New data goldmine forming under brands' noses

The future of search is here and it's not a new tool or an algorithm update. It's a bold leap into something entirely new, propelled by soaring AI use. The SEO playbook we've all relied on for the past three decades? It's time for a major rewrite and a new name - GEO (Generative Engine Optimization). 

What is GEO? And why does it matter?

GEO goes beyond keywords and favors clear, useful content that helps generate accurate and comprehensive responses to user prompts. It prioritizes context so heavily that the old rule, "content is king" is quickly fading; context is now claiming the throne. So, what are the rules of this new era? The only sure way to know is to look at the data.

How are people using AI search, and what insights can brands learn from it? 

We analyzed data on AI prompts to uncover how users interact with AI, the types of things they are looking for, and what it might mean for brands. The findings are rich (we hope you agree!)

Most AI prompts are informational. Nearly a third are commercial.

Nearly 60% of all AI prompts are informational in nature, meaning users are actively trying to learn, explore, or understand a topic. This kind of curiosity often reflects early-stage interest or even intent. After all, people typically ask questions about things they care about or need. For example, a prompt such as "How can video analytics improve safety?" isn't just about knowledge; it signals interest in potential solutions.

What's especially important for brands: roughly 30% of prompts are commercial. These queries involve direct product or service research, things like "best video analytics for airports" or "compare video analytics systems for 5,000+ cameras." This signals a clear shift. Here, we instantly notice that AI is becoming a powerful top-of-funnel discovery engine.

Takeaway: If you're not optimizing for AI discoverability, you're most likely missing where real consumer curiosity is happening.

AI users speak in imperatives and want the best.

Language patterns reveal a heavy use of directive verbs ("explain," "list," "provide") and superlatives ("best", "top"). Consumers are no longer going from search result to search result trying to build the answer they need; they're telling the AI exactly what they want, and expecting a clear answer, often one that ranks or compares.

What this means is that your content strategy needs to answer superlative-driven queries with clarity and confidence.

Takeaway: If your product or service is the "best," you'll need the proof and a format that AI can parse and deliver e.g., question-based content, structured lists, and ranking blogs.

Prompt sentiment skews neutral-to-positive.

Approximately 49% of prompts carry a neutral tone, while 43% are positive, often polite or enthusiastic. Our data shows that only 7% had negative sentiment, typically in the form of complaints or frustration.

This paints a clear picture: users approach AI with a collaborative mindset. They treat it more like a trusted advisor than a customer service chatbot (who has patience for those?).

Takeaway: Tone matters. You may want to review and update your brand tone of voice to make sure what you’re putting out there is approachable, solution-oriented, and helpful, even when dealing with pain points or challenges.

Users prefer to ask, not just type keywords.

About 39% of prompts are phrased as questions, and 19% as direct commands (e.g., "List 5 alternatives to Zoom"). The remaining 42% are statements or fragments, e.g., "best content calendar tools". They are keyword-rich but conversational in structure.

Takeaway: It's a good idea for brand content to align with natural language queries, beyond keyword stuffing. As mentioned in #2 above, this can include question-based content, lists, and comparisons.

Most popular topics: general knowledge, AI, business & product comparisons.

When we cluster prompts semantically, six major themes emerge:

• General knowledge (over 50% of all prompts): broad range of informational queries.

• AI & tech help: programming, computing best practices etc. 

• Business & marketing advice: market research, business plans, strategy etc. 

• Finance & investment questions: the stock market, investing etc. 

• Career and education: resume tips, job interview tips, career guidance and the like.

• Product research & comparisons: commercial investigation queries - this is where words like 'best', 'top' or 'alternative' come into play. 

• Navigational and web queries: safety of links, summary of web pages etc.

Of all the above, product-focused prompts in particular, e.g., "best project management software" or "compare Nike vs Adidas running shoes", show users using AI as a shopping assistant, not just an encyclopedia. They aren't just Googling anymore; they're consulting.

Takeaway: Being found is no longer the main goal; it's being recommended.

Final thoughts: AI search is where consumer intent is real.

More and more users are turning to AI search because it strips away the noise of traditional engines: no clickbait headlines, no cluttered results, no sponsored detours. Users enjoy expressing raw, unfiltered intent via natural language. And what that intent shows is simple: people want super fast, super clear, and super trustworthy answers (though AI still has work to do on that last part).
 
For brands, this is a massive opportunity. But it’s also a fresh challenge: once again, your content needs to evolve. It has to perform when AI summarizes, compares, or ranks it. Your message must be clear, your brand value obvious. 

In our next posts, we'll get into the details of what it takes for your brand to become the answer when consumers ask.

Questions? Comments? Write to us at answers@limy.ai. We’re not as fast as an AI search engine, but we’re working on it.