In 2024, already 20% (36% of Gen Z) of people now start their search journey using online Chat engines, and this number will only grow over time.

There’s a fundamental shift happening in how we search. Instead of scrolling through pages of search results, people are increasingly turning to AI assistants for personalized recommendations and answers. These conversations are becoming the new front door to your business – whether you’re prepared for it or not.

When someone asks “What’s the best marketing agency for AI implementation?” or “Who offers reliable custom software development?”, AI assistants draw from their vast knowledge to make recommendations. Some businesses consistently appear in these recommendations. Others, despite their expertise and market presence, remain invisible to AI – missing out on a growing channel of high-intent prospects.

This isn’t a future concern. Every day, potential customers are having conversations with AI assistants about products and services like yours. The businesses that understand and adapt to this shift now will have a significant advantage as AI continues to shape how people discover and evaluate businesses. Those who wait risk becoming increasingly difficult to find as AI assistants become more central to decision-making processes.

Being discoverable isn’t just about ranking on Google anymore. As we look ahead to 2025 and beyond, businesses increasingly need to consider how they appear in AI conversations. When potential customers ask ChatGPT, Claude, Perplexity, Meta AI or Gemini for recommendations, will your business be part of that discussion?

This shift in discovery patterns requires a thoughtful, consistent approach developed over months of strategic content creation and distribution. In this guide, we’ll break down the practical steps your business needs to take today to build lasting visibility in AI conversations. Whether you’re just starting to think about AI visibility or looking to validate your current approach, you’ll learn actionable strategies that go beyond traditional SEO.

Understanding How AI Discovers Your Business

When someone asks an AI assistant like ChatGPT about products or services in your industry, how does it know what to recommend? Unlike traditional search engines that mainly look at keywords and website links, AI assistants build their knowledge through extensive reading and learning from various trusted sources. Let’s break down where these AI systems typically gather their information, and more importantly, how you can thoughtfully position your business in these spaces:

1. The Common Crawl: Also known as “public website content”, think of this as AI’s view of the entire internet. To ensure your business is visible here, focus on creating clear, valuable content that thoroughly explains your expertise and offerings across your website and other online platforms.
2. Wikipedia and Knowledge Bases Wikipedia carries significant weight in AI training because it’s considered a reliable source of verified information. While creating a Wikipedia page requires meeting strict guidelines, you can build visibility by contributing your expertise to existing pages in your industry. For example, you might add well-researched information about innovations or developments in your field.
3. Social Media Conversations AI systems learn from meaningful social media discussions, particularly those that receive high engagement. This means thoughtfully participating in industry conversations on platforms like LinkedIn, Reddit, or YouTube can help establish your presence. The key is sharing valuable insights rather than promotional content.
4. Published Resources Creating comprehensive guides, ebooks, or contributing to academic discussions helps establish lasting authority in your field. These materials often become trusted sources that AI systems reference when answering questions about your industry.
5. Industry Publications Contributing quality content to respected industry websites and publications helps spread your expertise across multiple platforms. When other sites republish or reference your content, it reinforces your authority in AI systems’ understanding of your field.
6. Review Platforms and Local Business Data Services like Yelp, Google Business Profile, TripAdvisor, and industry-specific review sites serve as valuable sources of real-world validation for AI systems.

When someone asks an AI assistant for local recommendations or service provider suggestions, these platforms provide essential context about your business’s location, services, and track record. Through reviews and detailed business information, AI assistants can understand not just where your business operates, but also what you offer and how well you deliver on your promises. This real-world validation helps AI systems make confident, relevant recommendations to users seeking local solutions.

Understanding these key sources is just the first step in building AI visibility for your business. Success requires a deeper exploration of how AI assistants actually use this information to answer questions. To create an effective AI visibility strategy, we need to understand:

• How to identify which questions your potential clients are asking AI assistants
• Which content sources AI systems prioritize when forming answers
• How to adapt your writing style for better AI comprehension
• What technical requirements ensure your content is properly visible
• How to monitor and adjust your approach as AI capabilities evolve

In the following sections, we’ll break down each of these elements, starting with how to discover and optimize for the specific questions your audience is asking AI assistants.

How to Identify Questions Your Potential Clients Ask AI Assistants

To effectively appear in AI conversations, you first need to understand exactly what questions your potential clients are asking. This requires four essential steps:

1. Understanding Your Customer Before you can predict what someone might ask an AI assistant about your business, you need a clear picture of who they are. A well-defined customer profile helps you understand their challenges, goals, and how they think about solving their problems.
2. Mapping Their Journey People ask different questions at different stages of their buying process. By mapping out your customer’s journey, you can anticipate what information they need at each step – from initially discovering they have a problem, through comparing solutions, to making their final decision.
3. Gathering Real Question Data Theory and assumptions aren’t enough. You need to collect and analyze actual questions your target customers are asking about your type of product or service. This data comes from customer service interactions, sales conversations, online discussions, and reviews.
4. Organizing Questions by Journey Stage Finally, you need to understand where each type of question fits in your customer’s journey. This helps you ensure you’re visible to AI assistants for early research questions, comparison questions, and final decision questions alike.

By following these four steps, you create a framework for understanding not just what questions people might ask AI assistants about your business, but also when and why they ask them. This understanding is crucial for developing content that AI assistants will confidently reference when answering these questions.

Practical Example: Using AI to Determine Typical Customer Questions

Here’s a practical example of using AI to accelerate your research process, focusing on the software application: ClickUp

What is ClickUp? ClickUp is a project management software tool. We think of it like Jira and Asana had a baby. We are not affiliated with nor do we work with or for ClickUp, we just figured they would make a good example for this article.

Starting with quality data is essential. In this case, we’ll use hundreds of publicly available ClickUp reviews. This existing customer feedback provides a rich source of real-world insights that we can analyze systematically. You can make this data accessible to an AI assistant through attachments, training data, or as a project reference.

Once your data is loaded, you can ask the AI assistant targeted questions to help fast-track the research process. Here’s an example query that helps identify potential questions your customers might ask:

This approach quickly generates a structured list of inferred questions, organized by customer journey stage:

Important note about validation: While AI can rapidly analyze large amounts of data, you should never trust these outputs without careful review. Take time to validate the generated questions against your own customer insights and market knowledge. Consider which questions align with your business goals and are worth optimizing for.

This same data-driven approach can help you develop customer profiles and journey maps more efficiently (the focus of future articles we will publish).

The key is leveraging data you likely already have – whether that’s customer reviews, support tickets, sales calls, or other customer interactions. If you don’t have this data yet, now is the time to start collecting it systematically.

AI Source Priorities: Building Visibility Where It Matters

Understanding where AI assistants get their information is crucial for visibility. Let’s break down how to analyze and optimize your presence across these sources.

Finding Your Content Gaps Once you’ve identified the questions your customers are asking AI assistants, the next step is to see how well your business appears in the answers. This requires systematic monitoring across different AI platforms.

Tools you can use: At this time of writing we are aware of the following tools for side-by-side queries. Let us know if we are missing any important players!

ChatHub https://chathub.gg/
ChatAll https://github.com/ai-shifu/ChatALL
OpenWebUI https://openwebui.com/
LLMStudio https://lmstudio.ai/

When reviewing AI responses across platforms, look for patterns:

• Where is your business mentioned?
• Where is it missing entirely?
• Which competitors appear instead?
• What sources are the AI assistants citing?

Compare these findings against your customer journey research to prioritize which gaps need filling first. Focus on the questions that matter most to your customers at critical decision points.

If you want to approach this methodically, you will want to track your baseline so you can track your progress over time. Until the industry invents a tool to make this process easier, your best bet is to track all of these results in a spreadsheet so you can date and compare your performance over time. Below is a link to a public Google Sheet you can duplicate to use as a starting point for your own AI Search Optimization work (Which I will call AISO for short, but sometimes it is called generative search optimization, or generative AI optimization, or SEO for language models).

Download AI Search Optimization tracking template

Building Strategic Presence After identifying gaps, it’s time to develop a targeted content strategy. Here’s our approach:

1. Align with AI Company Ecosystems Different AI assistants tend to favor content from their parent company’s platforms. If a business owns a data source you can be pretty sure it will use that source in its training. If you are showing up on some LLMs but you are not showing up in one specific AI engine, consider targeting platforms they own as your top priority.

• For Google’s AI tools: Focus on YouTube content and Google Business Profile
• For Microsoft/OpenAI tools: Prioritize LinkedIn and GitHub presence
• For Meta AI: Prioritize Facebook. Meta has trained their AI models on all of their properties that go as far back as 2007.

2. Target Referenced Sources When sources appear in the AI responses, pay attention to which third-party platforms AI assistants frequently cite. For example:

• If Yelp reviews appear often, prioritize building a stronger review presence there
• If industry publications are commonly referenced, develop relationships with those outlets
• If professional forums are cited, become an active contributor in those spaces

The key is to be strategic rather than trying to be everywhere at once. Focus your efforts on the platforms that will cover the areas where you are currently weakest. If you are not showing up anywhere, use a more fundamental approach and start with what you can manage as you expand outwards and diversify.

However keep in mind that AI systems are inherently statistical engines, meaning that your best chance of being mentioned is from lots of data points all pointing towards you and your services. The more connections and the more data points you have out there, the greater the probability that you will be the source/product/service they recommend.

How to Write Content That AI Assistants Understand

Creating content that AI assistants can confidently reference requires a shift in how we think about writing. Unlike traditional SEO that focuses on keywords, AI optimization requires a more natural, comprehensive approach to content creation.

Focus on Intent Over Keywords AI assistants are designed to understand the meaning behind questions, not just match keywords. Your content should directly address the questions and concerns your audience has at each stage of their journey. Instead of optimizing for phrases like “Best AI marketing agency Portland,” create content that thoroughly answers questions like “How do I choose a marketing agency that specializes in AI implementation?”

Embrace Conversational Language As more people interact with AI through voice, conversational content becomes crucial. Write as if you’re having a dialogue with your reader. This means:

• Using natural language patterns
• Answering questions directly and completely
• Including follow-up information that anticipates related questions
• Avoiding overly formal or technical language (unless necessary or expected by your audience)

Keep Content Fresh and Relevant While AI assistants prioritize the most statistically numerous data, they will over time also weigh more heavily on the most current information. Think of your content strategy like tending a garden:

• Regularly update existing content with new insights
• Create new content that builds on current trends and developments
• Update outdated information
• Maintain a consistent publishing schedule

Establish Clear Attribution Make it easy for AI assistants to connect your content to your brand:

• Make sure you include your name and brand naturally within all of your content
• Attribute authorship clearly
• Maintain consistent naming across platforms
• Connect related content pieces through clear references

Writing Best Practices for AI Comprehension

• Structure content with clear headers and sections
• Provide comprehensive answers to specific questions
• Include supporting evidence and examples
• Use consistent terminology throughout
• Balance depth with accessibility
• Maintain a clear, logical flow

Remember: AI assistants are designed to understand and synthesize information much like humans do. The best content for AI comprehension is simply well-written, thorough content that directly addresses your audience’s needs and questions.

Maximize Local Business Visibility For businesses serving specific geographic areas, focus your energy on gathering detailed, expressive reviews across multiple platforms. Some of the most influential platforms for local business visibility in AI responses are:

1. Google Business Profile (formerly Google My Business)
2. Yelp
3. Facebook Business Pages
4. TripAdvisor

While these are the most established platforms, you need to understand which local data platforms are actually the most important to you and your local business. Each industry has specialized review sites and directories. The goal is to gather detailed, expressive reviews across as many credible platforms as possible. AI assistants may rely on these reviews when answering local queries, so aim to:

• Gather detailed customer reviews across multiple platforms
• Ensure your business is listed on every relevant local directory
• Encourage customers to share specific experiences in their reviews
• Maintain consistent business information across all platforms

The goal isn’t just to be listed everywhere – it’s to have rich, detailed reviews that AI assistants can reference when answering questions about businesses in your area. Each positive, detailed review increases your chances of being recommended in local queries.

Technical Requirements for AI and Search Visibility

As AI assistants evolve, they increasingly rely on well-structured, accessible content. Many of the technical requirements that make your content AI-friendly also improve your traditional SEO and user experience – a win-win for visibility across all platforms.

Core Technical Requirements Think of these as your technical foundation. Each element helps both AI comprehension and search engine visibility:

• Clear HTML Structure Make your content hierarchy obvious through proper heading tags (H1, H2, H3) and semantic HTML elements. This helps AI assistants understand the relationship between different pieces of information.
• Screen Reader Compatibility If a screen reader can’t parse your content, AI assistants will likely struggle too. Ensure:
  • Alt text for images
  • ARIA labels where needed
  • Logical content flow
  • Proper table structures
  • Descriptive link text
• Performance Optimization Fast-loading pages aren’t just good for users – they’re essential for thorough AI processing:
  • Optimize image sizes
  • Minimize code bloat
  • Enable caching
  • Use CDNs when appropriate
• Mobile Responsiveness With mobile-first indexing now standard, ensure your content displays properly across all devices.

Bridging AI and SEO As search engines integrate AI into their results, maintaining strong SEO practices becomes even more crucial. Your content needs to satisfy both traditional search algorithms and AI systems:

• Keep URLs clean and descriptive
• Implement proper schema markup
• Ensure your sitemap is current
• Maintain a logical site structure
• Allow proper indexing of important pages
• Create detailed meta descriptions
• Use consistent internal linking

Remember: Google and Microsoft are now combining their traditional search rankings with AI-generated responses. This means technical optimization isn’t an either/or choice between AI and SEO – you need both for maximum visibility.

Monitoring and Measuring Your AI Visibility Success

After implementing your AI visibility strategy, systematic monitoring becomes crucial. Let’s explore how to track your progress and adapt to changing AI landscapes.

Tracking Your Progress Remember the tools we discussed earlier for monitoring AI responses across different platforms [reference to previous tools section]. Use these same tools to:

• Track your brand mentions in AI responses
• Monitor competitor mentions
• Identify new opportunities for visibility
• Assess the effectiveness of your content strategy

Regular monitoring should focus on the specific questions we identified in your customer research. Set up a routine schedule to:

• Test priority queries across different AI platforms
• Document changes in AI responses
• Track your content’s performance on key platforms
• Monitor review growth and sentiment
• Assess content syndication reach

Measuring Success While AI visibility can be less straightforward to measure than traditional SEO, look for these key indicators:

• AI assistants citing your content as a source
• Your brand appearing in responses to industry-specific queries
• Growing presence on authoritative platforms
• Increasing engagement across your content channels
• Natural growth in backlinks and citations

Future-Proofing Your Strategy The AI landscape evolves rapidly, requiring adaptability and forward thinking. Stay ahead by:

• Maintaining consistent, high-quality content production
• Following developments in AI training data sources
• Understanding which platforms influence specific AI assistants
• Building genuine authority through expertise sharing
• Adapting to new platform opportunities as they emerge

Remember: Success in AI visibility is a marathon, not a sprint. Focus on sustainable practices that build lasting authority while remaining flexible enough to adapt to new developments in AI technology.

Conclusion

Between one-fifth and one-third of people are already starting their search journey through AI chat, and this shift away from traditional search is accelerating rapidly. This isn’t a future trend to prepare for—it’s today’s reality.

While the path to AI visibility requires multiple strategies, start with what matters most: either strengthening your foundational content or building your review presence. If your business struggles with clear positioning and content, focus first on creating high-quality, consistent content that explains your value. If you have strong content but few customer voices, prioritize gathering detailed reviews on the platforms most relevant to your industry.

Remember, AI assistants need quality information from both ends of the customer journey—your voice explaining what you offer, and your customers’ voices validating your claims. Choose your starting point based on which voice needs strengthening, then expand systematically as you build momentum.

As AI technology evolves, the fundamental principles of visibility will remain constant: authentic expertise, validated customer experiences, and consistent, quality content across multiple platforms. The platforms and tools may change, but businesses that build a strong foundation of valuable content and genuine customer advocacy will be strongly positioned to maintain their visibility, regardless of how AI systems evolve.

The businesses that adapt to this new landscape now will have a significant advantage as AI continues to shape how people discover and evaluate services. The time to start is today.

Sebastian Chedal has over 27 years of experience in technology, marketing, and digital strategy. As a principal founder and consultant at Fountain City, he helps businesses navigate digital transformation and AI integration. His expertise spans strategic marketing, UI/UX, and technical implementation, with a particular focus on emerging AI technologies and their impact on business visibility. A longterm tech optimist, Sebastian regularly writes about the intersection of AI, business strategy, and digital marketing.

Sources:

1. Christopher Penn: Optimizing Content for Generative AI
2. Open Source Trained Dataset for LLMs
3. LLM Training Data: The 8 Main Public Data Sources
4. Make Your Brand Sourced and a Top Result in AI Search
5. How to Improve your Site’s Visibility in AI results
6. How to do SEO for AI based search engines
7. Preparing your brand for generative AI in search marketing

Special thank you to Christopher Penn for peer reviewing this article, and to Lizz Adams for sharing her methodologies.