AI Topical Presence
Your Share of Voice score tells you how often you appear. Topical Presence tells you what for. That is the question that explains your score and points you towards what to actually do about it.
The short version
- Google ranks pages. AI builds associations. Topical Presence measures how strongly and broadly a model connects your brand to the topics buyers actually ask about.
- It is the diagnostic layer behind Share of Voice. Two brands with identical SOV scores can have completely different Topical Presence profiles and completely different strategic situations.
- Three components: depth, breadth, and concentration. How strongly you are connected to topics, how many topics, and how evenly spread those connections are.
- Most gaps are missing associations, not displaced ones. The AI simply has not learned to connect you to a topic yet. That is more fixable than being beaten by a competitor who owns it.
Two chapters worth reading first
Topical Presence analysis is built on prompt data. The quality of your results depends on how well your prompts are designed and which channel you are measuring.
Ch. 9 – NLP and Entity Analysis
Topical Presence is built on how AI clusters concepts and connects them to entities. Chapter 9 explains how that works at a linguistic level, which makes it much easier to understand why certain associations exist and how to build new ones.
Ch. 10 – Data Gathering Methods
Topical Presence analysis requires running a lot of prompts across multiple models. Chapter 10 covers how to collect that data at scale without introducing bias that distorts your results.
What Topical Presence actually measures
Not rankings. Associations.
When someone searches Google, the algorithm ranks pages. When someone asks an AI, the model draws on associations it has built over training. These are fundamentally different mechanisms, and they respond to different things.
A page can rank for a keyword without the AI ever associating your brand with that topic. And a brand can have strong topic associations in AI responses while ranking poorly in traditional search. The two do not automatically track each other.
Topical Presence measures the association layer. For each topic that matters in your market, it asks: does the AI connect your brand to this topic, how strongly, and how does that compare to everyone else?
If your Share of Voice is lower than it should be, the most likely cause is that the AI is not connecting you to enough of the topics buyers ask about. Topical Presence shows you exactly which ones are missing and which competitors have claimed them.
The two types of topical gap
Before you start trying to close a gap, it helps to know which kind you are dealing with. They need different approaches.
Missing association
The AI has simply not learned to connect your brand to this topic yet. The territory is available. You just have not claimed it. This is almost always a content coverage problem.
Displaced association
A competitor has built such deep coverage of a topic that the AI connects it primarily to them. Harder to address, but rarer than it appears. Most gaps are missing, not displaced.
How the score is built
Three components, one score
The AI Topical Presence score is made up of three components. Each one measures something different, and together they give a more complete picture than any single number could.
Depth
How strongly the AI connects your brand to each relevant topic, weighted by how important that topic is in your market. A brand with deep associations on high-value topics scores well here even if it does not cover many topics overall.
Depth = sum(freq / marketMaxFreq) x topicWeight
DepthNorm = Depth / maxDepth
Breadth
How many of the core commercial topics in your market the AI associates with your brand. Uses a logarithmic curve so emerging associations still get partial credit even if they are not yet strong.
Breadth = sum(min(1, log(1+freq) / log(1+threshold))) x topicWeight
BreadthNorm = Breadth / maxBreadth
Concentration
How evenly your topic associations are spread. A brand that is strongly associated with one topic but nothing else is fragile. One model update or one competitor campaign can remove most of its AI visibility. High concentration is penalised in the final score.
Concentration = sum(freq / brandTotal)²
TP = (0.45 x DepthNorm + 0.40 x BreadthNorm – 0.15 x Concentration) x 100
Illustrative weights. Breadth is weighted almost as heavily as depth because a narrow brand is a vulnerable brand.
Same depth, very different scores
This comparison shows why depth alone is not enough. Both brands have the same depth score. Brand B scores significantly higher because its associations are broader and less concentrated.
Brand A is well known for one thing. Brand B is well known for many things. If the market shifts or a competitor claims Brand A’s core topic, its AI visibility could drop dramatically. Brand B is much more resilient. Building breadth is not just about growing your score. It is about protecting it.
Interpreting your score
Here is how to read your Topical Presence score and what it signals strategically.
| Tier | Score | What it means | What to do |
|---|---|---|---|
| Category leader | 75+ | Broad, consistent AI presence across your market | Own the territory. Defend breadth against new entrants. |
| Mid-tier | 45 to 74 | Visible but patchy. Strong on some topics, absent on others. | Identify specific gaps and fill them systematically. |
| Niche or emerging | 20 to 44 | Narrow signal. Known for one or two things, little else. | Build breadth urgently before concentration becomes a liability. |
| Minimal presence | Below 20 | Largely absent from AI responses in your category. | Start from scratch. Focus on foundational content coverage first. |
When you find a gap
Not all gaps have the same fix
When the AI is not connecting you to a topic you should own, the cause matters. Publishing more content is only the right answer in some cases. Here is how to tell which situation you are in.
Product gap
Your product does not actually cover this capability. Publishing content about it creates AI visibility for something you cannot deliver. Before writing anything, check whether this is really a gap you should close.
Roadmap conversation first.
Documentation gap
Your product covers it but it is not documented in a way the AI can find and associate with your brand. The capability exists. The content that would let the model learn about it does not.
Technical writing conversation.
Content depth gap
It is documented, but the coverage is too thin for the AI to have built a meaningful association. A single page or a brief mention is rarely enough. The model needs to see consistent, substantive coverage across multiple sources.
Content strategy conversation.
Waikay extracts the topics, use cases, and concepts associated with your brand across every AI response it tracks, then scores your presence across depth, breadth, and concentration. The competitive quadrant plots your Topical Presence score against your Share of Voice so you can see at a glance whether your associations are translating into visibility.
