Huckleberry Branding’ SEO Strategist, Eric Hebert, contributed to this post
When ChatGPT burst onto the scene, the marketing world had a predictable reaction: panic.
“SEO is dead.”
“Google search is over.”
Then came the acronym avalanche: GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), LLMO (Large Language Model Optimization), and a dozen other variations. Many marketing agencies quickly packaged up shiny new GEO service offerings before anyone fully understood how AI visibility strategy actually worked.
Now, a few years in, the reality is much less dramatic — but far more interesting.
Traditional search isn’t dead. SEO still matters. But search behavior is evolving, and businesses that understand how AI fits into the customer journey have a significant advantage.
To understand how to build an effective AI visibility strategy for your business, it helps to first separate hype from mechanics.
How AI Answer Engines Actually Work
AI assistants like ChatGPT, Gemini, and Claude generate responses using two broad sources of information:
1. Model Knowledge (Training Data)
Large language models are trained on massive datasets that may include publicly available web content, documentation, licensed materials, code, books, and other sources depending on the provider. This built-in knowledge is not updated continuously in real time. It reflects what the model learned during training, up to a certain point.
2. External Retrieval / Grounding
For some queries — especially current events, fact-sensitive topics, or highly specific research questions — AI systems may supplement their built-in knowledge by retrieving live information from the web or other external sources.
This means AI visibility isn’t entirely separate from traditional search visibility. In many cases, the same signals that support strong SEO — accessible content, authority, clear expertise, and digital relevance — can also influence whether your brand appears in AI-assisted discovery.
Why Most AI Visibility Strategies Miss the Mark
A lot of AI visibility strategy advice today sounds suspiciously familiar:
- Improve your website structure
- Speed up your site
- Add schema markup
- Build authority
- Earn backlinks
- Get brand mentions
- Publish useful content
That’s…SEO.
That doesn’t mean developing an AI visibility strategy isn’t worthwhile — it absolutely is. But the idea that there’s some hidden technical trick, secret code, or proprietary AI optimization formula is mostly fiction and hype.
Technical SEO Still Matters
AI systems can’t cite content they can’t access, parse, or understand. That means SEO fundamentals still matter. Action items that should be in both your SEO and AI visibility strategy playbooks include:
- Fast load times
- Clean crawlable architecture
- Logical content hierarchy
- Strong metadata
- Internal linking
- Mobile usability
- Structured content formatting
- Schema markup (sometimes)
But obsessing over technical gimmicks misses the bigger opportunity.
We’ve already seen “AI optimization checklists” pushing things like LLMs.txt files or hyper-specific schema implementations that promise visibility gains.
The evidence just isn’t there. Technical hygiene definitely matters, but technical hacks? Usually not.
Where an AI Visibility Strategy Actually Creates Business Value
We advise clients to focus their optimization efforts — both on and offsite — on mid-funnel decision-making, where buyers are actively researching solutions and narrowing their options.
Think about how buyers use AI:
- “What’s the difference between HubSpot and Salesforce?”
- “Best ERP software for manufacturers under $50M”
- “How much does outsourced PPC management cost?”
- “Top engineering firms for data center site selection”
- “Alternatives to [competitor]”
These aren’t casual informational searches; they are commercial research (aka: “high intent”) behaviors. Buyers are actively searching for and narrowing options. Increasingly, AI is becoming part of that evaluation process.
Brand visibility inside AI-generated answers can be incredibly valuable because it influences high-intent moments.
Real-World Examples of Mid-Funnel AI Visibility
We’ve seen this play out in our own business over and over again. Here are some examples:
Industrial Services Business Finds Branding Agency Using ChatGPT
Recently, a new client told us they found Huckleberry through ChatGPT. When we asked how he found us, the owner walked us through his exact prompts in detail. He didn’t start with a vague prompt like “best branding agency in Nashville.” He started with a highly specific business problem:
“Help me find branding agencies for a new logo and website for our family-owned industrial services business.”
He elaborated on his specific needs and business niche, and ChatGPT returned several options. He continued refining the conversation, narrowing the criteria until he eventually asked the AI to recommend just one agency best suited for the project.
It recommended Huckleberry.
Why? We can’t know with absolute certainty, but we have a strong theory: we had published a case study featuring branding work for a similar family-owned industrial services company. In other words, we had content that clearly demonstrated category relevance, industry understanding, and proof of experience—all signals that matter in mid-funnel evaluation.
Businesses Seeking Brand Refreshes Finds Branding Agency Using Traditional SEO
We’ve seen the same principle at work in traditional search.
Several clients have hired us specifically for logo refreshes, not because we rank broadly for “branding agency” or “logo design”, but because we created a dedicated service page for something we call Brand Extension Explorations—our positioning for strategic logo refresh work. Many agencies offer this service, but few explicitly describe, package, and publish it in a way prospects can actually find.
Visibility doesn’t just come from ranking for broad awareness terms. It comes from showing up when buyers are actively refining what they need, comparing options, and looking for evidence that you’re the right fit.
Our Approach to AI Visibility
We’re not interested in selling AI hype or checklists. Our approach to AI visibility strategy starts with the same question we ask when building SEO strategies: Where in the customer journey would AI visibility actually influence revenue?
Instead of chasing vanity visibility for random prompts, we focus on the following tenets:
Customer Journey Mapping
Understanding where prospects ask research-heavy questions AI is likely to answer.
Competitive Positioning Content
Creating comparison pages, solution explainers, pricing guidance, and thought leadership that AI systems can reference.
Brand Authority Signals
Strengthening digital trust through PR, mentions, backlinks, expertise content, and ecosystem visibility.
Technical Accessibility
Making sure your website is structured so both search engines and AI systems can easily understand it.
Mid-Funnel Opportunity Research
Using tools strategically—not obsessively—to identify commercially meaningful prompts where visibility matters.
The Real Competitive Advantage
The brands that win in AI visibility won’t be the ones chasing technical loopholes.
They’ll be the ones that deeply understand:
- Their buyers
- Their buying journey
- Their competitors
- Their industry language
- Their unique expertise
Because ultimately, AI visibility is just another form of discoverability. And discoverability has always belonged to brands that create genuinely useful, trustworthy content.
The channels may evolve. The principle doesn’t.
SEO isn’t dead. It’s expanding.
AI is changing how people search, but the businesses that benefit most won’t be the ones reacting to every new acronym or gimmick.
They’ll be the ones building strong digital authority, understanding how customers make decisions, and showing up with the right information at the right moment — whether the answer comes from Google, ChatGPT or something else altogether.
An effective AI visibility strategy isn’t about technical tricks. It’s about buyer intent.
