AI answers have changed some search journeys, but they have not changed every query or every business in the same way. That makes a blanket budget rule hard to defend.
I use 70/20/10 as a first draft when a team needs somewhere concrete to begin. It is my planning heuristic, not a benchmark from research and not a percentage every company should adopt. The point is to make the tradeoffs visible, then change the split when your data says to.
TL;DR
- Treat 70/20/10 as Arthur’s starting planning heuristic, not a universal recommendation.
- Decide the final split from technical health, customer behavior, current visibility, measurement quality, team capacity, and opportunity cost.
- Keep established search work and AI-search work in one plan when that avoids duplicated ownership. Separate pilots when clean accounting helps you judge them.
- Cut line items because they underperform, not because they carry an old or new label.
- Report commercial outcomes first. Use AI-answer presence, citations, and source patterns as supporting diagnostics.
An illustrative 70/20/10 allocation
Suppose a team has $10,000 a month and has already fixed serious crawling and indexing issues. This is how I might draft the first allocation before reviewing its market and performance data:
| Planning bucket | Illustrative amount | Example work |
|---|---|---|
| Established search program, 70% | $7,000 | Technical maintenance, high-intent pages, content updates, digital PR, conversion improvements |
| AI-search work, 20% | $2,000 | Baseline prompt panel, source analysis, public-record corrections, selected content tests |
| Experiments, 10% | $1,000 | One or two time-boxed tests with a hypothesis, owner, and review date |
This example is not a budget calculator. A $10,000 program with a broken ecommerce template should put more into the foundation. A technically sound company with evidence that buyers use AI tools during vendor research may put more into measurement and source work. A team that cannot act on another dashboard should spend less on monitoring until ownership is clear.
Work the reallocation through a real line-item plan
Here is a fictional $10,000 monthly program. The team has no serious indexing blockers, has evidence that buyers use AI during vendor research, and can update existing pages. These amounts illustrate a decision, not market rates or a recommended spend for your company.
| Monthly activity | Before | First test | What changes |
|---|---|---|---|
| Technical maintenance | $1,500 | $1,500 | Protect essential access and indexability work |
| New articles | $3,500 | $1,500 | Commission fewer pieces while checking existing content gaps |
| Existing-page improvements | $1,500 | $2,000 | Give high-intent pages a named editor and revision brief |
| Earned visibility and PR | $1,000 | $1,000 | Keep relevant source and relationship work |
| SEO measurement | $500 | $500 | Preserve query, landing-page, and conversion reporting |
| AI-answer measurement | $500 | $1,000 | Define a fixed buyer-question sample and record variation |
| Cited-source corrections | $0 | $1,000 | Investigate and correct inaccurate or incomplete information |
| Experiments | $1,000 | $1,000 | Fund one explicit test with a review date |
| Conversion improvements | $500 | $500 | Keep the path from useful content to qualified inquiry |
| Total | $10,000 | $10,000 | $2,000 moves out of article volume, not out of search |
The revised plan puts $7,000 into established search work, $2,000 into the two AI-search lines, and $1,000 into experiments. No new retainer is added on top. That classification is for budgeting; it does not mean each activity benefits only one search surface.
Download the editable budget worksheet (CSV). It includes these illustrative amounts plus columns for your owner, deliverable, success measure, review date, and decision. Replace the amounts before using it for your own plan.
Set the decision date before spending
For this example, I would set a 90-day review window as a planning choice:
- First 30 days: confirm the baseline, owners, page sample, and tracking. If access or data is missing, fix that before expanding monitoring.
- Next 30 days: ship a small set of documented page or source changes. Keep a change log and use a consistent prompt sample.
- At the review: compare qualified inquiries, useful traffic, implementation progress, and the sampled answers. Separate a change in the answer from evidence that the work caused it.
Keep a line when it produces useful business results or information that changes a decision. Reduce or stop it when nobody can act on it, the data is too weak to interpret, or another unresolved constraint deserves the money. A 90-day review is not a promise that search results will improve within 90 days.
The short answer: reallocate, do not duplicate
Start with one search plan because technical work, content, analytics, and public information can serve more than one discovery surface. That does not mean the overlap is a known percentage or that every deliverable affects Google and AI answers equally.
Split out a pilot when it has a distinct hypothesis, owner, tool cost, and decision date. Otherwise, keep it in the existing program and tag the work so finance can see what was added, reduced, or stopped.
Why the budget conversation changed
A large behavioral study is useful context.
Pew Research Center studied 68,879 Google searches. In its sample, users clicked a traditional result in 8 percent of visits with an AI summary and 15 percent of visits without one. They clicked a source cited in the summary in 1 percent of visits.
That is useful evidence of changed behavior in the observed sample. It is not proof that every site’s informational traffic has been cut in half, that the effect is permanent, or that AI answers cause the entire difference. Use your own query, traffic, and conversion data to see where the risk is real.
The budget question becomes practical: which current activities produce qualified demand, which protect important visibility, and which new tests could change a decision?
The 70/20/10 framework
This is what each bucket means in my starting heuristic. The percentages are placeholders until the decision variables below are reviewed.
70 percent: the established search program
This covers technical health, indexation, site architecture, content maintenance, high-intent pages, conversion work, and earned visibility. Some of that work may also help systems that retrieve web pages for AI answers, but the effect and overlap are not fixed.
If the site has serious technical or indexing problems, this share will often need to rise because later tests will be hard to interpret. That is a sequencing decision, not evidence that AI systems “punish” technical weakness more than Google does.
20 percent: AI-search-specific work
Possible line items include:
- A baseline prompt panel. Track a small set of buyer questions, answer presence, citations, and sources. Use a tool or spreadsheet that matches the size of the test.
- Source analysis and record correction. Fix factual conflicts on your site and on sources that answer engines actually cite, including incorrect business information.
- Selected content improvements. Rewrite pages only when the page is unclear, incomplete, out of date, or hard for a customer to use. Treat any citation effect as something to measure.
- Governance. Assign an owner, prompt set, sampling method, and review date so results are comparable.
10 percent: experiments
Use this bucket for a small number of time-boxed tests. Every test needs a hypothesis, baseline, owner, cost, and stop or scale date. If the team cannot name the decision a test will inform, do not fund it yet.
What is an AI search optimization budget?
An AI search optimization budget is a planning label for work aimed at understanding and improving visibility in AI-generated search answers. It may include measurement, correcting cited business information, improving source pages, and running controlled tests.
I usually track it inside the broader search plan. A temporary separate line can still be useful when finance needs to isolate a pilot or a new tool. Either way, define what decision the spend should inform and when you will review it.
How much of your SEO budget should go to AI search?
There is no research-backed percentage for most companies. Twenty percent is simply the AI-search slice in my starting heuristic.
Before choosing the number, answer these questions:
- Is the site technically healthy? Unresolved crawling, indexing, template, or conversion problems may deserve the next dollar first.
- Do customers use AI tools in this buying journey? Use interviews, sales-call notes, referral data, and your own search observations. Do not substitute general adoption statistics for customer evidence.
- Where are you visible today? Establish a repeatable baseline across the prompts and markets that matter before buying a large monitoring program.
- What is the commercial value of the affected queries? A few high-intent questions can matter more than hundreds of broad informational prompts.
- Can the team act on the findings? Measurement without an owner or editing capacity becomes reporting overhead.
- What will be reduced or delayed? Compare the expected learning or return with the line item that gives up the money.
- When will you decide again? Set a review date and criteria for stopping, holding, or expanding the allocation.
AI search vs traditional SEO budget
The programs can share people, pages, analytics, and technical work, but the degree of overlap is not known. Keep the shared work visible and separate the measurement questions:
| Planning question | Established SEO view | AI-search test view |
|---|---|---|
| Where do we appear? | Search results and search features | Sampled answers for a fixed prompt set |
| What can we observe? | Impressions, clicks, queries, landing pages | Mentions, citations, cited domains, answer variation |
| What is the business test? | Qualified traffic, leads, revenue, assisted conversions | Whether observed AI visibility contributes to those outcomes or useful learning |
| What is the main measurement risk? | Attribution and rank variation | Small samples, personalized or changing answers, and limited referral data |
Some deliverables will sit in both columns. Others will not. Tag the shared cost instead of inventing a precise overlap rate.
GEO budget allocation by company size
Company size does not determine the right percentage. Maturity and opportunity are more useful:
| Situation | Sensible first move |
|---|---|
| No baseline and limited staff | Run a narrow audit of the buyer questions that matter most, then choose whether ongoing tracking is worth it |
| Strong SEO foundation and clear AI use in the sales journey | Fund repeatable measurement and a small set of source or content tests |
| Serious technical or conversion problems | Keep most spending on those constraints and reserve only enough to establish an AI baseline |
| Multiple brands, markets, or regulated claims | Budget for governance, sampling rules, review, and correction workflows before scaling content |
A small specialist company may have more reason to invest than a large company whose customers rarely use AI tools for the purchase. Apply the decision variables, not a company-size multiplier.
What to cut
Reallocation only works if something else changes. Audit line items with evidence:
- Content nobody uses. Look for pages with no qualified impressions, conversions, assisted value, links, sales use, or learning over a reasonable period. Update, consolidate, redirect, or stop commissioning the pattern.
- Production quotas without a business case. A per-post contract is not automatically bad, but volume is not an outcome. Tie briefs to an audience, journey, and measurement plan.
- Reports nobody acts on. Reduce keyword or prompt tracking that has no owner and never changes a decision.
- Duplicate tools and agency scopes. Map who collects which data and who is expected to respond. Pay once for the capability you need.
Do not protect or cut total search spending on principle. Compare each line with alternatives using qualified demand, risk, learning value, and opportunity cost.
Questions to ask your agency or team before approving the line
Ask for answers that can survive a budget meeting:
- “Which customer questions and markets are in the sample?” A metric without a defined prompt set can drift from month to month.
- “What is the baseline, and how much do answers vary between runs?” One screenshot is not a trend.
- “Which decision will this work change?” The answer should name an action, owner, and review date.
- “Which costs overlap with our existing search program?” Shared work should be tagged, not billed twice.
- “What would make us stop or expand the test?” Agree on the evidence before results arrive.
The takeaway
Use 70/20/10 when a blank spreadsheet needs a first draft, then challenge every number. Technical health, customer behavior, current visibility, commercial value, measurement quality, capacity, and opportunity cost should decide the final allocation.
The useful output is not a fashionable GEO line item. It is a search plan that names what will be funded, what will stop, how results will be judged, and when the team will decide again.
Frequently asked questions
How should I adjust my SEO budget for AI search optimization?
Start with the business decision, not a fixed percentage. Review technical health, customer search behavior, current visibility, measurement quality, team capacity, and the cost of existing commitments. I use 70/20/10 as an initial planning heuristic: 70 percent for established search work, 20 percent for AI-search work, and 10 percent for experiments. Move those numbers when the evidence in your market points elsewhere.
Do I need a separate budget for GEO?
Usually not as a separate cost center. SEO and AI-search work can share technical, content, and measurement resources, but the overlap varies by company. Keep one plan when that improves ownership and avoids duplicate work. Use a separate line only when you need to track a distinct pilot, tool, or team.
Should I cut my SEO budget because of AI search?
Do not decide from AI adoption alone. Cut or reallocate work that fails a business test, such as content with no qualified audience, conversion path, or useful learning. Keep work that protects technical access, supports high-value queries, or produces measurable demand. The right total may rise, fall, or stay flat depending on performance and opportunity cost.
What should an SEO budget include in 2026?
A useful plan can include technical health, content tied to customer needs, authority and public-record work, conversion improvements, measurement, and a small experiments line. The mix depends on the site’s constraints and commercial goals. AI visibility tracking belongs only when the team has a defined prompt sample, a baseline, and someone who can act on the findings.
How do I justify SEO spend to a CFO when AI is reducing clicks?
Use business outcomes first: qualified leads, assisted conversions, revenue, acquisition cost, and the cost of losing visibility on high-intent queries. Pew Research found lower link-click rates in its sample when a Google AI summary appeared, but that study does not prove the effect for every site or query. Add AI-answer presence and citations as diagnostic metrics, not as substitutes for commercial results.
What is an AI search optimization budget?
It is a planning label for work aimed at understanding and improving visibility in AI-generated search answers. It can include measurement, correcting public business information, improving useful source content, and limited tests. It may sit inside the SEO budget or be tracked as a temporary pilot. The label matters less than clear ownership, a baseline, and a decision date.
How much of my SEO budget should go to AI search?
There is no research-backed percentage that fits most companies. I use 20 percent as the middle of a 70/20/10 planning heuristic, then adjust it. A company with no AI visibility baseline may need a small measurement pilot first. A company whose customers regularly use AI tools in the buying process may justify more. A site with serious technical problems may need less until those are fixed.
How should GEO budget allocation change by company size?
Company size is only one variable. A small team may fund one baseline audit and a narrow source-correction project. A larger team may need governance, measurement across markets, and coordination with PR, product, and analytics. Set the allocation from the opportunity, existing gaps, and capacity to act on findings rather than applying one percentage at every tier.
For a visibility baseline and a prioritized implementation plan, see my SEO and AI search strategy service. If you want a second set of eyes on your search-budget allocation, Book a free 30-minute call and bring the spreadsheet.
