AI visibility isn’t built simply by publishing more content. It’s built when you know what type of questions you want to dominate, which pages you need to improve, and how you get AI to actually understand and use your content in its responses.

Many companies fail because they start with initiatives that seem productive but are implemented in the wrong order. The most robust approach is to begin with an analysis, prioritise key areas, build a solid foundation, and then continuously focus on measurement and growth.

Why You Need a Process

AI visibility is a multidisciplinary effort that involves content, structure, technical setup, and positioning. If you jump straight into schema, FAQs, or blog content creation without knowing which questions and topics actually matter most, it’s easy to optimize the wrong pages first.

A good process helps you focus your time on areas that offer both business value and a realistic chance of visibility. This is especially important in the beginning. You don’t need to fix everything at once. Based on our experience, we know it’s wise to choose a few topics and pages to prioritize first.

We recommend that you read our article “What Is AI Visibility” before you continue, if you haven’t already!

Step 1: how do you map AI visibility?

The first step is to establish a baseline and identify where the greatest potential for visibility is. You need to understand how your brand is currently perceived in AI, which competitors are mentioned in relation to the topics you want to dominate, and which themes actually emerge across AI platforms.

In practice, this means you should test questions with high business value in search interfaces like ChatGPT, Perplexity, Gemini, and Google AI Overviews, and document the results. Do you see your own brand? Which sources are used? Which competitors appear? How is the category described?

Look for:

• Whether your brand is mentioned at all

• If competitors are mentioned more often than you

• What types of sites appear to be used as sources

• Whether AI correctly understands your services and categories

• Which questions generate the most visibility for your market

This analysis does two things: it gives you a true baseline, and it reveals how AI already perceives your market in a way you can build on.

Step 2: Prioritise high-value questions and pages

Once the analysis is complete, you shouldn’t try to optimise the entire website at once. The most effective approach is to select a small set of pages that have both high commercial value and high relevance to your target audience, for example service pages if you only have a few.

The questions you prioritise should be closely aligned with the customer journey. This typically includes questions related to evaluation, comparison, usage, price, method, advantages and disadvantages. Such questions often provide a better foundation for both AI-generated answers and commercial visibility than broad definitional articles alone.

A good selection to start with might be:

• 5–10 questions you’d like to be associated with

• 3–5 existing pages that already have potential

• 1 pillar page on a topic you want to dominate

• 2–3 supporting articles that address the sub-questions

The goal isn’t to achieve broad coverage from day one. The goal is to establish a clear presence in a few key areas first.

Step 3: Build a foundation that AI can actually use

Once you know what to prioritise, it’s time to lay the groundwork. This isn’t just about technical measures, it’s about making the content easier to interpret, extract, and rely on. AI systems are more likely to select content that is structured, explicit, and easy to use as standalone answers.

Start with the pages you’ve selected and redesign them using an “answer-first” approach. This means the page should provide a clear answer early on, use questions as headings, and break the content down into short sections that can stand on their own.

The foundation should include at least the following:

• A clear H1 that matches the main topic

• A brief summary at the top of the page, before the long introductions

• H2s are formulated as actual questions or clear subtopics

• Short paragraphs with one main point per section

• Bulleted lists of steps, issues, benefits, and priorities

• FAQ where users naturally have follow-up questions

• Relevant schema, such as Article, FAQPage, HowTo, or Organization, as appropriate

This is often where many companies realise that they actually have good content, but that the presentation is too vague, too long, or not easily extractable by AI.

Practical example:

The Sikte AI homepage has the following structure:

• H1: (Main topic) We help you build you AI-visibility

• H2: (What is it and why is it important now?) What is AI visibility?

• H2: (How can we help?) How we can help you

• H2: (Who can we help?) Who we can help

• H2: (Who are we?) About Sikte AI

• FAQ: Frequently Asked Questions

The page has a simple layout with short paragraphs that answer key questions and describe our mission, without too much clutter or text. The content is carefully structured and unassuming. This works. We see that LLMs are able to extract our content and reproduce it in their responses.

Step 4: Clarify who you are and which topics you want to own

AI visibility isn’t just about providing good answers. It’s also about clearly defining the area in which you want to be recognised. AI systems prefer sources that appear consistent, specialised, and clear in terms of their field of expertise and range of services.

That’s why you should be consistent in your use of language, categories, and terminology throughout the website. If you want to establish a theme, it must be easy to recognise the same message in the hero text, service pages, blog, FAQ, schema, and internal links.

This means:

• Use the same terms consistently across pages

• Describe the services clearly and specifically

• Explain who you’re helping and what problems you solve

• Create thematic links between related pages

• Make sure the brand is consistently linked to the same key themes

This is the key difference between random visibility and strategic visibility over time.

Step 5: Focus on ongoing growth, not just the launch

Once the foundation is in place, the part that many people underestimate begins: the ongoing work. AI visibility must be measured and improved on an ongoing basis because the competition, question patterns, and AI responses are all changing rapidly.

This means you should track the same search terms over time and see how mentions, citations, and rankings evolve. If you notice that certain search terms yield better results, you can prioritise future content and updates where there is momentum.

A simple monthly routine could be:

• Test the same 10 questions in several AI tools

• Take note of whether you are mentioned, how you are described, and who else is visible

• Update the most important pages with clearer answers or new information

• Create a new piece of content that supports a priority topic

• Look for patterns in what AI actually seems to use

This results in a much more rigorous process than publishing articles without a clear hypothesis or measurement.

The most common mistakes in implementation

Many companies understand the theory but fail in its implementation. The most common mistake is that they take on too much at once and lose sight of their priorities.

Other common mistakes include:

• They don’t measure the baseline before making changes

• They optimise pages with low business value first

• They write new articles without improving the key pages they already have

• They add schema without cleaning up the actual content

• They are inconsistent in how they describe their brand and services

The most important thing isn’t to do everything perfectly. The most important thing is to work in the right order and make it easier for AI to understand what you’re relevant for.

Here’s what a simple work model might look like

If you want to start simple, you can use this model:

1. Select 5–10 questions you want to highlight

2. See how you and your competitors appear in AI today

3. Choose 3–5 pages to improve first

4. Organise the pages using an “answer-first” approach, FAQs, and clear subtopics

5. Add relevant schema types where appropriate

6. Track developments on a monthly basis and create supporting content around the topics that matter most

This is often enough to make the transition from random efforts to actual, systematic work on AI visibility.

Recommended next read: How to measure AI visibility: 5 KPIs

Frequently asked questions

How can I begin to work with AI visibility?

Start by testing a small set of high-value questions in the AI tools your audience actually uses, then document how your brand is currently described, cited, or ignored. From there, improve a few important pages first by making them clearer, better structured, and easier for AI systems to interpret before investing in large amounts of new content.

How many pages should I optimise?

For most businesses, starting with 3 to 5 pages is enough. That gives you enough coverage to spot patterns and measure change, while still keeping the project focused enough to do the work properly.

What matters more: schema or content?

Content comes first. Schema helps search engines and AI systems understand your pages more accurately, but it cannot fix weak answers, unclear services, or poor structure.

How often should I measure AI visibility?

A monthly review is a strong starting point because it gives you enough time to spot meaningful changes without making the feedback loop too slow. If you are in a fast-moving market, you can add lighter weekly checks for your most important prompts.

Do I need to publish new content all the time?

No. Many businesses will get better results by improving their most important existing pages before creating more content. New content becomes much more valuable when it supports clear priority topics and strengthens a deliberate topic cluster rather than adding volume for its own sake.