How to prepare your company website for AI search? GEO guide for companies
Author
Piotr Rompca
The way we look for information is changing faster than many companies have realized. Customers still use Google, but increasingly they are no longer just looking for a list of websites. They are looking for an answer, comparison, recommendation, explanation of a problem or a shortcut to a decision.
AI systems play an increasingly important role in this process: Google AI Overviews, ChatGPT Search, Perplexity, Gemini, Claude, Copilot and other tools that can collect information from many sources and prepare a ready-made answer for the user.
This means an important change for companies. A website is no longer just a place where a user goes after clicking on a Google result. It can also be a source of information that AI will use to build a response. It may be cited, omitted, summarized, or replaced by a competing source.
Therefore, preparing a company for AI search does not involve writing a few texts “for ChatGPT”. This is too narrow an approach.
It’s about organizing the entire visibility ecosystem: website, content, technology, brand, data, opinions, sources of trust, analytics and customer acquisition channels.
A company that wants to be visible in the new search model should stop thinking only by asking:
“How to get clicks from Google?”
And start thinking more broadly:
“How to be present when the customer asks a question, compares options and makes a decision?”
We write more about the change in the search method in the article:
We are no longer looking for sites. We are looking for answers. How does AI change customer search and decisions?
Check out the article
What does securing your business mean in the era of AI Search?
Securing your company in the era of AI Search means preparing it to be understandable, credible and accessible to users, search engines and AI systems.
It’s not about optimizing one subpage at a time. It’s a process that involves several layers.
The company should ensure that:
- the brand was clearly described,
- the offer was orderly,
- the website was technically available,
- the content answered real questions from customers,
- the data was readable by humans and robots,
- opinions and mentions confirmed credibility,
- analytics showed impact, not just movement,
- the company was not dependent solely on one customer acquisition channel.
In practice, securing a company involves reducing the risk that a customer will ask AI to solve a problem and the company will not respond, even though it could actually help him.
| area | what needs to be secured |
|---|---|
| brand | consistent description of the company, specialization and advantage |
| page | indexation, speed, structure, content availability |
| content | answers to questions, comparisons, data, case studies |
| external sources | opinions, mentions, publications, industry profiles |
| analytics | GA4, GSC, AI traffic, brand search, conversions |
| channels | SEO, AI Search, direct, newsletter, social media, YouTube |
| sale | quality of leads, customer questions, decision stage |
This is important because AI does not analyze the company solely based on one subpage. Response systems try to understand the whole picture: who the company is, what it does, whether it can be trusted, where else it appears on the web and whether its content helps the user make a decision.
We organize the basic concepts related to GEO, AIO and AEO in a separate article
GEO vs AIO vs AEO. How are new AI search engine positioning different?
Check out the article
Starting Point Audit: This is where you need to start
Preparing for AI mining shouldn’t start with writing new articles. First, you need to look at where the company stands today across the search ecosystem.
This is the diagnostic stage. Without it, it is easy to invest in activities that do not solve the real problem.
It’s worth checking a few things first.
Firstly,
whether the website is properly indexed and available to search engines. If the most important subpages are not visible, blocked, slow or poorly constructed, AI systems may also have problems using them.
Secondly,
whether the AI correctly understands the company. It is worth checking how ChatGPT Search, Perplexity, Gemini, Claude or Google AI Overviews describe the brand, offer, specialization and competition. If a company is omitted or described incorrectly, it is a signal that there is a lack of coherent information on the Internet.
Thirdly,
you need to analyze the content. Not only in terms of ranking in Google, but also in terms of whether they are suitable for use as a response snippet. Are they specific? Do they answer decision-making questions? Do they include examples, data, comparisons and conclusions?
Fourth,
you need to check the data and analytics. Does GA4 measure conversions? Do we know which subpages generate queries? Can we distinguish information traffic from sales traffic? Do we observe brand queries and traffic from AI tools?
Such an audit should cover:
indexation and page structure,
robots.txt and sitemap.xml,
the most important service, product and category pages,
blog and guide content,
brand visibility in Google AI Overviews and AI Search tools,
competition visibility,
consistency of company data on the Internet,
opinions and external sources of trust,
GA4 and Google Search Console configuration,
quality of leads and conversions.
Only after such an analysis can you decide whether the bigger problem is the technique, content, brand, analytics, external authority or lack of presence in new search places.
A strong brand is the most important safeguard against changes in AI
The company’s most lasting protection against changes in search is a strong, clear and recognizable brand.
It’s not just about the logo, colors or advertising slogan. In the context of AI, a brand means a set of consistent signals that allow systems to understand who a company is, what it does and why it can be trusted.
AI creates answers based on data available on the web. If a company has inconsistent descriptions, different names, outdated data, poor external profiles and little evidence of experience, the system may have trouble assigning it to the correct category.
This is especially important in B2B services, e-commerce, local companies and expert industries. The client is often not just looking for a definition. He is looking for a company that can be entrusted with implementation, design, audit, store, campaign or service.
A strong brand helps because:
users are more likely to search for it directly,
AI more easily assigns it to a specific specialization,
the company may appear as an example or recommendation,
direct and brand search reduce dependence on classic organic clicks,
consistent data increases the company's credibility across various sources.
What’s worth sorting out?
First of all, the company description on the home page and in the “About us” section. He should clearly state what the company does, who he works for, what he has experience in and what problems he solves.
It is also worth ensuring the consistency of NAP data, i.e. name, address and telephone number, in Google Business Profile, catalogues, industry profiles, social media and other places where the company appears.
The next element is opinions, case studies and implementations. AI and users need evidence. The mere declaration “we are experts” is weak. Much stronger are project examples, problem statements, deliverables, customer feedback, and specific team experience.
In practice, the company should ensure:
consistent brand description,
clear definition of specialization,
current contact and location details,
refined "About us" section,
visible case studies,
customer opinions,
company profiles,
mentions in external sources,
expert publications,
consistent communication across various channels.
AI must know for which questions it is worth mentioning a given company. If he doesn’t understand it, he can choose a competitor that is better described.
Content must be written for humans but readable by AI
Content on the site should still be written for people. It is the user who makes the decision, sends the form, calls, buys the product or compares the offer.
At the same time, the content must be readable by AI systems. This means that they should be specific, well-structured and easy to understand without additional context.
It is not enough to write long articles with keywords. AI is good at summarizing general definitions. If the text only answers the question “what is…” but does not add anything new, it may lose its meaning.
Content that helps the user make a decision is more valuable.
Good content in the AI era should include:
- a direct answer to the question,
- business context,
- examples,
- comparisons,
- data,
- restrictions,
- usage scenarios,
- case studies,
- responses to objections,
- practical conclusions.
It is worth using the answer-first model. This means that the most important answer appears at the beginning of the section, and only later is the context developed. This approach helps the user understand the topic faster, and it is easier for AI systems to extract a meaningful part of the answer.
Example:
Instead of starting a section with a long introduction to the history of a given solution, it is better to answer first:
"Magento makes sense when the store requires high scalability, multiple integrations, advanced catalog management and technological flexibility. For simpler B2C stores or a limited budget, WooCommerce or PrestaShop may be a better choice."
Only later can you develop the topic.
Content that is worth developing is primarily:
selection guides,
comparison of solutions,
case studies,
service pages,
product pages and categories,
sales FAQ,
local content,
industry content,
articles answering decision-making questions,
materials with data and examples.
It is worth avoiding mass production of texts that repeat the same things that already exist on the Internet. AI doesn’t need another general definition. It needs specific, reliable and well-described sources.
The website must be technically ready for AI robots
Even the best content will not help if search engine robots and AI systems cannot download, read or interpret it correctly.
AI-readiness of a website starts with technical basics.
The most important content should be available in HTML. If key information is hidden in PDF files, graphics, sliders, JavaScript-loaded elements or expandable modules, the robot may not see it or treat it as the main content of the page.
This is especially important for offers, service descriptions, products, price lists, comparisons, FAQ and case studies. It is these elements that can help AI understand the company and use the website as a source.
Technically you need to check:
indexation,
robots.txt,
sitemap.xml,
availability of key subpages,
how content is rendered,
page speed,
Core Web Vitals,
mobile version,
structured data,
canonical,
404 errors,
redirection,
content loaded with JavaScript,
locks in Cloudflare or WAF,
visibility of content hidden in accordions and tabs.
In practice, it is worth sticking to a few rules.
Firstly,
key content should be visible without the need for user interaction. If an important answer is hidden only after clicking, it may be less accessible to robots.
Secondly,
data and comparisons should be published as HTML text or tables, not solely as graphics. An image may look attractive, but a table is much more useful to a text-based content analysis system.
Thirdly,
PDF can be an addition, but it shouldn’t be the only place where important information is located. The most important data should also be available on the website.
Fourth,
you need to ensure correct structured data. JSON-LD helps search engines and systems better understand what the content is, who published it, what it is about, and how it connects to the rest of the site.
Things to consider include:
- organization,
- LocalBusiness,
- article,
- Author,
- FAQPage,
- product,
- BreadcrumbList,
- review,
- Service.
You can also consider the llms.txt file as an additional way to organize the most important website addresses and descriptions for LLM tools. However, it should not be treated as a reliable ranking factor. It is rather an experimental element of the AI-readiness layer, which may help to better describe the structure of the website.
Structured data and entities: AI needs to know what it is dealing with
AI does not analyze a website only as a set of key phrases. Understanding entities, i.e. specific objects: company, person, service, product, location, industry, technology, opinions and sources is becoming more and more important.
For the company, this means one thing: you need to clearly show what the system is dealing with.
The website should clearly indicate:
- company name,
- location,
- area of operation,
- specializations,
- services,
- products,
- content authors,
- publication and update dates,
- industries served by the company,
- case studies,
- opinions,
- related topics,
- related subpages.
This organizes knowledge about the company. This makes it easier for search engines and AI systems to connect a brand to a specific category.
Example? If a company deals with the implementation of B2B online stores, this specialization should be visible not only in one paragraph on the home page.
It should appear in the structure of services, case studies, articles, FAQs, technology descriptions, customer opinions and internal linking.
This creates a coherent picture:
company → B2B stores → ERP integrations → e-commerce → implementations → specific projects → opinions → experts.
Such connections help AI systems understand in what context it is worth mentioning a company.
Structured data won’t replace good content, but it helps organize it. In the era of AI, it is worth combining both: clear texts for people and clear markings for machines.
You need to build sources of trust outside your own website
A company website alone is not enough. The company will always write good things about itself. AI systems and users also look for confirmation in other places.
Therefore, external sources of trust become important.
These may be:
customer opinions,
Google Business Profile,
industry catalogues,
specialized portals,
expert articles,
rankings,
comparisons,
PR mentions,
podcasts,
YouTube,
case studies,
partnerships,
expert profiles,
publications by authors associated with the company.
If a company says one thing about itself and the Internet does not confirm it, its credibility is weaker. However, if the same information appears on the website, in industry profiles, opinions, articles and case studies, the systems have more reasons to consider the company credible.
This is especially important in industries where the customer makes decisions based on trust: B2B services, medicine, finance, law, IT, e-commerce, marketing, education and consulting.
Building visibility in AI begins to resemble a combination of SEO, PR, content marketing and reputation management.
It’s not enough to have text on the page. You need to have confirmation online.
A company cannot depend only on Google
Basing all customer acquisition on organic traffic from Google is an increasing risk.
Google is still very important and should not be overlooked. The problem begins when the company has no alternative source of contact with the customer.
Changes in search results, AI Overviews, CTR drops, zero-click search, algorithm updates and changes in user behavior can make some organic traffic less predictable.
Therefore, the company should also develop other channels:
- direct,
- brand search,
- newsletter,
- customer base,
- social media,
- YouTube,
- Google Discover,
- paid campaigns,
- remarketing,
- industry profiles,
- partnerships,
- webinars,
- materials to download,
- own communities.
It’s not about giving up on SEO. It’s about reducing risk.
If a company has a strong brand, contact base, active own channels, good remarketing and recognition beyond organic results, it is less susceptible to one change in Google.
In practice, the safest companies are those that can combine several sources of visibility. SEO then works together with the brand, content, advertising, social media, YouTube, newsletter and sales.
Analytics must show impact, not just clicks
In the era of AI, it is not enough to measure organic traffic alone. Some of the influence on a customer’s decision may happen without a click, and some of the traffic from AI may be more difficult to clearly attribute.
Therefore, analytics should show the bigger picture.
You need to analyze:
- organic traffic,
- traffic with AI Assistants,
- Direct,
- Reference,
- unassigned,
- brand search,
- conversions,
- quality of leads,
- remarketing,
- quality of leads,
- brand presence in AI responses,
- citations,
- share relative to the competition,
- the impact of content on customer decisions.
This means a change in the approach to reporting.
In the past, the main question was:
“How many hits came from Google?”
Today you have to ask:
“Was the company present in the customer’s decision-making process?”
Because the user may see the company in the AI response, not click immediately, and later come back through a branded or direct search. It may also reach the website from an AI tool, but the source will be classified differently than we expect.
Therefore, in GA4 and Google Search Console it is worth analyzing not only sessions, but also:
clicks,
views,
CTR,
brand inquiries,
entrance side,
conversions,
AI traffic sources,
quality of forms,
user paths,
traffic on decision-making websites.
We write more about the analysis of traffic drops, the Great Suppression and new data in GA4 in the article:
The phenomenon of loss of organic traffic. Why doesn’t fewer clicks from Google always mean there’s a problem?
Check out the article
Action plan for companies: what to do first?
It is worth treating the company’s preparation for AI search as a process. You don’t have to do everything at once, but you need to have a sequence of actions.
Stage 1: Diagnosis
First you need to check your starting point. Without a diagnosis, it’s easy to improve things that don’t have the biggest impact.
To be done:
- Google visibility analysis,
- presence analysis in AI,
- competition analysis,
- traffic and conversion analysis,
- technical audit,
- content audit,
- brand and data consistency analysis.
At this stage, the company should find out whether the problem is content, technique, lack of authority, poor analytics, lack of brand consistency or low visibility in new response systems.
Stage 2: Technical order
The second step is technique. If robots cannot download and understand content, subsequent actions will be weaker.
To check:
- indexation,
- speed,
- mobile,
- sitemap,
- robots.txt,
- diagram,
- HTML,
- JavaScript barriers,
- technical errors,
- redirection,
- 404 pages,
- canonical URLs.
Technology cannot replace a good offer, but without technology the offer may be invisible.
Stage 3: Content rebuilding
The next stage is to organize the content. It’s not about mass producing items. It’s about creating content that answers real questions from customers.
For development:
- service pages,
- categories,
- products,
- FAQ,
- case studies,
- selection guides,
- comparisons,
- answer-first content,
- updating old articles.
The greatest value has content that helps the customer make a decision, not just learn the definition.
Stage 4: Strengthening the brand
Then you need to ensure trust. AI and users look for confirmation.
To be done:
- collecting opinions,
- publication of case studies,
- development of industry profiles,
- expert publications,
- PR,
- consistency of company descriptions,
- visible content authors,
- presence outside your own website.
The goal is to create a situation in which the company is not an anonymous domain, but a recognizable and credible entity in its category.
Stage 5: Analytics and monitoring
Without measurement, a company doesn’t know whether its actions are working. That’s why you need to monitor more than just classic organic traffic.
To be implemented:
- correct GA4 configuration,
- connection to GSC,
- measuring conversions,
- traffic analysis with AI,
- brand search analysis,
- presence monitoring in AI responses,
- comparison with competitors,
- query quality analysis.
What is important is not only how many people visited the website, but whether they were people closer to the decision and whether the company appears where the customer is looking for answers.
Stage 6: Channel diversification
The final stage is to reduce your dependence on one traffic source.
For development:
- newsletter,
- direct,
- social media,
- YouTube,
- paid search,
- remarketing,
- own channels,
- community,
- expert materials,
- customer base.
A company that has several stable channels is less susceptible to changes in algorithms and the layout of search results.
Want to check if your company is prepared for AI search? We can analyze the website, content, technique, brand, analytics and presence in AI responses.
What should companies avoid?
The biggest mistake is waiting until the problem becomes visible in sales. Search transformation doesn’t always hit you right away. Sometimes information traffic drops first, then brand visibility drops, and only then does the number of inquiries drop.
There are a few things companies should avoid.
Firstly,
looking only at positions in Google. The items are still important, but they don’t show the whole picture. A company may be high in classic results but poorly visible in AI responses.
Secondly,
measuring only organic sessions. Traffic may decline and brand influence may still exist in AI responses, branded and direct queries.
Thirdly,
mass creation of content without specifics. Consecutive general articles will not protect your business if they do not provide experience, data, examples and answers to decision-making questions.
Fourth,
Hide important content in PDFs, graphics, accordions and dynamically loaded elements. The most important information should be available as readable HTML content.
Firstly,
looking only at positions in Google. The items are still important, but they don’t show the whole picture. A company may be high in classic results but poorly visible in AI responses.
Secondly,
measuring only organic sessions. Traffic may decline and brand influence may still exist in AI responses, branded and direct queries. Only organic sessions are measured. Traffic may decline and brand influence may still exist in AI responses, branded and direct queries.
Thirdly,
mass creation of content without specifics. Consecutive general articles will not protect your business if they do not provide experience, data, examples and answers to decision-making questions.
mass creation of content without specifics. Consecutive general articles will not protect your business if they do not provide experience, data, examples and answers to decision-making questions.
Fourth,
Hide important content in PDFs, graphics, accordions and dynamically loaded elements. The most important information should be available as readable HTML content. Hiding important content in PDF, graphics, accordions and dynamically loaded elements. The most important information should be available as readable HTML content.
Fifth,
ignoring opinions and external sources of trust. AI doesn’t have to trust only what a company writes about itself. He looks for confirmation in many places, ignoring opinions and external sources of trust. AI doesn’t have to trust only what a company writes about itself. He looks for confirmation in many places.
Avoiding these errors does not guarantee automatic presence in every AI response. However, it increases the chance that the company will be correctly understood, accessible and recognized as a reliable source.
What does an AI search-ready company look like?
A company prepared for AI search does not base its visibility on one channel, one phrase and one type of content.
It has an organized brand, a good website, specific content, technical availability, sources of trust and analytics that show the real impact of actions.
Such a company:
- has a clearly described specialization,
- has a consistent brand on the Internet,
- has a website technically accessible to robots,
- publishes specific content,
- shows experience and examples,
- has case studies and opinions,
- answers customers’ decision-making questions,
- uses structured data,
- has good analytics,
- monitors presence in AI,
- develops own channels,
- does not base all customer acquisition on one traffic source.
company unprepared
- only measures organic traffic
- has general content
- it only relies on Google
- has inconsistent data on the network
- hides data in PDF and graphics
- does not monitor AI
company prepared
- measures visibility, conversions and presence in AI
- has specific answers, data and case studies
- develops several access channels
- has an organized brand and sources of trust
- publishes data in HTML and tables
- regularly checks AI responses and competition
In practice, preparing a company for AI Search is not just one project, but a new standard of work on visibility. Website, SEO, content, brand, analytics and sales all need to work together.
Summary: securing your company is a process, not a one-time optimization
AI doesn’t mean the end of SEO. It means no more thinking that SEO alone is enough.
Companies that want to maintain visibility should work in parallel on brand, content, technology, data, authority, analytics, own channels and presence in AI systems.
The biggest risk isn’t that AI will take away some of your clicks. The biggest risk is that a company will no longer be considered when a customer asks AI about a problem, solution, product or supplier.
Therefore, preparing a company for AI Search should include:
- starting point audit,
- tidying up the page,
- improving content,
- brand strengthening,
- building sources of trust,
- improving analytics,
- channel diversification,
- constant monitoring of presence in AI.
This doesn’t have to be an overnight revolution. It is more important to systematically organize the most important elements.
Companies that start earlier will have an advantage. They will be better described, more reliable, easier to understand and less dependent on a single traffic source.
We can prepare an AI-readiness audit that will show whether your website is readable by search engines, AI systems and customers looking for specific answers.
FAQ
Czy każda firma musi przygotować się na wyszukiwanie AI?
Yes, but the scope of activities depends on the industry, sales model and the way customers look for information. Preparing an online store, a service company, and a local business is different. However, the foundations are common: a good website, specific content, a consistent brand, analytics and sources of trust.
Od czego zacząć przygotowanie firmy na AI Search?
It’s best to start with an audit. You need to check Google visibility, presence in AI responses, technical accessibility of the site, content quality, brand consistency, structured data, opinions, analytics and conversions. Only then is it worth planning changes.
It’s best to start with an audit. You need to check Google visibility, presence in AI responses, technical accessibility of the site, content quality, brand consistency, structured data, opinions, analytics and conversions. Only then is it worth planning changes.
Czy wystarczy dopisać kilka artykułów pod AI?
No. Articles alone are not enough if the company has inconsistent branding, poor site structure, technical issues, lack of reviews, lack of structured data and poorly configured analytics. Content is important, but it is only one element of preparing a company.
Czy SEO nadal jest potrzebne?
Yes. SEO is still a technical and content foundation. Without indexation, structure, speed, good content and authority, it is difficult to be a source for Google and AI systems. However, the role of SEO is changing. It should work with GEO, AEO, AIO, analytics, branding and trust building beyond your own website.
Co oznacza AI-readiness strony?
AI-readiness means that the website is technically accessible, well-structured, machine-readable and contains specific content, data, sources of trust and information that can be correctly understood by search engines and AI systems.
Jakie treści najlepiej zabezpieczają firmę przed zmianami w AI?
The most valuable decision-making content is: comparisons, case studies, sales FAQs, selection guides, data, reports, opinions, descriptions of services and products, and materials answering real customer questions. Definitions and general guides themselves will be increasingly easily replaced by AI answers.
Czy firma powinna rozwijać kanały poza Google?
Yes. Relying solely on organic traffic from Google is a risk. It is worth developing brand search, direct, newsletter, YouTube, social media, remarketing, customer database, industry profiles and other own channels. It’s not about giving up SEO, but about reducing your dependence on one traffic source.
Jak mierzyć przygotowanie firmy na AI Search?
It is worth analyzing not only organic traffic, but also the brand’s presence in AI responses, citations, brand and direct inquiries, lead quality, conversions, competition visibility, technical accessibility of the website and the effectiveness of decision-making content.
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