How My Teenager Researches Colleges (And What It Means for Your Brand)

I watched my teenage daughter research colleges last month, and it reframed something I'd been thinking about for a while in a way that no industry report or conference talk ever had.

She didn't open Google. She opened ChatGPT and said something like "I want to study film production somewhere in the Midwest with a focus on set building and a student population under 15,000. What are my best options?"

She got a list with explanations in about thirty seconds. Each school came with context about the program's strengths, campus size, and relevant details she'd specified. She followed up with more questions, narrowing by cost and location, and within about ten minutes she had a shortlist that would have taken me hours of browsing individual university websites to assemble when I was her age.

I'm telling this story not because it's remarkable, I'm telling it because it's not remarkable. To her, this is just how you research things. There's no memory of opening ten browser tabs and scanning through search results. No habit of clicking through to page two of Google. The concept of comparing ten blue links and deciding which one looks trustworthy is as foreign to her as using a phone book would be.

This is the default research behavior for an entire generation that will be running departments, signing purchase orders, and making vendor decisions within the next few years. And the implications for brands that depend on being discovered and evaluated online are significant in ways most marketers haven't internalized yet.

When my daughter asked that question, the AI didn't return a ranked list of websites. It returned an explanation. It told her about specific schools, described what they're known for, and made contextual recommendations based on her criteria. The schools that showed up weren't the ones with the best SEO or the most aggressive digital advertising budgets; they were the ones the system understood well enough to recommend with confidence.

Some schools that offer excellent film programs didn't appear at all. Not because they're bad schools, but because the system didn't have a clear enough understanding of what makes their program distinctive. Their websites probably described themselves in broad terms, mentioned dozens of majors, and didn't emphasize the specific strengths that would have matched my daughter's query. The system couldn't connect the dots, so it connected different dots instead.

Now translate that to your industry. When a potential customer asks an AI assistant about your category, the system is doing the same thing. It's interpreting the question, identifying relevant entities, recalling what it knows about each one, and assembling a response. The brands that show up are the ones the system has a stable, specific understanding of. The brands that don't show up are the ones that are too vague, too inconsistent, or too poorly documented for the system to include with confidence.

What struck me most watching my daughter wasn't the technology; it was the trust. She didn't question the AI's recommendations the way I might have. She didn't cross-reference them against Google results or check university rankings. She used the AI's response as her starting point and built from there. The schools that were mentioned first shaped her entire perception of the landscape before she'd visited a single website.

That level of trust in AI-generated recommendations is only going to increase as these systems get better and as more people grow up using them as their primary research tool. The window for shaping a first impression is shifting upstream. By the time someone visits your website, their impression of your brand may already be partially formed by what an AI told them, and you may never even know that conversation happened.

This isn't a problem you can solve with better ad targeting or more aggressive remarketing. It's a problem you solve by making sure the AI has an accurate, specific, and favorable understanding of your brand before the question gets asked. That means the work happens months or years in advance, through consistent messaging, clear positioning, and content that helps machines understand who you are and what you're uniquely good at.

I keep coming back to my daughter's experience because it makes the abstract feel concrete. She wasn't evaluating websites, she wasn't comparing search results, she was having a conversation with a system that had already formed opinions about every school in the country, and those opinions determined which schools she'd even consider. The admissions offices that understand this dynamic and respond to it will have an enormous advantage over the ones that are still optimizing for page rankings.

The same is true in every industry. Your buyers are increasingly asking machines for guidance before they ask you for a demo, a quote, or a consultation. The question is whether the machine's answer includes your name and describes you accurately, or whether it sends the prospect in a different direction entirely before you've had a chance to make your case.

If that question concerns you, or if you've already run a query and found that your brand is missing from the conversation, my book Explainable: Why AI Recommends Some Brands & Ignores Others was written specifically for this moment. It covers the dynamics behind AI brand visibility and gives marketing teams a practical framework for making sure the machines get it right.