There's a subtle but massive difference between an AI mentioning your brand and an AI recommending it. A mention is "Company X exists and does email marketing." A recommendation is "For your use case, I'd suggest Company X because their pricing works well for solopreneurs and their automation features are solid." One informs. The other sells.
So what exactly is an AI recommendation?
An AI recommendation happens when a language model explicitly suggests or endorses a specific product, brand, or service in response to a user's question. It goes beyond a neutral reference. The AI is taking a position, telling the user "this is worth considering," often with reasons why.
This is different from a citation, where the AI references your content as a source of information. And it's different from a mention, where your brand name simply appears in the response. A recommendation carries an implicit endorsement. The AI is doing what a knowledgeable friend would do: pointing someone toward a specific option and explaining why it fits.
When someone asks Perplexity "what's the best time-tracking tool for freelancers?" and it responds with "I'd recommend Toggl for its simplicity and free tier, or Harvest if you need invoicing built in," those are recommendations. Toggl and Harvest aren't just listed. They're suggested, with reasoning attached.
Why should you care?
AI recommendations carry a type of trust that's hard to replicate through other channels.
Think about how people interact with AI assistants. They're having a conversation, asking for help, treating the AI as a knowledgeable advisor. When that advisor says "I'd suggest this tool," it lands differently than a Google ad or even a top-ranking blog post. It feels personal, even though it's algorithmic.
Research into user behavior shows that people tend to accept AI recommendations with less scrutiny than traditional search results. With Google, users expect to compare multiple options. With an AI recommendation, many users take the suggestion and act on it directly. The conversion path is shorter and the trust level is higher.
This also means the downside is significant. If an AI consistently recommends your competitor instead of you, you're losing deals at the most critical moment, when a buyer is actively asking "what should I use?" And unlike traditional search, where you can at least see your ranking and work to improve it, AI recommendations happen in private conversations you have zero visibility into by default.
What makes AI recommend one brand over another?
Several factors influence whether your brand gets recommended.
Brand presence across trusted sources. AI models build their understanding from a wide range of web content. If your brand is mentioned positively across authoritative review sites, industry publications, comparison articles, and community discussions, the model has more material to draw from when making a recommendation. A brand that only exists on its own website has a thin footprint that AI models treat with less confidence.
Clarity of positioning. AI models recommend brands they can clearly categorize. If your website clearly states who you're for, what you do, and how you differ from alternatives, the model can match you to relevant prompts. Vague positioning leads to vague (or absent) recommendations.
Sentiment and reputation. The tone of what's written about you online matters. Consistently positive reviews, testimonials featured on third-party sites, and favorable comparisons all feed into whether an AI presents your brand as a recommendation versus a cautionary tale.
Specificity of fit. AI recommendations often include qualifiers like "best for freelancers" or "great if you need simplicity." Your content should make these qualifiers easy for the AI to attach to your brand. If you're the best option for a specific audience, say so clearly and repeatedly across your online presence.
The binary nature of AI recommendations
Here's what really separates AI recommendations from search rankings: there's no gradual decline. In Google, position 5 still gets some clicks. In an AI recommendation, you're either named or you're invisible. There's no "sort of" recommended.
This binary dynamic means small improvements in your AI visibility can produce outsized results. Going from "not mentioned" to "one of three recommendations" is a dramatic shift in customer acquisition potential.
The honest truth
AI recommendations aren't fully controllable. You can influence them by building a strong, clear online presence, but you can't guarantee a specific outcome. Models change, training data shifts, and the same prompt can produce different recommendations on different days.
What you can control is awareness. Knowing where you're being recommended, where you're not, and how your visibility changes over time. That's the foundation for doing anything about it.
