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\n\t\tOpinions expressed by Entrepreneur contributors are their own.\t<\/p>\n
Sixty-four percent of consumers now use AI<\/a> tools to discover new products and brands. Among frequent online shoppers, that number rises to 66% \u2014 and 34% of them turn to ChatGPT first. If your brand isn\u2019t showing up in those answers, you\u2019re losing out on one of the highest converting referral traffic sources at the moment.<\/p>\n That\u2019s the new reality. Google still matters, but generative AI \u2014 ChatGPT, Gemini, Claude \u2014 now runs as a parallel recommendation engine. And it doesn\u2019t just mirror Google\u2019s top ten results. It pulls from a much wider set of signals to decide who gets mentioned and who gets ignored. For a brand with no history, no backlinks and no reviews, you\u2019re invisible to both systems simultaneously.<\/p>\n The good news? I\u2019ve seen new brands show up in AI recommendations before they\u2019ve cracked page one on Google. But there\u2019s no shortcut. Here\u2019s what actually works.<\/p>\n The fastest way to confuse an AI system is to tell it you do five things at once. I worked with a fitness tech startup last year that was positioning itself as a wearable company, a coaching platform and a wellness community \u2014 all at the same time. When we ran test prompts across ChatGPT and Gemini, it showed up in none of those categories. Zero.<\/p>\n We stripped the positioning down to one line: advanced wearables for runners. Within weeks of aligning everything around that single category, the brand started appearing in AI answers for running-related prompts.<\/p>\n And that\u2019s not just anecdotal. The GEO research paper out of Princeton<\/a> showed that deliberate optimization for generative engine responses improved source visibility by up to 40%. That optimization starts with clarity. If you haven\u2019t decided what category you own, nothing downstream will work.<\/p>\n Pick one. Lock it. You can expand later \u2014 but only after the machines know who you are.<\/p>\n Once you\u2019ve nailed your positioning, resist the urge to start churning out blog posts. Your first job is building what I call the identity seed set \u2014 the minimum footprint that tells AI crawlers \u201cthis brand exists, here\u2019s what it does, and here\u2019s where to verify it.\u201d<\/p>\n That means a homepage with structured, unambiguous information about your offering. An about page that names real people. Niche directory listings \u2014 not 50 generic ones, but the three or four that matter in your vertical. And review profiles on whatever platform your buyers actually trust, whether that\u2019s G2, Capterra or Trustpilot.<\/p>\n Here\u2019s why this matters technically: Perplexity\u2019s team explained in a Search Engine Journal interview<\/a> that their system doesn\u2019t retrieve whole pages. It performs sub-document processing, pulling roughly 130,000 tokens of the most relevant snippets from across the web. Small, clear text blocks travel better than dense, meandering narratives. If your brand information is scattered across inconsistent pages, the retrieval system has less usable material to grab.<\/p>\n Consistency beats volume every time. Get this wrong, and you\u2019ll spend months wondering why AI keeps recommending your competitors instead.<\/p>\n There\u2019s a critical gap between being findable and being recommendable. AI systems \u2014 much like a cautious investor \u2014 want corroboration before they put your name forward. You can say you\u2019re the best on your own website all day long. The model wants to see someone else say it too.<\/p>\n I saw this play out with a B2B services company in London. Solid product, clean website, great in-depth content and decent positioning. But zero external mentions. No reviews, no press, no third-party lists. ChatGPT wouldn\u2019t touch them. We got them listed on several services comparison sites and helped secure a handful of genuine G2 reviews. Three months later, they were showing up in key purchase-intent prompts.<\/p>\n The data confirms this matters at scale. Research by Seer Interactive<\/a> analyzed over 3,000 queries across 42 organizations and found that brands cited within AI Overviews received 35% more organic clicks and 91% more paid clicks compared to brands that weren\u2019t cited. External proof isn\u2019t a nice-to-have. It\u2019s the mechanism.<\/p>\n The first three steps give you a foundation. This step is what makes AI systems keep recommending you.<\/p>\n I\u2019ve seen brands land a few great media features, ride the wave for a half year or so and then vanish from AI answers entirely. The problem? AI doesn\u2019t just want proof; it wants recency. And patterns. LLMs want to encounter your brand across multiple independent contexts over time before recommending you becomes a low-risk output.<\/p>\n For a new brand on a limited budget, this doesn\u2019t mean hiring a six-figure PR agency. It means building a loop. Get included in curated industry lists. Write guest pieces for niche publications. Send your product to reviewers who cover your space. Contribute meaningfully in communities where your audience hangs out \u2014 Reddit, niche Slacks, industry forums \u2014 so those contributions get indexed and referenced.<\/p>\n What matters often isn\u2019t any single mention. It\u2019s the compounding effect and the recency signal. If all your external validation is from a year ago and there\u2019s nothing fresh, AI systems notice.<\/p>\n This is the step almost everyone skips at the moment \u2014 and it\u2019s the one that separates brands that stay in AI recommendations from those that appear briefly and then fade.<\/p>\n Even if ChatGPT recommends you today, that can change next week. Competitors are optimizing for this. Negative reviews accumulate. Models get updated. Similarweb\u2019s 2026 Generative AI Brand Visibility Index<\/a> tracked 113 brands across ChatGPT, Gemini and Perplexity and found dramatic swings in visibility over just nine months.<\/p>\n Tools like Semrush and Peec let you programmatically track how often AI systems mention your brand. Or go low-tech: Open ChatGPT, Gemini and Claude once a month and run a fixed set of prompts. Test \u201cbest X for Y\u201d to see if you show up. Test \u201cX vs. Y\u201d to see if you\u2019re considered a viable alternative. Test \u201cwhy not X\u201d to find out what evidence gaps are keeping you out.<\/p>\n When you\u2019re missing from answers, the diagnostic question is always the same: What proof is the model not finding? Ask the AI directly. It\u2019ll tell you \u2014 and while you should take the answer with a grain of salt, it\u2019s a surprisingly useful starting point.<\/p>\n The brands that win in AI search won\u2019t necessarily be the ones with the biggest budgets. They\u2019ll be the ones that understand what retrieval systems need to see before they\u2019re willing to put a name forward. That bar isn\u2019t impossibly high. But it is specific \u2014 and for new brands willing to build methodically, the window is wide open.<\/p>\n<\/p><\/div>\n1. Pick one category and own it completely<\/h2>\n
2. Build a machine-readable identity before you chase rankings<\/h2>\n
3. Stack proof signals outside your own domain<\/h2>\n
4. Earn ongoing external validation, not a one-time PR push<\/h2>\n
5. Track your AI visibility like you track your SEO<\/h2>\n
Key Takeaways<\/h2>\n
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