Imagine, you open ChatGPT or Perplexity out of curiosity and type a query frighteningly close to your ideal customer search:
‘Best B2B SEO platforms for tracking AI visibility.’
The answer loads. It lists a neat summary, a few recommendations, and even a comparison style explanation. You read carefully.
Your competitors are there. Twice.
You? Nowhere.
Your website is doing “okay” on Google. You rank on page one for a bunch of your core keywords. But inside this answer - the exact place where more and more users are getting their information - your brand does not exist.
That gap between “we rank” and “we are mentioned” is exactly where AI share of voice lives. And if you are serious about the future of SEO, you now have to care about both.
What Is AI Share Of Voice, In Plain Language
The traditional share of voice was simple. You looked at how often your brand appeared in ads, organic rankings, or conversations compared to others. In a world of AI search visibility, things feel more blurry, but the core idea stays the same.
AI share of voice is basically this:
Out of all the AI generated answers, summaries, and overviews in your niche, how often does your brand get cited, linked, or even named compared to others?
Notice how different that feels from just tracking classic rankings. In a normal SERP, you might rank position 3, which is clear and obvious. In an AI answer, you could:
Be one of multiple sources used silently in the background
Get a small link in a “Sources” or “Learn more” area
Be mentioned by name inside the generated paragraph
Or be completely ignored while still being technically “visible” in traditional SEO tools
And for you as a marketer, this raises new questions that older dashboards never had to answer, like:
Are we being cited as a primary reference or just buried as one link among fifteen?
For which topics do AI engines instinctively reach for us vs a competitor?
Are we only visible for branded queries, or do we show up in category-level conversations too?
Once you start thinking this way, you realize something important - rankings alone are not telling you how much of the conversation you own.
Why Rankings Alone Are No Longer Enough
You can be proud of your SEO score, your technical setup, and your blue-link positions, and still lose the new war that is being fought in AI answers.
Here is why relying on only positions is dangerous in 2025 and beyond:
First, AI Overviews and conversational engines compress the decision journey. Instead of scanning 10 blue links, a user sees one tight explanation. If your competitor is the one explicitly mentioned or cited, the user’s perception is:
‘These guys must be the authority.’
Second, answer engine optimization changes what “winning” looks like. It is no longer just about who ranks first, but who is considered reliable enough to be summarized, paraphrased, and quoted. That is a level of trust traditional rank tracking does not fully measure.
Third, users are increasingly lazy in a very human way. If Perplexity or Gemini already compares three tools and clearly explains trade-offs, they may not even scroll further. That means your beautifully optimized landing page might get fewer chances to impress, even if it sits at position 2.
So when you look at your reports and see green arrows, your CMO asks, “Okay, but how often are we showing up inside AI answers where people actually read now?” you need a new KPI. That KPI is an AI share of voice.
The Anatomy Of An AI Answer: Where Your Brand Can Appear
Before you can improve something, you have to see it clearly. So let us break down how AI responses actually “show” brands in a way your dashboards can track.
When you type a query into ChatGPT with browsing, Perplexity, Gemini, or Copilot, you usually see some mix of:
A text answer written in a conversational style
A list of recommended tools, brands, or websites
A source section - tiles, logos, or links
Sometimes inline callouts like “according to [Brand]” or “a report by [Company]”
From an AI SEO perspective, every one of these is a visibility surface. Your brand can show up as:
A named expert mentioned in the explanation
A recommended product or platform in a list
A source tile that the user might click
A deep link to a blog, case study, or feature page
Now connect this to your metrics reality. You have tools that tell you rankings, keyword volumes, and basic AI SEO tools outputs. But none of that fully answers:
How often is my domain used in AI answers per 100 queries on a topic?
For which queries are we cited vs totally ignored?
Are we “trusted” enough to be used as a reference in sensitive queries like pricing, comparisons, or best practices?
Once you start mapping answers this way, your content strategy stops being generic and becomes targeted at how AI actually talks about your market.
How To Measure AI Share Of Voice In A Practical Way
You do not need a PhD-level framework to start. You need a repeatable way to audit queries and connect them to actions. Think of it like building your own mini AI visibility index.
A simple starting method you can adopt internally:
Pick your critical topics
Take 30-50 queries that actually matter for revenue - category terms, “best [solution] tools”, “alternatives to [competitor]”, “how to [problem] for [industry]”.Test them across AI engines
Run these in ChatGPT with browsing, Perplexity, Gemini, and AI Overviews (where available). Note who gets cited, which domains repeat, and which phrases appear.Score your presence
For each query, assign a small score like:Identify patterns instead of obsessing over single wins
You are not chasing one mention; you are looking for clusters. Where do you systematically lose to the same 3-4 competitors? Which topics seem to “trust” your domain more?
Once you have even a scrappy version of this tracking, you can turn it into a real KPI that sits alongside classic metrics like impressions and CTR. Over time, this becomes the foundation of your own AI search visibility reporting.
What Usually Goes Wrong When Brands Check Their AI Presence
When teams first run this kind of audit, the emotional reaction swings between relief and panic. Both are useful if you know how to interpret them.
Common patterns you are likely to see:
You over-index on branded queries. AI engines happily talk about you when someone has already typed your brand. But on “best [category] tools”, you vanish. That means your authority is recognized, but only inside your own bubble.
Long-tail educational content drives more AI mentions than your main product pages. That “boring” in-depth guide you published two years ago might be quietly feeding AI models. Thin feature pages, on the other hand, rarely get cited.
Competitors with strong PR and thought leadership are everywhere. They show up in “according to” statements, original studies, or quotes. AI systems love them because they look like primary sources rather than just another tool.
Your data is invisible because it is locked. PDFs, gated reports, and complex JS-heavy pages are harder for crawlers and models to interpret. If your strongest evidence lives there, your AI share of voice will always underperform your real expertise.
The good news is that none of this is permanent. These engines are constantly re-crawling, re-ranking, and re-evaluating. Which means every improvement in clarity, trust, and structure can translate into better mentions faster than you are used to in old-school SEO.
Content That Gets Cited, Not Just Indexed
Now the real question: what kind of content gets you named, not just crawled?
AI engines tend to favor pages that feel like “answer hubs” rather than random fragments. That means they prefer content that:
Directly addresses the exact question or comparison a user would ask
Includes clear definitions, frameworks, and practical steps
Provides original angles - data, benchmarks, quotes, or strong POVs
Uses language that is easy to lift into a natural sentence
If you want a page to be frequently used in AI answers, build it as if an assistant will scan it and say, “If I had to explain this in 3 lines, what would I grab from here?”
Very often, that leads you to formats like:
“X vs Y” breakdowns that explain trade-offs honestly
Topic deep dives that answer multiple related questions on one page
Opinionated essays where you take a stand instead of staying neutral
FAQ clusters where every answer is written in one-breath, spoken-friendly sentences
It is no accident that this overlaps with answer engine optimization principles. When your content is optimized for being quoted out loud, it is naturally easier to reuse inside AI answers as well.
Where Serplux Fits In: Turning AI Visibility Into A Real Metric
All of this is powerful in theory, but you do not want a workflow that lives in a random Notion doc forever. You need something trackable, repeatable, and visible to your team.
This is where a platform like Serplux becomes less of a “nice AI SEO tool” and more of a command center. Instead of only checking whether a keyword ranks, Serplux can be used to:
Track which keywords are traditional SEO plays vs which lean heavily on AI surfaces
Monitor AI share of voice by logging how often your domain is cited for priority topics over time
Tag keywords by intent surfaces - classic SERP, AI Overviews, answer engines, or hybrid
Connect those visibility patterns to real outcomes like traffic, signups, or demo requests
In practice, that means you stop reporting only “we improved rankings for 50 keywords” and start saying, “We increased our presence in AI answers by 30% for high-intent queries in the last quarter.”
For agencies, this is even more critical. The clients asking “Is SEO dead?” are often the same ones seeing AI answers on their phones every day. Having a clean AI search metrics layer gives you a calm, concrete way to explain:
“No, SEO is not dead. It has moved. And we are tracking that movement on Serplux.”
From Insight To Action: How To Grow Your AI Share Of Voice
Once you know where you stand, the only thing that matters is what you do next month. A simple, realistic playbook you can start applying:
Pick one topic cluster where you are absent in AI answers but strong in rankings. This is where you have authority in Google’s eyes but not yet in AI systems.
Create or upgrade one “answer hub” page for that cluster. Turn thin posts into one powerful resource that covers definitions, comparisons, FAQs, and use cases.
Add spoken-friendly, one-breath style answers inside that page. This makes it easy for AI to reuse your words.
Use Serplux to log AI visibility for 10-15 queries related to that cluster every month. You are not chasing perfection, just upward movement in mentions and citations.
As this loop repeats, your reports slowly shift from pure rankings graphs to something more aligned with how users actually search in 2025 - between search bars, chat windows, and generative interfaces.
And when you finally open Perplexity again and see your brand calmly sitting inside the recommended list - not because you bought an ad, but because the system “chose” you as a reliable voice - that is when AI share of voice stops being a theory and starts feeling like a real, hard-earned asset.
Also Read: Adobe Buys Semrush: What It Means for SEO & AI Search
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