How do you do SEO with AI? Tools, limits, and Google's rules

How do you do SEO with AI? A five-step workflow

The route to productive use is to place the tool in the middle of the process rather than at its beginning: a person determines the goal, the tool speeds up drafting, and the person checking it has the final say. In practice, the following workflow works:

1. Goal and audience: Write down whom the page will serve, which question it will answer, and what the business actually knows about the subject.
2. Real data: Give the tool Search Console queries, frequently asked customer questions, and product or service information as context.
3. Draft: Ask the tool for keyword groups, a heading structure, meta options, or a schema draft.
4. Verification: Check every number, rule, address, and link individually against its source.
5. Measurement: After publication, monitor the page in Search Console; changes in clicks and impressions become input for the next revision.

The tool saves time in steps two and three; it does not replace steps one and four. The basic operation of search engine optimization is explained separately in the article what is SEO; the table below places the tool’s contribution and the human checkpoint side by side for each task.

AI in keyword research and grouping

AI SEO tools save the most time at this stage because the work is largely linguistic. Given the seed phrase “wooden dining table” for a furniture store, a tool can generate dozens of variations by size, material, room type, and purchase intent, and divide them into groups seeking information, comparing, and ready to buy.

The weak point is numbers. A language model does not measure how many times a phrase is searched each month; the volume it states is an estimate and often has no basis. Volume and competition information comes from real data sources such as the Google Ads keyword planner, query data in Search Console, or SEO platforms that perform measurements.

Points to watch when grouping

• Variations answering the same question are collected on one page; a separate page is not created for every minor wording difference.
• The intent distinction is confirmed by looking at search results for the relevant query; the tool may misread intent.
• For local phrases, district and neighborhood names are limited to areas the business actually serves.
• The spelling of brand and product names is compared with the manufacturer’s official source rather than accepted from the tool’s output.

The first item is where scaled content risk begins; Google’s policy on this subject is addressed in a separate section below.

Content outlines: Structure from the tool, knowledge and experience from people

The phrase “adding structure to original content” in Google’s guidance describes appropriate use for content well. The tool is productive for creating a heading hierarchy, revealing omitted subquestions, simplifying a long text, or turning scattered notes into orderly paragraphs. The business’s own process, product dimensions, delivery times, and problems encountered in the field are information the tool cannot know by itself.

The people-first content page asks whether content provides original information, research, or analysis and goes beyond rewriting other sources. The same page lists effort as a criterion when assessing main content; generating large amounts of text with generative AI without manual checking and editing is included among examples of low effort.

What should a good content prompt include?

• The page’s target reader and the main question it will answer
• Verified information belonging to the business: service scope, area, process steps
• A list of expressions not to use and claims not to make
• Addresses of official documents to cite as sources
• A note that the output is a structure to work on rather than publication-ready text

It also matters that the same page explicitly states Google has no preferred word count. Asking a tool for a specific length often increases filler rather than information.

Titles, meta descriptions, alt text, and schema drafts

The generative AI guidance applies accuracy checks not only to body text but also to metadata that may appear in search results: the title element, meta description, structured data, and image alternative text are included. Because these fields are short, it is easy to get ten options from a tool in a few seconds; errors also stand out more in short text.

• Give the tool the page’s actual text; providing only a keyword leads to promises being written that do not exist on the page.
• Remove expressions such as “free,” “same day,” and “best price” if they have no counterpart on the page.
• Alt text describes what actually appears in the image and is not turned into a keyword list.
• Count character limits separately without trusting the tool’s statement.

What should be expected from a tool in a schema draft?

AI can quickly write a JSON-LD structure for an FAQ section or business information. Google’s general structured data guidelines, however, require markup to accurately represent page content and prohibit marking up content that is invisible to readers or misleading. A common mistake by tools is adding a rating, address, or opening hours that do not appear on the page.

The draft is checked with the Rich Results Test before publication. On the same page, Google states that even correct markup passing the test is not guaranteed to appear as a rich result in search.

Technical checks, internal linking, and report interpretation

AI SEO tools work as explainers in technical and analytical tasks; they do not see the website themselves and interpret only the data given to them.

Technical check

Asking what a robots.txt rule means, why a redirect chain causes problems, or what an indexing error in Search Console requires usually produces an understandable explanation. The proposed fix, however, is tested again on the live website using Google’s own tools such as URL Inspection. Comprehensive crawling, speed, and indexing issues are addressed as a separate work item within the technical SEO service.

Internal link suggestions

If the tool is given the website’s actual URL list, it produces useful suggestions on which pages a new article can link to and which anchor text would sound natural. Without a list, the tool may invent addresses that seem plausible but do not exist on the website. Every suggested link is opened in the browser and checked before publication.

Report interpretation

When a table exported from Search Console or Analytics is given to the tool, a brief breakdown of declining pages and rising queries is produced quickly. The risk is that the tool establishes a cause-and-effect relationship between two changes and presents an explanation absent from the table as proven. Every number in the summary is compared with the source table, and the interpretation is read alongside the dates of changes made on the website.

Common AI mistakes in SEO work and the right approach

In SEO work with AI, most errors arise from publishing output without checking it rather than from the tool’s limitations. The most common errors and their corresponding approaches can be listed as follows:

• Unsupported numbers: Search volumes, market shares, or percentages beginning with “according to research.” The right approach is to remove numbers whose sources cannot be shown.
• Nonexistent sources: Links that look real but do not open and quotations attributed to the wrong person. The right approach is to open every external link and read its content.
• Outdated information: Interfaces, rules, or product names changed after the training data. The right approach is comparison with current official documentation.
• Local information errors: Incorrect districts, imaginary addresses, guessed opening hours. The right approach is matching against the business’s own records.
• Turkish that sounds translated: Literal transfers of English expressions and transitional sentences repeated in every paragraph. The right approach is reading the text aloud and simplifying it.
• Template repetition: The same text on many pages with only the city or product name changed. The right approach is to add information unique to each page or merge the pages.

The final item opens the door to a risk greater than an error on a single page: a spam policy violation that may affect the entire website.

Scaled content abuse: Where the line is crossed

Google’s spam policies define scaled content abuse as creating large numbers of pages to influence search rankings rather than help users. This is the rule a website doing SEO with AI needs to know most closely. The key point is that the production method is not considered decisive: whether pages are written manually or produced with tools, they may constitute a violation if they add no value. Some examples listed in the policy are:

• Creating large numbers of pages adding no value to users with generative AI or similar tools
• Scraping feeds, search results, or other content and turning it into large numbers of pages through automated transformations such as synonyms or translation
• Combining content from different websites without adding value
• Creating multiple websites to conceal that content is produced at scale
• Publishing large numbers of pages containing search phrases but making no sense to readers

A moving company publishing hundreds of pages for every district of Istanbul with only the district name changed approaches this definition, regardless of whether the text was prepared using AI or copy and paste. At the end of the policy, Google recommends excluding such content from Search if it exists on the website; merging pages or adding real local information to each are also options to consider.

The self-assessment questions on the people-first content page point in the same direction. Using extensive automation to produce content on many subjects and restating what others say without adding much value are among the situations Google considers warnings that the approach to content creation should be reconsidered.

The difference between bulk production and supervised use

AI-assisted SEO is implemented in two different ways in the market, and the difference lies in the process rather than the tool. Comparing common practices side by side without naming anyone clearly shows which approach aligns with Google’s documentation:

The practical answer to how to do SEO with AI is also in this table. In supervised use, the tool is still present at every stage; what changes is that responsibility for the final text remains with a person. For businesses considering building their website with AI, a similar boundary is discussed in the article building a website with AI.

Onur Freelance’s service for AI and SEO

Based in Maltepe, Onur Freelance has provided web design and digital marketing services since 2019. The AI SEO service, meaning work on the website’s visibility in AI answers such as ChatGPT search and Google AI Overviews, is offered together with the SEO service rather than as a separate package. The SEO service starts from 9,000 TL per month.

No guarantee is given for search rankings or citation in AI answers; which page is shown depends on Google’s and the relevant platforms’ own systems. Onur Freelance is not an official support channel for Google or any AI platform and does not speak on these companies’ behalf. At the start of the work, the website’s current condition is reviewed during a free initial assessment, and the scope is clarified in the initial discussion.