Try this right now. Open ChatGPT and type the query your ideal client would use to find someone like you.
"What's the best SEO consultant for small businesses?" "Can you recommend a good CRM for freelancers?" "Who should I hire for website design?"
Whatever your version is, type it in. Read the response.
Are you in the answer? Or is your competitor?
If you've never done this before, the result might sting. Because there's a good chance ChatGPT is recommending your competitors by name, for the exact queries your potential clients are asking, and you had no idea it was happening.
The invisible loss
Traditional marketing has visible competition. You can see who's running Google Ads for your keywords. You can check who ranks above you on page one. You can monitor competitor social media campaigns. The battlefield is visible, and you can at least see who's winning.
AI recommendations are different. They happen in private conversations between a user and a chatbot. No public ranking to check. No ad dashboard to spy on. Someone asks ChatGPT who they should hire, ChatGPT says your competitor's name, and that prospect is gone. You never knew they existed.
This isn't a theoretical problem. Over 200 million people use ChatGPT weekly. Millions more use Perplexity, Gemini, Claude, and Grok. A growing percentage of these users are asking high-intent questions: "who should I hire," "what tool should I use," "which service is best for my situation."
Every one of those queries that mentions a competitor instead of you is a potential client you'll never see in your pipeline.
What this looks like in practice
Sarah runs a bookkeeping service for e-commerce businesses. She's been getting steady referrals and some Google traffic. Business is fine, but growth has flattened.
What Sarah doesn't know: when someone asks ChatGPT "What's the best bookkeeping service for Shopify store owners?", the AI recommends three specific competitors. Sarah's business isn't mentioned. Not because she's bad at what she does, but because the AI has never encountered enough information about her to form a recommendation.
Meanwhile, one of her competitors has been featured in a few industry publications, has strong reviews on multiple platforms, and maintains a clear, specific positioning on their website. The AI picks up these signals and recommends them confidently.
Sarah's competitor isn't necessarily better. They're just more visible to the systems that are increasingly driving discovery.
Or take Mark, a web designer who specializes in websites for therapists. He ranks well on Google for his niche keywords. But when a therapist asks Perplexity "Who's the best web designer for therapy practices?", Perplexity recommends someone else. That someone else has fewer Google rankings but more third-party mentions, clearer positioning, and a stronger presence on review sites.
Mark's SEO advantage doesn't transfer automatically to AI platforms. Different systems, different signals.
Why AI recommends your competitors
AI platforms make recommendations based on the information available to them. That information comes from several sources.
Training data includes published content from across the web. If your competitors have been written about more frequently, in more contexts, and by more sources, the AI has a stronger signal for them.
Real-time browsing (for platforms that support it) pulls from current web content. Review sites, comparison articles, industry directories, and your own website all contribute to what the AI knows about you.
Third-party mentions are particularly powerful. What others say about your business carries more weight with AI than what you say about yourself. One independent review mentioning "this is the best bookkeeping service for Shopify stores" teaches the AI more than ten pages of self-promotional content on your own site.
Clarity of positioning matters enormously. If the AI can't quickly understand what you do and who you serve, it won't recommend you. Vague positioning like "we help businesses grow" gives the AI nothing to work with. Specific positioning like "bookkeeping for Shopify stores doing $500K-$5M in revenue" gives it a clear match for relevant queries.
The compounding problem
AI recommendations create a feedback loop that works against you if you're not in the conversation.
When AI recommends a competitor, that competitor gets more traffic, more clients, more reviews, and more mentions. These new signals feed back into the AI's knowledge base, making it even more likely to recommend them in the future.
Meanwhile, your absence from AI recommendations means fewer new clients, fewer reviews, and fewer mentions. The gap widens over time.
This is why early awareness matters. The businesses that identify and address their AI visibility gaps now will build momentum. The ones that discover the problem two years from now will face a much larger gap to close.
How to find out where you stand
Step one is simple: manually test. Run 10-15 queries that your ideal client would ask across ChatGPT, Perplexity, Gemini, and Claude. Record which queries mention you, which mention competitors, and which mention nobody relevant.
This gives you a baseline snapshot. But it's just a moment in time. AI responses change as the underlying data changes, so what the AI says today might differ from what it says next month.
For ongoing tracking, tools like Mentionable automate this process. You set up the queries that matter to your business, and it monitors whether AI platforms recommend you, your competitors, or someone else entirely. You get alerts when things change.
Whether you track manually or with a tool, the point is the same: you need to know where you stand before you can improve.
What to do when you're not being recommended
The fix isn't quick, but it's straightforward.
Sharpen your positioning. Make it unmistakably clear what you do, who you serve, and what makes your approach different. This clarity needs to be consistent across your website, your profiles, your content, and any third-party mentions. The AI needs to be able to map your business to specific queries. Give it an easy match.
Build third-party credibility. Get reviewed on relevant platforms. Pursue editorial mentions in publications your audience reads. Participate in podcast interviews. Contribute to industry discussions. Each mention creates a signal that AI platforms pick up.
Create content that demonstrates expertise. Not just "we offer these services" content, but genuinely useful content that showcases your knowledge. Case studies with specific results. Guides that solve real problems. Analyses that offer original insight. This builds the topical authority that AI systems reward.
Be specific about your niche. The more specific your positioning, the more likely you are to be recommended for targeted queries. "Marketing consultant" is too broad. "Email marketing strategy for B2B SaaS companies" is specific enough for AI to match you to the right queries.
The uncomfortable truth
Every day you're not visible to AI platforms, potential clients are being directed to someone else. Not because that someone is better than you. Because the AI knows about them and doesn't know about you.
The good news: this is fixable. The signals that drive AI recommendations, third-party credibility, clear positioning, demonstrated expertise, are the same things that build a strong business generally. You just need to be intentional about building them in ways that AI systems can recognize.
The sooner you check where you stand, the sooner you can start closing the gap. Your competitors may already have a head start, but the race is just beginning.
