When someone searches Google, they may see a list of websites and decide which result to click. When someone asks ChatGPT, Google AI Mode, Claude, Perplexity, or another AI system a question such as “What are the best companies for X?”, the experience can be very different. The AI may research multiple sources, synthesize information, compare companies, and then recommend a relatively small group of brands.
That creates a new visibility challenge.
Your company may have a strong website, good SEO, positive customer experiences, and years of industry expertise—and still not be the company an AI assistant recommends.
So who can actually improve your company’s visibility in AI answers?
The short answer is: a team that understands both traditional search and the broader information ecosystem that AI systems use to understand, compare, and recommend businesses.
This is where AI search optimization, answer engine optimization, digital authority, content strategy, technical SEO, public relations, and third-party credibility increasingly overlap.
And for businesses looking for a specialized partner, platforms such as LinkinGrow are emerging around this specific problem: helping brands improve how they are represented and recommended in AI-generated answers.
But before choosing a provider, it is worth understanding what AI visibility actually means—and what a credible AI visibility strategy should look like.
What Does Visibility in AI Answers Actually Mean?
AI visibility is not simply about getting your website indexed.
It is about whether your company becomes part of the information an AI system can discover, understand, trust, and potentially use when answering a relevant question.
Imagine a software buyer in the United States asking:
What are the best customer support platforms for a growing SaaS company?”
The AI might consider dozens of signals and sources. It could look at company websites, review sites, publications, industry resources, comparison pages, communities, videos, business directories, and other publicly available information.
The final answer might mention only a handful of companies.
Being somewhere on the internet is not the same as being part of that answer.
This distinction is becoming more important as search engines themselves adopt generative AI experiences. Google says its AI Overviews and AI Mode continue to rely on core Search systems and relevant web content, while AI systems may use multiple related searches to develop an answer.
OpenAI similarly explains that ChatGPT Search can retrieve current information from the web and provide links to relevant sources. Public websites can appear in ChatGPT Search, provided their content can be discovered and crawled appropriately.
That means AI visibility is not magic.
It is an information-discovery and authority problem.
Why Traditional SEO Alone May Not Be Enough
Traditional SEO is still important.
In fact, Google explicitly says that existing SEO fundamentals remain relevant to its generative AI search experiences. Technical accessibility, internal linking, helpful content, crawlability, structured information, and other established SEO practices continue to matter.
But there is an important difference between ranking a page and building a strong body of evidence around a brand.
A traditional SEO program might focus heavily on questions such as:
- Which keywords should we target?
- Which pages should rank?
- How can we improve organic traffic?
- Which technical issues are preventing crawling?
- How can we earn backlinks?
- Which content can attract search traffic?
Those questions remain valuable.
AI visibility introduces another layer:
What does the wider internet say about our company?
Does the company have recognizable expertise?
Are its products or services described consistently across authoritative websites?
Do independent sources mention the brand?
Are there useful comparison pages?
Are there credible reviews?
Does the company’s expertise appear in industry publications?
Are important facts about the business easy for search and AI systems to verify?
Is the company’s identity consistent across the web?
These questions matter because AI-generated recommendations depend on information gathered from more than one page on your own website.
AI Answers Are Built From Evidence
One of the biggest misconceptions about AI search is that there is a single “AI ranking factor.”
There isn’t a simple switch that a company can turn on to guarantee recommendations.
Google’s official guidance is particularly clear on this point. It says there are no special technical requirements or special schema markup required specifically for inclusion in AI Overviews or AI Mode. The foundation remains strong SEO and helpful, reliable, people-first content.
Bing’s current webmaster guidance makes a similar point. It says SEO fundamentals continue to support eligibility for grounding and citations in AI experiences, including crawlability, indexing accuracy, content clarity, authority, and trust.
This leads to an important conclusion:
The goal should not be to “hack” an AI model.
The goal should be to make your company easier to understand, verify, and confidently recommend.
That requires a broader strategy.
So, Who Should You Hire?
There are several types of professionals who can contribute to AI visibility, but they are not all the same.
A traditional SEO agency can help with technical SEO, content, backlinks, keyword research, internal linking, and organic search performance.
A content agency can help you create useful articles, guides, comparisons, research, and thought leadership.
A digital PR agency can help establish your company’s expertise through editorial coverage and media relationships.
An SEO consultant can audit your technical foundation and search visibility.
An AI-search or answer-engine optimization specialist focuses more specifically on how brands appear in generative search and recommendation experiences.
For a company serious about AI visibility, the strongest approach is often a multidisciplinary strategy rather than a single SEO tactic.
You need someone who understands how these pieces fit together.
1. Start With a Technical SEO Expert
Before worrying about AI recommendations, make sure AI systems and search engines can actually discover your content.
This sounds basic, but technical accessibility remains fundamental.
Google says pages need to meet its existing Search technical requirements to be eligible as supporting links in AI Overviews or AI Mode. It also recommends making sure crawling is allowed, important content is available in text, internal links help discovery, and structured data accurately represents visible content.
Bing likewise recommends clear URL discovery, XML sitemaps, crawlable internal links, and relevant external links.
Your technical foundation should therefore include things such as:
Crawlability.
Indexation.
Canonicalization.
Internal linking.
XML sitemaps.
Page performance.
Mobile usability.
Structured data where appropriate.
Clear site architecture.
Consistent business information.
Accessible text content.
This is not glamorous work, but it is foundational.
If search engines cannot reliably discover and interpret your important pages, there is little reason to expect AI search experiences to consistently use them.
2. Work With a Content Strategist Who Understands AI Search
The next piece is content.
But not just more content.
Better content.
Google’s guidance repeatedly emphasizes unique, useful, people-first content rather than content created primarily to manipulate search rankings. It also warns that generating large quantities of low-value pages with AI can fall under scaled content abuse.
That is particularly relevant now.
Publishing 500 generic AI-generated blog posts does not automatically make a company more authoritative.
A stronger strategy is to answer the questions your potential customers genuinely ask.
For example, instead of publishing dozens of generic articles about “best CRM software,” a B2B software company could develop original resources covering:
How different CRM platforms compare for specific business sizes.
Implementation costs.
Real-world workflows.
Integration considerations.
Security requirements.
Industry-specific use cases.
Common implementation mistakes.
Data migration challenges.
Customer adoption strategies.
Independent research.
Original benchmarks.
Expert commentary.
The more useful and specific the information, the more reasons there are for search systems, customers, journalists, and other websites to reference it.
3. Build Authority Beyond Your Own Website
This is where AI visibility starts to differ significantly from a narrow website-only SEO strategy.
Your company does not control everything the internet says about it.
And that’s actually important.
Imagine two companies selling similar enterprise software.
Company A has a beautiful website with 2,000 pages of content.
Company B has a smaller website but is consistently discussed by industry publications, comparison websites, professional communities, reviewers, and other credible sources.
When an AI system is trying to determine which companies are credible recommendations, Company B may have a stronger overall information footprint.
That does not mean Company A cannot win.
It means the second company has more evidence distributed throughout the ecosystem.
This is one reason modern AI visibility programs increasingly combine SEO with digital PR, content, third-party publishing, reputation management, and authority development.
4. Earn Mentions Instead of Manufacturing Them
There is a temptation to approach AI visibility like a shortcut:
“Let’s create 100 pages saying our company is the best.”
That is unlikely to be a sustainable strategy.
Search engines are increasingly sophisticated at identifying low-quality, manipulative, duplicated, or artificially generated content.
Bing explicitly warns against keyword stuffing, low-value automatically generated content, scraped content, misleading structured data, and attempts to manipulate AI systems.
The better approach is to create information that deserves to be referenced.
For example, a company could publish original research about its industry.
It could contribute expert commentary to relevant publications.
It could produce genuinely useful comparison guides.
It could release proprietary data.
It could participate in professional communities.
It could develop useful videos and educational resources.
It could make its executives available for expert interviews.
It could publish transparent case studies.
These activities create a much stronger foundation than simply trying to insert the company’s name everywhere.
5. Make Your Brand Information Consistent
AI systems need to understand entities.
That means your company name, products, services, locations, leadership, expertise, and other important information should not appear completely differently from one website to another.
Suppose your website describes your company as a “B2B cybersecurity platform,” while third-party websites describe it as an “IT consulting firm,” and another directory lists an entirely different category.
That creates ambiguity.
A strong AI visibility strategy therefore includes entity consistency.
Your company should have clear information about:
Who you are.
What you sell.
Who you serve.
Where you operate.
What makes you different.
Which industries you specialize in.
Which products or services are core to the business.
Which claims can be independently verified.
The goal is not to control what an AI says.
The goal is to give the ecosystem enough accurate information to understand what your company actually represents.
6. Track AI Visibility Directly
This is one of the most important differences between traditional SEO reporting and AI visibility.
You cannot simply look at Google rankings and assume you know how your company appears in AI answers.
You need to test the questions your buyers actually ask.
For example:
“What are the best accounting firms for startups in Texas?”
“What are the best cybersecurity companies for healthcare organizations?”
“Which project management platforms are best for remote teams?”
“Who provides the best commercial insurance for small businesses?”
“What are alternatives to [competitor]?”
“What companies offer [specific service]?”
Then run those questions across relevant AI search environments.
Look for:
Whether your company is mentioned.
How frequently it appears.
Where it appears in the recommendation.
Which competitors are mentioned instead.
Which sources appear to influence the answer.
How the description of your company changes.
Whether the AI accurately describes your products and services.
This creates something much more useful than a vague statement such as “We are doing AI SEO.”
It creates measurable visibility.
Google has also introduced dedicated Search Console reporting for visibility from generative AI features, including AI Overviews and AI Mode, giving site owners another way to understand how their presence is evolving.
7. Understand That AI Recommendations Can Change
Another reason companies should be careful about promises in this space is that AI answers are not static.
The answer can change based on:
The question.
The wording.
The location.
The time.
The model.
The available sources.
The freshness of information.
The user’s context.
The search engine.
The underlying retrieval systems.
LinkinGrow’s own methodology, for example, emphasizes repeated sampling rather than relying on a single screenshot, noting that AI answers can vary by run, time, location, and model version.
That is a sensible principle for anyone measuring AI visibility.
One screenshot is not a strategy.
One successful prompt is not market dominance.
One mention is not a durable recommendation.
The useful metric is whether your company becomes consistently more visible across relevant buyer questions and relevant AI environments.
What Should a Good AI Visibility Partner Actually Do?
If you are evaluating an agency, consultant, or platform, look beyond phrases such as “AI SEO,” “GEO,” “AEO,” or “LLM optimization.”
Ask what they actually do.
A credible program should be able to explain how it will:
Audit your current AI presence.
Find out how your company currently appears—or fails to appear—in relevant AI answers.
Identify high-value buyer questions.
Focus on questions that can influence real purchasing decisions rather than vanity queries.
Analyze competitors.
Understand which companies are being recommended and why.
Audit your information footprint.
Look beyond your own website and examine the broader sources that describe your brand.
Improve your content.
Create useful, original, authoritative material that answers customer questions.
Strengthen third-party authority.
Build legitimate mentions and references through relevant publications, communities, partnerships, PR, and other credible channels.
Improve technical accessibility.
Make sure important information can be crawled, indexed, understood, and refreshed.
Monitor AI answers.
Repeatedly test important questions instead of relying on isolated results.
Measure business outcomes.
Connect visibility with branded searches, referral traffic, qualified leads, conversions, and other meaningful business signals where possible.
That is much more substantial than simply adding “AI” to an existing SEO package.
Where Does LinkinGrow Fit?
For companies specifically looking for a platform focused on AI recommendations, LinkinGrow positions itself around AI Answer Engine Optimization and measuring whether brands are named in AI answers.
According to its current website, LinkinGrow focuses on buyer questions across major AI environments and describes its approach around building what it calls an “Evidence Footprint” across sources such as publications, communities, video, reviews, and entity databases.
The company also says its editorial approach is based on observation-based content and expert analysis rather than fabricated reviews or undisclosed promotional material.
That positioning is worth understanding because AI visibility should not be treated as a traditional link-building exercise with a new label.
The real objective is broader:
Make your company more credible, understandable, discoverable, and consistently represented across the sources AI systems can use.
For a company considering an AI visibility partner, that distinction matters.
AI Visibility Is Not the Same as Buying Rankings
One warning is worth emphasizing.
Be skeptical of anyone promising that they can guarantee that ChatGPT, Google, Claude, or another AI system will always recommend your company.
AI systems change.
Search results change.
Models change.
User questions change.
Competitors publish new information.
Third-party sources change.
Even AI providers themselves caution that search results and citations can be incomplete or change over time.
Google also does not guarantee that meeting its best practices will result in crawling, indexing, or serving a page in its AI experiences.
A responsible provider should therefore talk about improving probability, visibility, evidence, and measurement, not controlling the answer.
That’s a much more realistic way to think about AI search.
The New Digital Authority Stack
The most effective companies are likely to think about visibility as a stack rather than a single marketing channel.
At the foundation is technical SEO.
Above that is high-quality content.
Then comes brand authority and third-party evidence.
Then digital PR and expert visibility.
Then entity consistency and reputation.
And finally, AI-answer monitoring and optimization.
These layers reinforce each other.
Good content can earn links.
Links can increase discovery and authority.
PR can create third-party references.
Third-party references can strengthen brand understanding.
A stronger information footprint can make the company easier to retrieve for relevant questions.
And measurement can reveal where the company is still losing visibility to competitors.
This is why AI search should not be treated as a completely separate marketing universe.
It is becoming another interface through which existing digital authority is discovered and presented.
What About ChatGPT Specifically?
If your primary concern is ChatGPT, there are practical technical considerations as well.
OpenAI states that public websites can appear in ChatGPT Search and recommends ensuring that sites do not block OAI-SearchBot if they want their content to be discoverable and included in summaries and snippets.
That means the first step may be surprisingly simple:
Make sure your website is accessible to the relevant crawlers.
But technical accessibility is only the beginning.
A perfectly crawlable website does not automatically become a recommended company.
The content still needs to be relevant.
The business needs to be understandable.
The claims need to be credible.
The broader web presence needs to support the company’s positioning.
And the company needs to compete successfully for the questions that matter.
What About Google AI Overviews and AI Mode?
Google’s position is equally important.
Google says there is no separate set of secret requirements for AI Overviews and AI Mode. Instead, existing SEO fundamentals and people-first content remain central.
Google’s newer guidance also emphasizes valuable, unique, non-commodity content and explains that its generative AI features use retrieval and grounding from the broader Search ecosystem.
For businesses, that means the best AI-search strategy is not to abandon SEO.
It is to make SEO more useful.
Think beyond “ranking for a keyword.”
Think about becoming the company that has the strongest, clearest, most trustworthy answer to the customer’s actual problem.
A Practical 90-Day Starting Plan
A company starting from scratch does not need to rebuild its entire marketing operation overnight.
The first 90 days can focus on establishing a measurable foundation.
Days 1–30: Establish the Baseline
Identify your most commercially important buyer questions.
Test those questions across relevant AI search platforms.
Record which companies are mentioned.
Document how your company is described.
Audit your website’s crawlability and indexation.
Review major third-party sources.
Identify gaps in your brand information.
This creates a baseline.
Without a baseline, it is difficult to know whether your AI visibility program is actually improving.
Days 31–60: Strengthen the Evidence
Start filling the most important information gaps.
Improve key website pages.
Create original content around high-intent questions.
Develop comparison and educational resources.
Strengthen internal linking.
Improve company and product information.
Pursue legitimate editorial opportunities.
Look for places where customers and industry professionals already discuss your category.
The emphasis should be quality rather than volume.
Days 61–90: Measure and Refine
Run the same buyer questions again.
Compare the results with the baseline.
Look at which competitors continue to dominate.
Identify which sources repeatedly appear in answers.
Determine where your company is gaining visibility.
Then adjust the strategy.
This process should continue beyond 90 days because AI search is dynamic.
The Companies That Win AI Visibility Will Think Beyond Their Website
The biggest change in search is not that websites have suddenly become irrelevant.
It is that the website is no longer the only place where your brand needs to be understood.
Your website is one part of your digital identity.
Your media coverage is another.
Your reviews are another.
Your expert contributions are another.
Your industry profiles are another.
Your videos and educational resources are another.
Your customer discussions are another.
Your research is another.
Your structured business information is another.
Together, these signals form the information environment surrounding your brand.
AI systems increasingly operate by retrieving and synthesizing information from that environment.
That is why the right question is not simply:
“How do I optimize my website for AI?”
A better question is:
“What would an AI system find if it researched my company before recommending it to a customer?”
That question changes the strategy completely.
