AI Keyword Research in 2026: How to Find Keywords That Rank on Google and Get Cited by AI

Keyword research used to answer one question: what are people typing into Google?

In 2026, it needs to answer two questions: what are people typing into Google, and what topics are AI systems like ChatGPT, Perplexity, and Gemini pulling into their answers?

These are not always the same lists. Traditional keyword tools measure search volume, which is the number of times a phrase is searched per month. But AI search does not work on search volume. It works on subject authority, brand name recognition, and content structure. A phrase that gets 10,000 monthly searches might never appear in a ChatGPT response. A very specific question with 200 monthly searches might be exactly what triggers an AI citation if your content answers it clearly and your site is known as a trusted source on that topic. This is part of why AI search traffic converts at a much higher rate than standard Google clicks.

This guide covers how to do keyword research for both audiences.

---

Why traditional keyword research is missing half the picture

Traditional keyword tools like Ahrefs, Semrush, and Moz are built around Google's search model. They tell you how many people search for a phrase, how hard it is to rank for, and what the competing pages look like.

That data is still valuable. Google still sends the majority of search traffic and you absolutely need to rank there. But there are two gaps in the traditional approach that are growing in 2026.

Gap 1: AI searches do not have volume data

When someone asks ChatGPT "what's the best way to audit my site for AI visibility?" there is no search volume you can look up for that question. AI search is natural and question-based. The queries are longer, more specific, and far more varied than typed Google searches. Traditional keyword tools cannot measure this directly.

Gap 2: Ranking on Google and being cited by AI require different types of content

Google ranks pages. AI systems quote sources within answers. To rank on Google, you need site authority, backlinks, and content that matches the topic. To be cited by an AI, you need your content to be structured in a way that makes it easy to pull a specific answer from it: a definition, a list, a number, or a step-by-step process.

A page can rank on page one of Google and still never appear in a ChatGPT response if the content is not set up to give direct answers. And a page can be quoted frequently by AI tools for very specific questions even if it ranks modestly in traditional search.

The goal of modern keyword research is to find topics that give you a shot at both.

---

Part 1: Traditional keyword research (still essential)

The basics of keyword research have not changed. You still need to find terms your target audience searches for, where you have a realistic chance of ranking, and that connect to what you actually offer.

Understanding search intent

Every keyword has a reason behind it. Match your content type to that reason:

• Informational ("what is AI SEO"): Blog posts, guides, explainers
• Commercial ("best AI SEO tools", "AI SEO audit reviews"): Comparison pages, tool roundups
• Transactional ("hire AI SEO consultant", "AI SEO audit pricing"): Service pages, landing pages
• Navigational ("OptiScale Advisors login"): Do not target these for new content. Just make sure your own brand pages are well set up.

Using a sales page for an informational keyword, or a blog post for a buying keyword, is a common mistake that wastes effort no matter how good the content is.

Keyword difficulty and site authority

The biggest mistake new sites make is going after high-volume, high-competition keywords before they have the authority to rank for them.

A site with a Domain Rating (DR) of 20 has almost no chance of ranking for "SEO tools" because sites with DR 80 and above fill those results. The same site has a real chance of ranking for "AI SEO audit checklist for small business" if they create genuinely useful content.

Practical rule: Target keywords where the top-ranking pages have site authority scores within 20 points of yours, or where the top results come from sites that are not well-optimised for the specific question despite having high overall authority.

The tools that still matter

Ahrefs Keywords Explorer: the strongest mix of keyword data accuracy, competitive analysis, and click rate estimates. Best for: finding what your competitors rank for and spotting gaps.

Semrush Keyword Magic Tool: excellent for filtering by intent and finding questions. Best for: building out topic clusters and finding long-tail variations.

Google Search Console: free and underused. Shows you what searches your site is already getting impressions for, at what position, with what click rate. Best for: finding quick wins where you are ranking between position 8 and 15 and a content update could push you to page one.

AlsoAsked: maps out the "People Also Ask" question tree for any topic. Best for: finding the specific questions your audience is asking that you have not covered yet.

AnswerThePublic: creates question-based and phrase-based keyword ideas. Best for: content ideas and finding angles competitors have not covered.

Building a keyword list: the practical workflow

1. Start with five to ten starting keywords: the core phrases that describe your service or topic area
2. Run each through Ahrefs or Semrush to generate hundreds of variations
3. Filter by intent to separate informational, commercial, and transactional keywords
4. Filter by difficulty: for a new site, target keywords with difficulty scores below 30; for more established sites, you can push into the 40 to 60 range
5. Identify topic clusters: group related keywords together so you are building content on a topic, not just writing one-off posts
6. Check the Google results page for each priority keyword: look at what is actually ranking and ask whether you can create something clearly better

---

Part 2: Keyword research for AI search visibility (the new layer)

This is where 2026 keyword research parts ways with older approaches. AI search optimisation is not about finding keywords with high search volume. It is about identifying the topics, questions, and named entities that AI systems draw on when building answers in your subject area. This is the foundation of Generative Engine Optimization (GEO).

How AI systems decide what to cite

AI search tools like Perplexity and ChatGPT with web search turned on do not rank pages the way Google does. Instead they:

1. Identify the topic of the person's question
2. Search for and pull in relevant content
3. Combine that content into an answer
4. Credit the sources they drew from

To get credited, your content needs to be: findable (not blocked to AI crawlers), structured so it is easy to pull a direct answer from, and clearly about the specific topic being asked. A solid AI technical SEO audit will check all three of these.

This changes how you think about keyword research. Instead of asking "what phrase should I rank for?" you ask "what questions is my target audience asking AI tools, and does my content give a clear, quotable answer?"

Researching AI search topics

Because AI search queries are not tracked by volume, you need a different research method.

Method 1: Ask AI tools directly

Open ChatGPT, Perplexity, and Gemini and ask the questions your ideal client would ask. Notice:

• What sources do they cite? Those are your benchmark competitors for AI visibility.
• What format do they use in their answer? That tells you what structure your content should follow.
• What questions do they answer poorly? Those are your content opportunities: topics where there is a gap in quotable content.

For example, if your business is AI visibility consulting, search in Perplexity: "how do I get my business to appear in ChatGPT results?" Note every source cited. Then ask: does my site appear? If not, why might those sites be cited instead of mine? What do they have that you do not? Better structure, more specific answers, more mentions on other sites?

Method 2: Find the question layer beneath your keywords

Traditional keyword tools show you what people search. AlsoAsked shows you the question tree that Google's "People Also Ask" boxes reveal. Those questions are often very close to what people ask AI tools, because both are trying to answer specific questions rather than just point to a website.

For any topic you are creating content on, run it through AlsoAsked and map out every branch of the question tree. Then ask: does my article answer all of these questions? Which ones are missing?

Method 3: Watch Reddit, Quora, and industry forums

The questions people ask in online communities are very close to the questions they ask AI tools. Search your core topics on Reddit and look at what questions come up over and over. These are strong content opportunities because they represent real questions without satisfying answers: exactly the gap AI search is trying to fill.

Identifying quotable keyword opportunities

Not every keyword is worth optimising for AI citation. Focus on topics where:

The question is specific, not a brand or navigation search. "What is the difference between SEO and GEO?" is a question an AI will answer. "Ahrefs login" is navigation. Focus on question-type searches.

There is a clear, direct answer your content can give. Topics with a clear definition, process, or comparison are easier to pull into AI answers than topics that need a lot of personal judgment or opinion.

You have or can build genuine expertise. AI tools draw heavily from sources that are consistently quoted across many different places. A site that covers one narrow topic deeply is more likely to be recognised as an authority than a site that covers many topics lightly.

Your competitors in AI search are beatable. Check who is currently being cited by AI tools for your target topic. If all citations come from Wikipedia, major industry publications, and sites with DR 80 and above, you have a harder path. If citations include mid-sized specialist sites, you have a more realistic shot.

The named-entity keyword layer

Traditional keyword research focuses on phrases. AI search is built on named entities: specific people, organisations, products, and concepts. Finding the entities most relevant to your topic is a new layer of keyword research that directly affects your AI search visibility.

For any topic cluster you are building content around, map out the key named entities:

• Which tools and products are most commonly discussed in this topic area?
• Which named experts, researchers, or professionals are seen as authorities?
• Which organisations publish trusted research on this topic?
• What are the exact technical terms (not vague descriptions) used by people in the field?

Then check: does your content use these specific names, or does it use vague general terms instead? "AI language models" is vaguer than "ChatGPT, Claude, and Gemini." The specific names are what AI tools use to recognise and sort your content.

Action: For your existing articles, do a name-check audit. Find every case where you used a vague general term and replace it with the specific name. This helps both Google's understanding of your content and your chances of being cited by AI tools.

Structuring keywords for both audiences

The goal is to find keywords where the same piece of content can rank on Google for volume-based searches and be cited by AI tools for question-based searches. These often sit at the intersection of:

• A topic with meaningful Google search volume (500 or more monthly searches)
• A specific question within that topic that AI tools get asked often
• A clear answer that can be written as a definition, list, or step-by-step process

Example: The keyword "AI SEO audit" has reasonable search volume and is a topic people ask AI tools about. A page targeting that keyword can rank on Google for the phrase and be cited by AI tools for questions like "how do I audit my site for AI search visibility?" if the content includes a clear definition of what an AI SEO audit is, a structured checklist, and specific steps.

That is the keyword research target in 2026: topics where one well-structured, specific, entity-rich piece of content can serve both audiences.

---

Building your topic cluster strategy

Rather than targeting individual keywords, the most effective approach for both Google ranking and AI visibility is building subject authority: becoming the most complete resource on a specific topic area.

For each core topic you want to own:

1. Create a main pillar page covering the topic broadly. This targets the higher-volume, broader keywords.
2. Create supporting articles covering specific parts of that topic in depth. These target long-tail keywords and specific AI search questions.
3. Link the supporting articles to the pillar page and to each other. This builds subject authority in Google's eyes and creates a complete knowledge base that AI tools can draw from.

For OptiScale Advisors, the core topic is AI search visibility. A well-built topic cluster might look like:

• Pillar: Complete guide to AI search visibility
• Supporting article: How to check if your business appears on ChatGPT
• Supporting article: Why your business is not showing on AI search
• Supporting article: AI technical SEO audit guide (including GEO checks)
• Supporting article: AI keyword research for GEO (this article)
• Supporting article: How to appear on Perplexity and Gemini

Each supporting article targets specific long-tail keywords and specific AI search questions. Together they build subject authority that benefits the whole domain.

---

Priority keyword categories for 2026

Based on what we are seeing in 2026, these keyword types perform strongly in both traditional and AI search:

"How to" + specific process
These match informational intent on Google and are highly quotable by AI for question-based searches. Example: "how to optimise your site for ChatGPT citations."

Comparisons and differences
"X vs Y" and "difference between X and Y" formats are consistently cited by AI tools because they answer the common question of how two things relate. Example: GEO vs SEO: what is the difference.

Definitions of new concepts
New terms in fast-moving fields (AI search, generative engine optimisation, AI overviews) have low competition on Google and high AI citation potential because there are few established sources. Example: what is generative engine optimisation.

Checklists and step-by-step guides
Numbered processes are one of the most commonly cited content formats in AI responses. Example: "AI visibility audit checklist."

"Why" questions
Explanatory questions are asked to AI tools constantly. Example: why is my business not appearing on ChatGPT.

---

Measuring success: metrics for both audiences

Track these separately for Google and AI:

Google performance (Google Search Console)

• Impressions: are you appearing in results for your target keywords?
• Average position: where are you ranking?
• Click rate: are people clicking when they see you?
• Clicks: total traffic from organic search

AI visibility (check manually, every month)

• Does your brand appear in ChatGPT, Perplexity, or Gemini responses for your target topics?
• Are your articles being cited as sources in AI-generated answers?
• Which competitors are being cited that you are not?

Content performance signals

• Time on page: are people reading your content all the way through?
• Pages per session: are people exploring your site after landing on an article?
• Return visits: are people coming back? This is a strong signal of genuine value.

---

Common mistakes to avoid

Targeting keywords beyond your current authority. Focus on realistic opportunities first. Build authority in a narrow area before expanding.

Ignoring your Google Search Console data. Your best quick wins are keywords where you are already getting impressions but have a low click rate. These pages just need better titles, meta descriptions, and content updates, not entirely new articles.

Writing for search volume without thinking about AI structure. A 2,000-word article full of vague paragraphs might rank but will not be cited by AI tools. Add definition blocks, numbered steps, and FAQ sections to every important article.

Treating AI visibility as separate from SEO. The same content improvements that help you capture the highlighted answer box at the top of Google results (clear answers, structured formatting, specific names and details) also improve your AI citation chances. They work together, not against each other.

Forgetting to check whether AI crawlers can access your site. If your robots.txt file blocks GPTBot or ClaudeBot, you are invisible to those systems no matter how good your content is. Check this as part of your technical SEO audit.

---

Your action plan

Week 1
Run a keyword check in Google Search Console and find your ten highest-impression, lowest-click-rate pages. These are your fastest improvement opportunities.

Use AlsoAsked to map out the full question tree for your two or three most important topic areas. Find the gaps in your current content.

Week 2
For your highest-traffic articles that get views but no clicks: add FAQ sections, short definitions, and numbered process steps. Rewrite titles and meta descriptions based on the frameworks in this guide.

Ask ChatGPT, Perplexity, and Gemini the questions your ideal client would ask. Write down who gets cited and what format those answers take.

Week 3
Find three to five specific questions your audience asks AI tools that your site is not currently answering well. Create or update content to answer them directly and clearly.

Week 4
Set up a monthly tracking routine for AI visibility. Create a list of ten to fifteen questions to test in ChatGPT and Perplexity each month. Track whether your citations grow as you improve your content.

Ongoing
Refresh your keyword research every three months. AI search is moving fast. Topics that have no strong sources today may become crowded in six months. Move early on new terms appearing in your industry.

---

Keyword research in 2026 is not harder than it was. It is just wider. The sites that build subject authority with structured, specific, answer-ready content will win in both Google rankings and AI citations. The sites still writing general content for search volume alone will see their traffic shrink as AI search captures more of the queries they used to rely on.

---

Frequently asked questions

---

---

Related reading

• AI technical SEO audit guide
• How to check if your business appears on ChatGPT
• Why your business is not showing on ChatGPT
• What is Generative Engine Optimization (GEO)?
• GEO vs SEO: what is the difference?