How To Do Topic Research for AI Search

AI Search platforms are fundamentally changing how buyers discover brands. Right now, tools like ChatGPT, Google’s AI Mode, and AI Overviews are shaping purchase decisions before prospects ever reach your website. Yet many businesses remain completely invisible in this new landscape.

Recent analysis of thousands of AI-generated responses across multiple industries reveals a striking pattern. Some websites dominate traditional search but are nowhere to be found in AI Search results. Meanwhile, other sites with modest traditional search visibility are thriving in AI platforms.

We’ll show you how to do topic research for AI Search, the manual way and the fast way, so that you can dominate wherever your customers are searching.

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The 38% Visibility Gap

A recent study examined the overlap between brands with strong traditional search visibility and those appearing frequently in ChatGPT responses. If AI Search Optimisation were simply Search Engine Optimisation (SEO) under a different name, you’d expect nearly 100% crossover.

The actual overlap was just 62%.

This means roughly 38% of websites performing well in traditional search are failing to capture AI Search visibility. The implications are significant. Just because you’re winning in the old world doesn’t guarantee success in the new one. But there’s an opportunity here too. Brands struggling with traditional SEO can still dominate AI Search.

If you’re leading marketing for a large organisation, your content budget shouldn’t just drive page views and impressions. It should drive traffic and conversions. When AI platforms fail to cite your brand during decision-making queries, you’re losing visibility at the most strategic part of the buyer journey.

These aren’t casual browsers. People using AI Search tools arrive exceptionally well-informed and ready to purchase because they’ve received repeated brand recommendations throughout their research conversations.

When AI Search Favours Your Content

Some brands are succeeding across both traditional and AI Search. Take Mailchimp’s comprehensive guide on email marketing. Search Google for “email marketing”, and you’ll find this pillar content piece ranking at the top of organic results. It’s also featured as the first link in Google’s AI overview and cited at the start of the response. Search “What is email marketing?” on Perplexity, and the same Mailchimp article appears as a source.

This content dominates because it’s structured specifically for AI Search.

When Traditional Rankings Don’t Transfer

Other times, strong traditional rankings simply don’t translate. Consider the query “What are the best business accounts in the UK?” Money Supermarket, a comparison site that generates substantial revenue from referral traffic to banks, ranks at the top of Google for this term. Yet in AI Overviews, it’s completely absent. Check Perplexity, and Money Supermarket is nowhere to be found.

What’s happening in these cases?

Sometimes AI tools simply don’t recommend certain website types for specific queries. But more often, the content lacks answers to the subqueries AI Search tools prioritise.

How AI Search Actually Works

Understanding what happens under the hood reveals why traditional content often fails. When you ask an AI tool a question, it frequently runs multiple background searches. For “What are the best bank accounts in the UK?” Perplexity executes numerous related queries, then pieces together answers from all of them to deliver a comprehensive response.

This is called query fan out. A single search fans out into multiple sub-searches. If your content doesn’t answer all those subtopics and you lack visibility for those related queries, you’ll miss crucial AI Search visibility.

Finding Your AI Search Content Opportunities

Here’s how to identify which topics to cover and which subtopics to address in your AI-friendly blog strategy.

The Manual Method

Start with the product or service you want to sell. Then work backwards to identify questions people ask when they’re reasonably close to making a purchase.

For example, if you sell skin cleansers, “good skin cleanser” indicates purchase intent. Someone searching this isn’t just browsing out of boredom. They’re looking for a product to buy.

Enter these queries into Google and observe which site types appear in AI Overviews. This reveals whether AI platforms will cite your type of website for these queries.

Example 1: When Your Site Type Won’t Appear

Search “good skin cleanser”, and you’ll see AI Overviews citing:

• Amazon
• YouTube
• Media sites (British Vogue, Marie Claire, CNN)
• Beauty content sites

Notice what’s missing? Actual skincare brand websites. This suggests Google doesn’t want to cite beauty brands’ own sites for this query, preferring third-party sources instead.

The same pattern appears for “what are the best skin cleansers for acne.” Results include:

• The Guardian
• Pharmacies and retailers (Boots)
• Medical media sites

No brand websites. In these cases, producing excellent content might not matter. If you want product recommendations here, focus on digital PR to get featured in these third-party articles.

Example 2: When Your Site Type Will Appear

Contrast this with “best skincare routines for sensitive skin.” Here, Google readily shows skincare brand websites. CeraVe, a skincare brand, ranks at the top of AI Overviews and appears multiple times in citations.

This is a topic worth covering on your website because Google will cite brand content.

Once you identify queries where your site type appears, examine the content structure. You’re looking for the subtopics these articles answer.

For “best skincare routines for sensitive skin,” the top-ranking article includes these subtopics:

• What is sensitive skin?
• What causes sensitive skin?
• How to manage sensitive skin
• Dry sensitive skin
• Oily sensitive skin

Notice how the content breaks the topic into chunks with detailed answers for each. The paragraph on dry sensitive skin is what Google cited in its AI mode.

Interestingly, this article’s headline doesn’t match the search query. Google likely broke the query into sub-queries and ran those in the background, which is why AI mode results differ from organic search results.

The Challenge of Manual Research

To do this thoroughly, you’d need to:

• Run this process across numerous searches for each core product and service
• Repeat searches multiple times (AI responses vary)
• Track sites consistently ranking and being cited

It’s time-consuming work with no shortcuts.

The Faster Approach: Using AI Visibility Tools

Tools like Semrush’s AI Visibility Toolkit dramatically accelerate this research. Here’s how the process works using a beauty brand example.

Overall Visibility Assessment

Enter your domain to see your overall AI Search visibility score and relative visibility across different AI platforms. You’ll notice trends, like improved AI Overview visibility as Google expands AI Overview usage.

While strong brand visibility might produce a decent overall score, the real opportunity lies in topic research.

Your Performing Topics

This section shows topics and prompts where your website is already cited. You’ll see:

• Individual prompts (e.g., “Dove cherry body wash”)
• Full AI responses with your links
• Visibility score (percentage of times you appear in answers)
• Number of mentions across prompts
• AI volume (monthly search frequency)

Topic Opportunities: Your Growth Engine

This is where the magic happens. This section compares your visibility to competitors, showing all topics and prompts where competitors appear but you don’t.

Select relevant competitors, and the tool analyses thousands of prompts, grouping them into topics. Instead of manually reviewing 15,000 individual prompts, you can focus on roughly 3,000 organised topics.

This represents an enormous time savings compared to manual research.

Prioritising Your Content Topics

With thousands of potential topics, you need filters to identify priorities:

Filter 1: Relevance

Eliminate anything completely irrelevant to your business. If you’re Dove, competitor brand topics like “CeraVe skincare products” aren’t priorities unless you’re creating comparison content.

Filter 2: Commercial Intent

Focus on queries indicating purchase readiness. “What does face cleanser mean?” shows low intent. “Good face cleanser for dry skin” indicates someone actively shopping for a product.

Filter 3: Site Type Compatibility

Because you’re analysing competitor visibility, you know Google will cite branded websites for these prompts. But you can verify by checking Google directly to confirm branded sites appear in citations.

Filter 4: Existing Content Opportunities

Identify whether you already have content that could be optimised for these terms. You might have relevant articles that simply need restructuring or enhancement.

The Content Structure AI Platforms Prefer

AI tools favour pillar content structures organised around topic clusters, not scattered individual articles.

Poor Structure Example

A disorganised content section with mixed topics thrown together in a single category. Articles about skin cleansing, hair care, and various unrelated topics are all jumbled without a clear hierarchy or relationships.

Preferred Structure: Topic Clusters

Imagine covering skincare with a strategic cluster approach:

Main Cluster: Seasonal Skincare

• Winter skincare
  • Moisturisers for winter skin
  • How to deal with dry skin in winter
  • Winter skincare routine
• Spring skincare tips
• Summer skincare tips
• Autumn skincare tips

Each subtopic has its own cluster of related content. This strategic approach makes gaps obvious and creates clear pathways for comprehensive coverage.

Why Thin Content Fails

You might already have content on target topics that’s simply underperforming. Often, this content is too thin to establish authority. It lacks the depth and comprehensive subtopic coverage that AI platforms prioritise when selecting citations.

Additionally, content duplicated across multiple site versions can devastate organic search visibility, further limiting AI Search performance.

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Taking Action on AI Search Visibility

AI Search represents a fundamental shift in how buyers discover and evaluate brands. The 38% of websites invisible to AI platforms are missing opportunities at the most critical moment in the buyer journey.

Success requires understanding how AI platforms structure queries, identifying topics where your site type will be cited, and creating comprehensive content that answers not just the main query but all related subqueries.

The brands that master this now will dominate the recommendations AI platforms make to ready-to-buy customers. Those that don’t risk becoming invisible precisely when prospects are making purchase decisions.

The question isn’t whether AI Search will impact your business. It’s whether you’ll be visible when it matters most.