.
Our guide to measuring AI search ROI goes deeper.
Common mistakes
- Creating a separate AI budget that duplicates SEO work — paying two teams or agencies for the same content and technical fixes.
- Buying tools before defining prompts and KPIs. Dashboards without a plan rarely change decisions.
- Starving measurement. Spending on content while having no way to see whether AI visibility moved.
- Copying survey percentages. A benchmark from large enterprises may be meaningless for a 20-person business.
- Expecting guaranteed placements. No one controls AI answers; budget for influence, not guarantees.
Conclusion
The smartest AI search budget starts small, sits alongside your SEO and content spend, and grows only where measurement shows progress. Fund the baseline and foundations first, then phase content and off-site work against clear decision points.
If you would like help sizing a programme for your business, request a custom quote and our SEO team will scope AI search work around what you already have. For background on how agencies typically structure fees, see AI search services pricing.
Related Guides
- Building an AI Search Process: Roles, Workflows and Cadence
- A 90-Day AI Search Plan: What to Do First
- How to Run an AI Search Audit, Step by Step
Frequently Asked Questions
Is there a standard percentage to spend on AI search?
No reliable benchmark exists yet. Surveys report AI spending broadly, not AI search specifically, so size the budget from your existing SEO and content spend and the gaps you find.
Should AI search have its own budget line?
Usually only for genuinely new items such as AI visibility tools and prompt tracking. Most other work belongs in existing SEO, content and PR budgets.
What is the cheapest first step?
A manual baseline: a fixed prompt set checked in major AI tools, AI referral tracking in analytics, and the free Search Console and Bing Webmaster Tools reports.
How long before we see results?
Technical and factual fixes can show up within weeks; content and PR effects typically take several months. Plan decision points rather than fixed deadlines.
Do we need a paid AI visibility tool?
Not at the start. Manual tracking works for small prompt sets; tools become worthwhile when you track many prompts, markets or competitors.
References
- Gartner 2026 CMO Spend Survey press release — Gartner, May 2026
- Only 22% of marketers have fully integrated AI search and SEO [Study] — Semrush, June 2026
- We Studied the Impact of AI Search on SEO Traffic — Semrush, July 2025
- AI features and your website — Google Search Central
- Generative AI performance report (Search) — Search Console Help
- Introducing AI Performance in Bing Webmaster Tools (Public Preview) — Bing Webmaster Blog, Feb 2026
