Katie Jewett

UPRAISE + rbb: Expanding our reach, elevating our impact

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The New Rules Of Brand Discovery In An AI-First World

Search used to be simple: a question, a page of blue links and a fight to win the click. Brand discovery was essentially a story about rankings, keywords and referral traffic.

That’s no longer how people find answers.

As AI assistants and generative search become the first place people turn to for information, many buyers are getting what they need before they ever reach a website. Instead of scanning a results page, they ask a question and receive a synthesized answer that blends sources and opinions into one concise response.

For communications leaders, that shift doesn’t just change SEO. It rewrites the rules of brand discovery.

Here’s how those rules are changing, and what to do about it.

Discovery Is Moving From Clicks To Answers

Traditional search rewarded the brands that could win the click. In an AI-first environment, your goal is to earn a place in the answer. People may learn about your company without ever visiting your website, and the quality of that impression often matters more than the volume of traffic you receive.

Brand discovery becomes less about “How much traffic did we get?” and more about “When someone asks about this problem, does our brand show up in the explanation, and how are we framed?”

AI-generated answers now function as a new layer in the funnel—one that sits between awareness and consideration.

Treat AI As An Earned Channel, Not Just A Technical One

It’s tempting to view generative search as a technical task to hand off to SEO or engineering. But AI systems don’t just crawl your website; they pull from news coverage, analyst commentary, reviews, social conversations, forums and reference sites. In other words, they read the same places humans do when they’re trying to decide whether a brand is credible. That makes AI visibility a communications issue.

Instead of asking which keywords to optimize for, ask which publications and platforms AI cites in your category, how often your brand is mentioned and whether those mentions reflect your messaging. If your PR, content and digital teams aren’t aligned around those questions, you’re leaving influence on the table.

Design Content For Both Humans And Machines

The good news is that the same elements that help AI understand your content also make it easier for humans to scan. Instead of overhauling your entire content strategy, the real shift is learning to structure information in a way that feels natural to readers but also gives generative engines clear signals about what matters most. Here are a few ways to structure your content for both AI and human readers:

  • Lead with a plain-language summary that answers the core question up front.
  • Use clear, descriptive headings that mirror how someone would phrase a question.
  • Break complex explanations into short paragraphs, bullets or numbered steps.
  • Include specific, sourced data points instead of vague claims.

Think of each section of your content as a snippet that could stand on its own in an AI answer. Long, meandering paragraphs without a clear takeaway are unlikely to be reused by either humans or machines.

Make Social Listening Your Early Warning System

AI doesn’t invent your reputation; it summarizes it. If a model describes your prices as high or your product as confusing, that perception started somewhere (in reviews, forums, social feeds or in news coverage). Those conversations shape the raw material that generative engines draw from, which is why social listening and media intelligence are strategic resources rather than nice-to-haves.

By paying close attention to the themes that surface repeatedly, from persistent complaints to recurring misconceptions, you start to see the narratives that AI is learning from. Once those patterns come into focus, you can act on them by clarifying your messaging, creating educational content or addressing legitimate concerns inside the business.

Rethink How You Measure Success

If you only judge success by traditional SEO metrics, you’ll miss a growing portion of how people discover brands. Success now includes whether you appear in AI-generated responses, whether you’re being cited as a source and how well those messages match your strategy. Even small volumes of AI-driven traffic can represent high-intent visitors, so it’s worth tracking how those referrals convert compared to traditional search.

This requires communications and marketing teams to build a measurement framework that accounts for both visibility (how often and where the brand appears) and narrative quality (what’s actually being said). That doesn’t mean abandoning core SEO and PR metrics. It just means you need to add AI-related insights alongside them. Traditional search continues to matter, but generative engines introduce an additional layer that you can’t afford to ignore.

Build An Integrated Discovery Strategy, Not A New Silo

Brand discovery no longer sits within a single discipline. PR, SEO, social, content, corporate communications and analytics all shape how AI interprets your brand. Treating generative engine optimization as a stand-alone initiative only creates another silo.

Use AI-driven discovery as a catalyst to unify the work your teams are already doing. Ensure your core stories appear consistently across earned, owned and social channels and that your subject matter experts appear in credible places with messaging that reinforces your positioning. You’ll need to tighten the connection between listening, publishing and monitoring so you understand not just what you’re putting into the world but how AI is picking it up and interpreting it over time.

Preparing Your Brand For AI-Driven Discovery

AI won’t replace the fundamentals of strong communication. Clarity, credibility, relevance and consistency will always matter. What AI will do is reveal where those fundamentals are weak and increase the pressure to strengthen them.

The brands that excel will be those that treat generative search as an extension of their storytelling, understand how they’re perceived today and create content that both humans and machines can easily trust, reuse and share.

You don’t need to become a machine learning expert. You do, however, need to take ownership of the narrative that AI repeats about your brand before someone else defines it for you.

This article was originally published on Forbes.com

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