A potential client asks an AI tool for advice about a challenge. The answer explains their options, names some businesses and offers reasons for considering them.
Your business could enter that conversation before the person knows your name. But what would give an AI tool a reason to include you?
In the latest episode of The Visibility Advantage Podcast, I spoke with Tony Restell, founder of Social Hire, about AI discoverability. His team has been working on this for its own business and early clients, examining how businesses appear in AI-generated answers and recommendations.
The conversation builds on our previous episode about what makes expertise believable. Once you have credible expertise and evidence of your work, the next question is how someone might encounter it when researching a challenge.
Here are seven questions to consider, drawing on Tony’s experience and the practical implications for your own professional visibility.
How could potential clients find you before they know your name?
They could encounter your expertise through an answer to a question they are already asking.
Tony used the example of a retail business trying to reverse a decline. Its initial research might focus on possible actions rather than which consultancy to hire. A consultancy that has published a useful explanation of that challenge could become relevant during this earlier stage.
That gives us a broader way to think about content. Your services page explains what someone can engage you to do. Your articles can explain the situations in which that work becomes valuable.
Consider the questions new clients bring to your first conversation. What have they already tried? What are they uncertain about? What prompted them to seek advice?
Those questions can reveal opportunities to publish something useful before the next potential client contacts you.
What is the difference between being mentioned, cited and recommended?
These outcomes tell you different things about your visibility.
A mention includes your name or business. A citation identifies your content as a source for part of an answer. A recommendation presents you as a possible provider, ideally with an explanation of why you fit the person’s needs.
When reviewing an AI answer, look at the context surrounding your name. Does it describe your expertise accurately? Does it identify the right audience? Are the reasons for considering you supported by evidence?
An accurate citation can introduce your thinking to someone new. A relevant recommendation can bring you into their consideration. An incorrect description may reveal information you need to clarify online.
How does clear positioning support AI discoverability?
Clear positioning gives people a more specific explanation of when your expertise is relevant.
Tony described Social Hire’s focus on particular client sectors, including recruitment agencies, management consultancies, corporate training companies and SaaS businesses. His reported results relate to those niches rather than a broad claim to be the best agency for everyone.
You can apply that thinking to your own website and LinkedIn profile.
“Experienced consultant working with organisations of all sizes” leaves the reader to work out whether you suit their situation. Explaining the challenges you address, the people you work with and the experience you bring gives them more to assess.
Start with one type of work you want to attract. Make sure your introduction explains it clearly, then support that explanation with relevant examples.
You can still show the breadth of your experience. Give it a clear point of entry.
What role does schema markup play?
Schema markup is structured information in a website’s code that describes aspects of the business and its pages. Tony places considerable emphasis on it in Social Hire’s approach.
For a business owner, a useful starting point is to ask your website provider what markup is already present, whether it is accurate and whether it matches the information visitors can read.
There is also an important qualification. Google’s guidance says no special schema markup is required to appear in AI Overviews or AI Mode. Its existing search practices remain relevant, and structured data must match the visible content.
So treat schema as part of a website review, alongside clear wording, accessible content and sound search fundamentals. Adding it does not guarantee a recommendation.
You can read Google’s guidance on AI features and your website for the technical context.
Why does evidence beyond your website matter?
Your website explains your expertise from your own perspective. Other sources can support that explanation.
Tony identified external credibility as another part of Social Hire’s approach, discussing reviews, industry directories, articles, videos and relevant online discussions.
The practical question is whether someone researching you can find evidence that supports your claims.
A detailed client recommendation can explain the challenge you addressed and the value of your contribution. An interview can demonstrate your judgement. A case study can show how you approached a situation and what happened.
Review your strongest claims about your work. Then ask what evidence a prospective client could find to assess them.
This connects directly to the Link∙Ability Authority Audit: examining what you claim, what you demonstrate and what others corroborate.
What kinds of content could you publish?
Begin with questions you hear repeatedly from people who could become clients.
Tony gave the example of whether a business should manage social media internally or outsource it. Someone asking that question may still be exploring their options, but a useful answer can explain the decision and demonstrate relevant expertise.
For your own content, choose a question and answer it properly. Explain the circumstances, the available options and the factors that affect the decision. Add an example where it improves understanding.
Tony also reported seeing LinkedIn articles and newsletters cited more prominently than everyday posts in his work. That is an observation from his experience, rather than a promise that any particular article will be cited.
Long-form content gives you room to explain your reasoning. Clear question headings can make it easier for readers to locate the part they need.
Before creating something new, review your existing articles. You may already have valuable answers that need a clearer introduction, an updated example or more specific headings.
How can you assess whether your visibility is improving?
Choose a small set of relevant questions and monitor the answers over time.
Tony described tracking buyer questions across several AI tools. He also discussed how results can vary, which makes a single encouraging search an incomplete picture.
Record the question, tool, date and relevant context. Note whether your business was mentioned, your content was cited or you were recommended. Check the accuracy of the description and save the sources used.
Repeat the exercise periodically, including a few natural variations in wording. The aim is to understand patterns across the questions that matter to your business.
Alongside that monitoring, ask new enquiries how they found you. This helps connect what you observe in AI answers with actual business conversations.
Where can you begin?
Choose one client challenge you want to be known for addressing.
Check whether your website and profile explain that work clearly, whether you have published a useful answer to a related question, and whether credible evidence supports your expertise.
That gives you a manageable starting point for improving AI discoverability and a specific area to monitor.