There is a strange anxiety spreading through marketing departments right now.
It usually starts with a simple question from a CEO, a sales director, or an entrepreneur who has read one too many LinkedIn posts:
“How do we make our brand appear on ChatGPT?”
The question sounds modern. Strategic, even. It gives the impression that there is a new territory to conquer, a new search engine to dominate, a new set of rules to learn before competitors do.
And, of course, an entire market has already appeared to sell the answer.
GEO. LLMO. AEO. GSO. AI visibility. Conversational readiness. Citation monitoring. Optimization for generative engines. New names, new dashboards, new promises. The packaging changes, but the mechanism is very familiar: create urgency around something unclear, give it an acronym, then sell certainty where certainty does not exist.
The problem is not that companies are interested in how AI systems retrieve, summarize and recommend information. They should be. The problem is that many are skipping the most basic strategic question:
Is our own digital home good enough to deserve being found?
Before investing budget in the dream of being mentioned by ChatGPT, companies should look at the only digital asset they truly control: their website.
Not their LinkedIn page.
Not their YouTube channel.
Not their paid media campaigns.
Not their visibility inside someone else’s platform.
Their website.
Because if your website is weak, unclear, outdated, slow, generic or built only as a corporate brochure, the problem is not that AI cannot find you. The problem is that even when people find you, there is not enough value to keep them there.
The GEO fantasy: treating AI as if it were Google with a nicer interface
The first misunderstanding is technical, but its consequences are very practical.
Many people are trying to apply old SEO logic to generative AI as if ChatGPT, Gemini, Claude or Perplexity were simply search engines with a conversational interface. This is comforting because it suggests that the same game can continue with new labels: find the ranking factors, optimize the content, monitor the position, sell the service.
But large language models do not work like a traditional search results page.
There is no stable “page one” of ChatGPT. There is no universal SERP for generative AI. There is no fixed ranking where your brand is number three today and number two tomorrow. There is no public, deterministic algorithm that tells us exactly why one source is cited, another is ignored, and another is compressed into a generic summary.
Yes, AI tools may use search engines. Yes, they may retrieve external sources. Yes, they may rely on structured, fresh and authoritative information. But moving from that to “we can optimize your brand for ChatGPT” is a very large leap.
It is also a very convenient leap for those selling services around the anxiety of the moment.
The uncomfortable truth is simpler: nobody fully controls how these systems will interpret, retrieve, synthesize or present information. Their behavior changes. Their sources change. Their models change. Their interfaces change. Their commercial policies will change too.
So when someone sells GEO as a precise science, the real product is not visibility. The real product is reassurance.
And reassurance is expensive when it is built on unstable foundations.
AI is not an index. It is closer to a user.
A better way to think about AI systems is not as databases you can manipulate, but as strange, probabilistic users that arrive with questions.
They do not “browse” your website like a human customer. They do not “rank” your pages like Google. They do not “understand” your brand in the way your sales director would like. But they do process available information, identify patterns, connect meanings and generate plausible answers based on the context they can access.
This changes the practical question.
Instead of asking, “How do we teach AI to recommend us?”, a company should ask:
- Are our answers clear enough to be understood?
- Are our pages structured around real customer questions?
- Is our expertise visible, or hidden inside vague corporate language?
- Do we publish content that has a point of view?
- Do we update what we say when the market changes?
- Do we own the knowledge we are asking platforms to distribute?
These are not GEO questions. They are marketing questions.
Actually, they are business questions.
Because the way a company explains itself is not a cosmetic layer added at the end. It is part of the value it creates. A confused website often reflects confused positioning. Generic content often reflects a generic strategy. A poor FAQ section often reflects a company that has never seriously listened to the doubts of its customers.
This is where the conversation becomes more interesting than the current AI buzz.
Your website is not a brochure. It is your source of truth.
Many companies still treat the website as a static object. Something to redesign every few years, fill with institutional content, connect to campaigns, then forget until the next rebranding project.
That approach was already weak in the age of search. In the age of AI, it becomes even more dangerous.
A website should be the company’s source of truth: the place where its positioning, expertise, answers, cases, language, proof and point of view are organized in a coherent architecture.
If LinkedIn is where you start conversations, your website is where those conversations should become structured knowledge.
If YouTube is where you distribute video, your website is where video should become part of a useful customer journey.
If newsletters nurture relationships, your website should preserve the knowledge generated by those relationships.
If AI systems look for answers, your website should be one of the clearest places where those answers exist.
This is not nostalgia for owned media. It is strategic realism.
Platforms are useful, but they are not home. They are rented spaces with changing rules. Social reach can decline. Algorithms can shift. Content can be buried. AI systems can exclude, misread, summarize or never surface what you publish.
Your website is different because it is the place where you can design the whole context.
You can decide what matters.
You can connect topics.
You can update content.
You can create depth.
You can build trust over time.
You can turn scattered expertise into a visible asset.
That is why “publish at home first” is not a conservative idea. It is one of the few rational responses to a digital environment becoming more unstable, more intermediated and more dependent on systems companies do not control.
The real battlefield is the middle funnel
There is another mistake hidden behind the obsession with appearing in AI answers: many companies still think content strategy is mainly about top-of-funnel visibility.
They want traffic. They want awareness. They want generic educational content that attracts large audiences. But on broad topics, most companies will always struggle to compete with Wikipedia, media outlets, large publishers, marketplaces, global brands and institutional sources.
At the opposite end, low-funnel content is usually already present in some form: product pages, service pages, contact forms, demos, commercial pages.
The real opportunity is in the middle.
The middle funnel is where people are no longer just curious, but not yet ready to buy. It is where they compare options, clarify doubts, evaluate risks, look for examples, test expertise and try to understand whether a company really knows what it is talking about.
This is where most websites are weak.
They say what the company does, but they do not help the customer think.
They present services, but they do not explain choices.
They list benefits, but they do not address objections.
They claim expertise, but they do not demonstrate it through useful answers.
For marketing managers and entrepreneurs, this should be the real priority. Not “How do we appear in AI?”, but “How do we become the best answer for the questions that matter before a buying decision?”
That means creating content around real problems, such as:
- what customers misunderstand before contacting you;
- what they compare incorrectly;
- what risks they underestimate;
- what internal objections slow down decisions;
- what language they use when they describe their needs;
- what information sales teams repeat every week;
- what questions appear in meetings, emails, support tickets and proposals.
This is not content production as decoration. This is content production as infrastructure.
Do not ask ChatGPT before asking your customers
One of the most absurd habits of the current phase is asking AI what customers want before speaking to actual customers.
AI is useful. Very useful. It can help organize interviews, cluster questions, rewrite explanations, create drafts, extract patterns, generate alternatives and speed up production. But it should not replace direct contact with the market.
If you want to build content that works, talk to people.
Talk to clients.
Talk to lost prospects.
Talk to your sales team.
Talk to customer service.
Talk to people outside your sector and ask what they do not understand.
Study the words they use before you impose your internal terminology.
Then use AI to transform that raw material into a stronger content system.
This distinction matters. Companies do not need more generic AI-generated articles. The web is already full of polished, empty content that sounds correct and says almost nothing. What companies need is proprietary knowledge translated into useful formats.
That requires listening first.
Then structuring.
Then publishing.
Then updating.
AI can accelerate the process, but it cannot replace the meaning behind it.
AI video Q&A: not one-click magic, but scalable usefulness
This is where AI becomes genuinely interesting for a company website.
Not because it allows you to create “content in one click”. That is the childish version of the promise. The real value is not producing more stuff faster. The real value is producing more specific, more useful, more consistent content around the questions customers actually ask.
An AI-generated Q&A video is a good example.
Imagine taking the questions that prospects repeatedly ask your team and turning them into short, clear video answers. Not generic promotional videos. Not corporate theatre. Practical answers that help people understand what you do, how you work, what to expect, what to evaluate and how to make better decisions.
With AI-based video production, these assets can become much more flexible than traditional video content. They can be produced in different languages, adapted for different markets, updated when information changes, and distributed across channels without rebuilding the entire production process every time.
But again, the strategic point is not the technology.
The point is not saying, “We made a video with AI.”
The point is saying, “We can now answer more customer questions, with greater consistency, in more languages, and keep those answers updated over time.”
That is a completely different level of usefulness.
A video Q&A can live on the website, next to the relevant service page. It can include a transcript, so the content becomes readable and searchable. It can be transformed into FAQ sections, short clips, LinkedIn posts, newsletter content and sales enablement material.
In other words, the video is not just a piece of content. It becomes part of the company’s knowledge architecture.
And yes, this also makes the website more useful for AI systems that may be looking for clear, structured answers to users’ questions. But that is the consequence, not the starting point.
First, be useful to customers.
Then let distribution channels, search engines and AI systems do what they can with that usefulness.
The strategic risk: everyone optimizing themselves into sameness
There is also a deeper issue that marketing managers should take seriously.
If every company follows the same GEO recipes, the result will be the same as every previous wave of optimization: sameness.
Same article structures.
Same “ultimate guides”.
Same FAQ blocks.
Same neutral tone.
Same keyword logic.
Same generic expertise.
Same content written to please the imagined machine rather than the real customer.
This is strategically dangerous.
Competition does not reward companies that become indistinguishable. If everyone tries to make a living in the same way, with the same content patterns and the same borrowed language, the market compresses them into alternatives.
The goal is not to sound like everyone else because someone said AI prefers clear answers.
The goal is to be clear and distinctive.
A company needs its own language, its own perspective, its own way of framing problems. Not artificial originality. Not creativity for its own sake. But a recognizable point of view that helps customers understand why this company, and not another, should be trusted.
This is where website strategy, content strategy, brand strategy and AI readiness meet.
Your website should not only answer questions. It should answer them in a way that reveals how your company thinks.
Because that is what creates difference.
So, what should companies actually do?
Before buying another “AI visibility” service, companies should take a more concrete path.
Start with an audit of the website, but not only from a technical SEO perspective. Look at it as a customer would. Look at it as a sales tool. Look at it as a knowledge base. Look at it as an AI-readable source of truth.
Ask yourself:
- Is our positioning clear in less than a minute?
- Do our pages answer the questions customers really ask?
- Do we explain our method, or only list our services?
- Do we have content for the middle funnel?
- Are our best insights trapped in sales calls and presentations?
- Do we update old content, or only publish new content?
- Do we have video, FAQs, articles, cases and data connected in a coherent way?
- Is our website useful enough to be worth returning to?
If the answer is no, the priority is not GEO.
The priority is to build a better digital home.
That means designing a content architecture around customer questions, business priorities and proprietary expertise. It means using AI to accelerate production, not to replace thinking. It means turning internal knowledge into public assets. It means publishing at home first, then distributing intelligently.
LinkedIn, YouTube, newsletters, communities, search and AI tools are all valuable. But they are channels.
They should amplify your house, not replace it.
The point is not to ignore AI. The point is to stop worshipping the buzz.
None of this means companies should ignore generative AI. That would be just as naive as blindly chasing every new acronym.
AI is changing how people search, learn, compare and decide. It is changing how content is summarized, how answers are produced and how authority is perceived. Marketing teams must understand this shift and adapt.
But adaptation does not mean panic.
It does not mean paying for imaginary certainty.
It does not mean outsourcing strategy to people who discovered AI three months ago and now sell themselves as specialists in a discipline that has no stable rules.
The smarter move is more grounded: build assets that make sense regardless of the next platform update.
Clear positioning.
Useful content.
Structured answers.
Updated knowledge.
Customer language.
Video explanations.
Multilingual assets.
A website that behaves like a real source of truth.
This is less fashionable than promising to “rank on ChatGPT”.
It is also much more likely to create value.
At Playmarketing, we believe companies need a different conversation about AI and marketing. Less noise. Less acronym fever. Less obsession with tricks. More strategy, more semantic architecture, more customer understanding, more owned content.
Because before you ask an AI to recommend you, your company should become worth recommending.
And that work starts at home.
Your website is home.
Everything else is distribution.
p.s. want more project directions? It’s a click away from here: info@playmarketing.it
