# AI SEO: how to use AI for SEO work and how to optimise for AI search

URL: https://serpel.app/blog/ai-seo

Updated: 2026-10-10

AI SEO means two different things: using AI to do SEO work faster, and optimising your site so AI search products can find and cite it. AI helps most with research, briefs, internal linking, audits and automation, but it invents facts, and Google’s spam policies treat mass-produced pages without added value as scaled content abuse however they are made. This guide covers both meanings, what to automate, what to check by hand and which categories of AI SEO tools exist.

## Key takeaways

- AI SEO has two meanings: using AI as a tool for SEO work (research, briefs, internal links, audits, automation) and optimising for AI search products such as ChatGPT search and Google’s AI Overviews. They need different skills and different measurements.
- AI is strong at drafting, clustering and summarising, and weak at facts. Google says generative models predict a likely sequence of words instead of retrieving facts, so verify every number, quote and claim and review metadata too.
- Google’s spam policies define scaled content abuse as generating many pages mainly to manipulate rankings, however the content is created. Using generative AI to produce many pages without adding value is one of the listed examples.
- Give your assistant real data instead of asking it to guess. APIs and MCP servers, including Serpel’s, let an agent read rankings, search data and audit results as tools.
- Google says optimising for AI search is still SEO. Focus on crawlable, original, quotable content, and measure citations with prompt checks and the AI reports in Search Console and Bing Webmaster Tools.

## What does AI SEO mean?

AI SEO is a label for two jobs that people often mix up. The first is **using AI for SEO**: asking a language model or an agent to help with keyword research, content briefs, internal linking, technical audits and reporting. The second is **optimising for AI search**: making your content easy for ChatGPT search, Google’s AI Overviews and AI Mode, Perplexity and Copilot to retrieve and cite. People use “AI SEO” for both. “AI for SEO” and “AI in SEO” lean towards the first, and “SEO for AI” towards the second.

**The two meanings of AI SEO**
| Question | Using AI for SEO | Optimising for AI search |
| --- | --- | --- |
| Goal | Do SEO work faster and with less manual effort | Be retrieved, quoted and cited in AI answers |
| Typical tasks | Research, briefs, internal links, audits, metadata drafts, reporting, automation | Crawler access, server-rendered content, quotable passages, entity clarity |
| Main risk | Wrong facts, generic pages and scaled content abuse | Chasing unproven tactics and buying guaranteed citations |
| How you measure it | Time saved, error rate, quality of the shipped pages | Citation and mention rates, AI report impressions, AI crawler hits |
| Go deeper | The sections below | [GEO vs SEO](https://serpel.app/blog/geo-vs-seo), [LLM SEO](https://serpel.app/blog/llm-seo) and [answer engine optimization](https://serpel.app/blog/answer-engine-optimization) |

## How can you use AI for SEO work?

Use AI where a wrong answer is cheap to catch and a right one saves hours. The pattern that works in every case below is the same: give the model real data, let it propose, and have a person check before anything ships.

### Research and clustering

A model is good at grouping hundreds of queries by intent, spotting gaps in a topic and summarising what the top pages cover. It is not a source of numbers. Never ask it for search volumes, difficulty scores or rankings, because it will produce plausible figures that are not measurements. Take those from a data provider or your own Search Console, and let the model work on the data you give it.

### Briefs and outlines

Google says generative AI can be useful when you research a topic and to add structure to original content. A brief that lists the question, the audience, the sources to use and the facts to include is a good job for a model. The expertise, the original data and the examples must come from you, because a page that only restates what exists adds nothing for a reader.

### Internal linking

Give the model a list of your URLs with titles and ask which pages should link to which, with suggested anchor text. Then verify that each suggested URL exists and returns status 200 before you add a link, because models invent paths. A crawl is the easiest way to get a trustworthy list of pages. With the Serpel CLI you can export it as JSON.

```bash
serpel crawl pages --crawl <crawl-id> --limit 200 --json > pages.json
```

### Technical audits and fixes

An audit produces a long list of findings. An assistant can explain each one, group them by cause and propose a code change, which is where it saves the most time for developers. Our [SEO audit report example](https://serpel.app/blog/seo-audit-report-example) shows what such findings look like, including a link finding where 31 of 43 flagged targets turned out to be fine after a human re-check.

### Metadata and structured data drafts

Titles, descriptions, alt text and JSON-LD are all fair game for a first draft. Google’s [guidance on generative AI content](https://developers.google.com/search/docs/fundamentals/using-gen-ai-content) says the review duty applies to metadata as well, such as title elements, meta descriptions, structured data and image alt text. Validate markup with a tool such as our free [schema validator](https://serpel.app/tools/schema-validator) before you publish it.

### Automation with APIs, agents and MCP

The step beyond chat is to let an agent read your SEO data itself. The [Model Context Protocol](https://modelcontextprotocol.io/docs/getting-started/intro) (MCP) is an open-source standard for connecting AI applications to external systems. Anthropic created it and contributed it to the Agentic AI Foundation, a fund of the Linux Foundation, in December 2025. Google’s [Search Console API](https://developers.google.com/webmaster-tools/v1/how-tos/search_analytics) exposes the data of the Performance report in batches of up to 25,000 rows, and Bing has a similar Webmaster API, covered in our [Bing Webmaster Tools guide](https://serpel.app/blog/bing-webmaster-tools).

Serpel’s remote [MCP server](https://serpel.app/developers/mcp) offers 13 tools that let Claude Code, Cursor, Codex and other agents read rankings, search data, crawl issues and recommendations and, after a `serpel scan`, relate findings to the routes in your code. Only the keyword research tool spends credits, and only within a budget you approve. Our guide to the [Google Search Console MCP](https://serpel.app/blog/google-search-console-mcp) shows the same idea for Google’s data. Serpel does not write articles for you. It supplies the data and findings your own assistant works from.

## Where does AI go wrong in SEO?

Google puts the core problem plainly: generative models don’t retrieve facts, but predict a likely sequence of words, so outputs can contain inaccuracies, known as hallucinations, and it is critical to fact-check AI-generated content. The 2025 paper [Why Language Models Hallucinate](https://arxiv.org/abs/2509.04664) by Adam Tauman Kalai and co-authors argues that models guess when uncertain because training and evaluation procedures reward guessing over admitting uncertainty. In SEO that shows up in predictable ways.

**AI tasks in SEO and what to check before you ship**
| Task | How well AI fits | Check before you ship |
| --- | --- | --- |
| Keyword metrics | Poor. A model has no measurements | Take numbers from a data provider or Search Console, never from the model |
| Statistics and quotes | Poor. It can invent both | Find the primary source yourself and link it, or leave the claim out |
| Clustering and summarising | Good | Spot-check a sample of clusters against the real queries |
| Briefs and outlines | Good | Add the original data and expertise only you have |
| Internal link suggestions | Good, given a real URL list | Every URL exists and returns 200 |
| Metadata and schema drafts | Fair | Length limits, accuracy and a validator run |
| Full articles | Risky | Fact-check every claim, add original input and decide whether the page deserves to exist |

## What does Google say about AI-generated content?

Google does not ban AI content. Its [guidance on using generative AI](https://developers.google.com/search/docs/fundamentals/using-gen-ai-content) says to review AI-generated content manually before publishing, and warns that generating many pages without adding value for users may violate its spam policy on scaled content abuse. The [spam policies](https://developers.google.com/search/docs/essentials/spam-policies) define that abuse as many pages generated for the primary purpose of manipulating search rankings and not helping users, and they apply no matter how the content is created. The examples Google lists include:

- using generative AI tools or similar tools to generate many pages without adding value for users
- scraping feeds or search results to generate many pages, including through automated transformations such as synonymizing or translating, with little value for users
- stitching or combining content from different pages without adding value
- creating many pages whose content makes little sense to a reader but contains search keywords

The tool is not the test. The purpose and the value are. Google’s [helpful content guidance](https://developers.google.com/search/docs/fundamentals/creating-helpful-content) also asks whether the use of automation or AI is clear to visitors through disclosures, and says such disclosures are useful where someone might wonder how the content was created. If you publish AI-assisted pages, a short note on how they were made costs nothing.

> **A checklist for AI-assisted pages:** Would this page exist if search engines did not? Does it contain something a competitor’s page does not? Has a person checked every claim and every link? Did you avoid creating one page for every minor variation of a query? If you cannot answer yes to all four, do not publish it.

## How do you optimise for AI search?

This is the second meaning of AI SEO, and Google’s position is that it is still SEO. Its [optimisation guide](https://developers.google.com/search/docs/fundamentals/ai-optimization-guide) says you don’t need special files, markup or rewriting for its AI features, and that unique, non-commodity content will likely matter more than any other suggestion in it. The practical list is short:

1. Let the crawlers in, and keep pages indexable. See [AI crawlers](https://serpel.app/blog/ai-crawlers).
2. Serve the main content as server-rendered text. See [JavaScript SEO](https://serpel.app/blog/javascript-seo).
3. Lead each section with the answer and support it with attributed facts. See [answer engine optimization](https://serpel.app/blog/answer-engine-optimization).
4. Cover the follow-up questions a reader would ask, on one useful page.
5. Measure citations over time instead of trusting a single answer. See [how to rank in ChatGPT](https://serpel.app/blog/how-to-rank-in-chatgpt).

## Which AI SEO tools exist?

AI SEO tools fall into categories, and a good choice depends on the job, not on a league table. We do not rank products here. Google also advises caution with third-party tools that promise ranking success or claim to use internal Google metrics, because no third-party tool has access to its internal ranking or AI systems.

**Categories of AI SEO tools**
| Category | Good for | Watch out for |
| --- | --- | --- |
| General-purpose assistants | Drafting, clustering, summarising and explaining findings | No live SEO data by default, and confident mistakes |
| SEO suites with AI features | AI summaries and writing help on top of keyword and audit data | Check which data is measured and which is generated |
| Content optimisation and writing tools | Briefs, outlines and first drafts | Generic output and scaled content abuse if used for volume |
| Technical audit tools | Finding crawl, indexing, speed and markup problems, with explanations | Heuristic findings need a human check |
| AI visibility trackers | Checking whether AI answers cite or mention your domain | Answers vary, so a single check is a sample |
| APIs and MCP servers | Giving your own agent real rankings, search data and audit results | Permissions and spending limits for paid calls |

Before you adopt any of them, ask where the data comes from, whether the tool shows its sources, whether you can export the results and who reviews the output. Serpel sits in three of these categories: a technical audit that renders JavaScript, an AI visibility tracker for ChatGPT with web search and Google AI Overviews, and an API, CLI and MCP server. Compare it with others in our guide to the [best AI visibility tools](https://serpel.app/blog/best-ai-visibility-tools).

## A practical AI SEO workflow

1. **Ground the model in your data** Connect Search Console and Bing, run a crawl and give your assistant those results, through exports or an MCP server, instead of asking it to guess.

2. **Let AI propose, not publish** Ask for clusters, briefs, link suggestions and fix proposals. Treat the output as a draft that a person owns.

3. **Verify facts and add original input** Check every number, quote and URL against a primary source, and add the data, examples and expertise the model cannot supply.

4. **Ship in small batches** Publish a few pages or changes at a time, so you can see what worked and roll back what did not.

5. **Measure and re-crawl** Read the Search Console performance data, re-run your rank and AI visibility checks and crawl again to confirm that the technical fixes landed.

```bash
serpel crawl compare --project <project-id>
```

## Frequently asked questions

### What is AI SEO?

AI SEO means two things. One is using AI to do SEO work, such as research, briefs, internal linking and audits. The other is optimising your site for AI search products such as ChatGPT search and Google’s AI Overviews, so they can find and cite your content. Google says the second is still SEO.

### Can you use AI for SEO without being penalised?

Yes. Google does not ban AI-generated content. Its spam policy on scaled content abuse targets generating many pages mainly to manipulate rankings without adding value, however the content is created. Review the output, add original value and do not mass-produce thin pages.

### Which AI SEO tools are best?

It depends on the job, and no honest list can rank them all. General assistants suit drafting, audit tools find technical problems, AI visibility trackers measure citations and APIs or MCP servers feed your own agent real data. Check where a tool’s data comes from and avoid any that promise guaranteed rankings or citations.

### Can AI do keyword research?

It can cluster and group keywords you give it and suggest topics, but it should not supply search volumes or difficulty scores, because a language model has no measurements and will produce plausible numbers. Take metrics from a data provider or Search Console.

### Is AI search replacing SEO?

There is no evidence of that. Google says optimising for its generative AI features is still SEO, and AI answers still depend on pages that are crawlable and indexed. SEO now includes measuring citations in AI answers as well as rankings.

## Sources

- [Google Search Central: Google Search’s guidance on using generative AI content on your website](https://developers.google.com/search/docs/fundamentals/using-gen-ai-content), accessed 2026-10-10
- [Google Search Central: Spam policies for Google web search](https://developers.google.com/search/docs/essentials/spam-policies), accessed 2026-10-10
- [Google Search Central: Creating helpful, reliable, people-first content](https://developers.google.com/search/docs/fundamentals/creating-helpful-content), accessed 2026-10-10
- [Google Search Central: Optimizing your website for generative AI features on Google Search](https://developers.google.com/search/docs/fundamentals/ai-optimization-guide), accessed 2026-10-10
- [Kalai et al., Why Language Models Hallucinate (arXiv 2509.04664)](https://arxiv.org/abs/2509.04664), accessed 2026-10-10
- [Model Context Protocol: What is MCP?](https://modelcontextprotocol.io/docs/getting-started/intro), accessed 2026-10-10
- [Linux Foundation: Agentic AI Foundation announcement](https://www.linuxfoundation.org/press/linux-foundation-announces-the-formation-of-the-agentic-ai-foundation), accessed 2026-10-10
- [Google for Developers: Query your Search Analytics data with the Search Console API](https://developers.google.com/webmaster-tools/v1/how-tos/search_analytics), accessed 2026-10-10