While optimizing for AI visibility is multifaceted (and our knowledge of it evolving), we see a few themes in how brands are set up to get AI mentions—all related to how well machines can understand your brand’s value, who it serves and why they’d buy from you, and how they can measure your expertise.
Why care about brand visibility in AI answers? Buyer behavior has shifted. Prospects use ChatGPT, Claude, and other AI tools to research their purchases. They ask questions, refine their needs, create short lists, and evaluate vendors—all without visiting your website. And they trust what AI tells them.
This is an opportunity and a challenge for marketers. It’s a new channel to grow visibility, one with new priorities. If you’re not visible where your buyers are looking, you’re invisible.
Over 16 years, Two Octobers has helped hundreds of businesses improve search and now AI visibility and drive real results. That work points to four problems that consistently compromise visibility in both traditional search and LLMs.
These four common gaps keep brands out of AI answers. Here’s what to do about each one.
Clarity about who you are and what you do
Can both people and machines understand what you do and who you serve?
If your business name resembles competitors or uses confusing abbreviations, you’ve already made it harder for AI to understand who you are. Clear naming is the foundation.
But there’s a deeper problem we see: the language you use to describe your business doesn’t match the words prospects search for solutions. You might use aspirational marketing language for investors and visionary customers. AI needs concrete information instead: what category you’re in, who you serve, and what problems you solve. If your homepage speaks abstractly while prospects search specifically, you’ve created a gap.
Here’s what to do
Ask someone outside your industry to read your homepage and About Us page. Can they quickly tell you what you do and for whom? If not, augment existing copy with clear descriptions of your category, ideal customer, and concrete benefits—using the language your buyers actually use.
Not enough audience-need content
Do you talk about how your product solves prospects’ needs?
Your marketing highlights features, benefits, and differentiators—but there’s a blind spot. You’re selling to someone solving a need, so content that speaks about that problem helps prospects find you through AI, plus confirms you’re the right solution.
When prospects ask AI for help, they’re asking about their problems: What solutions exist? Which fits their situation? The more your content answers prospect questions in prospect language, the more material AI has to connect you with the right buyers. When your content helps prospects see themselves, it helps AI see your ideal customers there too. That makes AI more likely to surface you as the right answer for the specific prospects you’re interested in.
Here’s what to do
Identify the core problems your best prospects have and the questions they ask. Answer those questions on your product pages, in case studies, and in articles. Give AI—and your prospects—material that connects your solution to their specific needs.
Read more: How Two Octobers uses AI-powered research to generate question-based buyer personas
Great content, not connected
Do your readers discover all the knowledge you’ve built?
If your business has been around a while, you’ve probably built plenty of content—blog posts, articles, videos, podcasts. But is it easy to find? Scattered and disconnected content means readers and AI can’t see the full depth of what your brand’s expertise and advice.
Linking related pieces together and creating resource hubs does two things. First, it helps readers discover the depth of your knowledge and engage with more of it. It also signals to search engines and AI that you have genuine topical authority.
That’s how machines understand what you truly know and what builds credibility with both humans and AI.
Here’s what to do
Map your content by topic. Identify where you have strong clusters around a single theme. Turn those clusters into resource pages featured on your homepage and key product pages. Add links between related articles so readers can easily navigate your expertise, and AI can see the full picture.
Read more: Guide to SEO Topic Clusters
Holes in demonstrated expertise & authority
Can prospects see your expertise on the page?
You have authority. Your product works. Your customers prove it. But what if that credibility isn’t clear enough to AI?
Prospects and AI don’t always start on your homepage. They land on blog posts, service pages, or case studies. On each page, they need to understand immediately who wrote this and how credible they are.
Blogs should have author bylines with credentials, trustworthy facts cited to their source, sufficient depth for their topic, and visible publish dates.
The more you share expertise—and prove it with credentials and facts—the more confidence AI has in surfacing you as a trusted answer.
Here’s what to do
Pull up three recent blog posts. Does each have a named author with credentials visible on the page? Look at your service pages and case studies. Are client logos, partnership logos, years in business, or outcome metrics visible where prospects will see them? If not, you’re making it harder than necessary to trust you.
The four gaps that keep you invisible
These four problems determine whether you’re part of the AI conversation or invisible in it. You could have the best product in your category, but if AI can’t understand who you are or why prospects should trust you, they won’t find you.
Your buyers are researching in AI tools right now. Will they find you?
Ready to close these gaps? Let’s start with an audit of where you stand. We’ll look at your positioning, your content, and your visibility across the web—and show you exactly where the opportunities are. Read our latest AI visibility case study. Then, let’s start a conversation →
