AI search brand discovery discovery is changing how consumers and business buyers find, evaluate, and choose brands—often before they visit a company’s website. In this Q&A, Leah Nurik, CEO of Brandi AI, explains what that shift means for marketing leaders responsible for brand visibility, website traffic, and customer acquisition. She examines how Search Engine Optimization (SEO), Answer Engine Optimization (AEO), and Generative Engine Optimization (GEO) work together; why AI citations, sentiment, and brand narrative matter; and how public relations, earned media, and human-created content can help brands earn visibility and recommendations in AI-generated answers.
Key Takeaways
- AI is reshaping brand discovery. Consumers and business buyers increasingly use AI-generated answers to research, compare, and evaluate brands before visiting company websites.
- SEO remains essential, but GEO is broader. Technical SEO helps AI systems find and read web content, while Generative Engine Optimization also addresses citations, authority, sentiment, and brand narrative.
- Lower website traffic does not necessarily mean fewer opportunities. Visitors arriving after conducting research through AI may be better informed, more qualified, and more likely to convert.
- Citations and sentiment determine how AI presents a brand. Marketers must monitor not only whether their brands appear in AI answers, but also which sources influence those answers and whether the resulting portrayal is accurate and favorable.
- Sustainable AI visibility requires credible evidence and cross-functional collaboration. Public relations, earned media, content, brand, product marketing, digital strategy, and SEO must work together to build authority instead of trying to manipulate AI algorithms.
About the Signal & Noise Interview on AI-Powered Brand Discovery
Nurik joined Signal & Noise hosts Rio Longacre and Brett House on September 3, 2026, to discuss how artificial intelligence is rewriting the rules of brand discovery. For more than two decades, digital marketing followed a familiar path: rank in search, earn the click, drive website traffic, and convert the visitor. ChatGPT, Google AI Overviews, Perplexity, Gemini, Claude, and other AI experiences are disrupting that model by answering buyers’ questions directly.
The following Q&A was condensed and lightly edited from the Signal & Noise podcast interview.
Q: Is AI-powered discovery the biggest change to online brand discovery since Google established traditional search?
Leah Nurik: Yes, without a doubt. I think we’re on page four of the prologue to War and Peace. It’s just the beginning.
This is a complete paradigm shift—not only in how marketers do their jobs, but also in how consumers and business-to-business buyers discover brands. The people responsible for ensuring a buyer discovery path within the marketing organization are not completely different, but there are more of them. Digital used to own the clickstream, visibility, traffic, and online demand generation. Now multiple marketing disciplines are involved.
That is a fundamental shift. It is going to change how marketing organizations are structured, how their teams work together, the talent they acquire, and what their budgets look like.
The buyer is also more in control. In the traditional model, the brand had more control because search returned a blue link. People had to click through multiple results and conduct the research themselves. Now AI is summarizing the information and helping buyers go deeper before they ever reach a company’s website.
Q: Does traditional SEO still matter when buyers increasingly receive AI-generated answers?
Leah Nurik: SEO is still incredibly important. Reports of SEO being dead are widely exaggerated.
An AI engine cannot find or read your website if it is not indexed. If your site lacks the technical structure required to be indexed, found, and read, your brand cannot appear. SEO is not dead; it now plays a role alongside everything else that contributes to how a brand is positioned and mentioned, and to the narrative presented in an AI-generated response.
I like to think about the difference as syntax versus semantics. Traditional search was heavily focused on matching. AI-powered discovery is more about storytelling and readability. Technical structure remains important, but so do the content, the story behind it, and the authority and credibility of the words you use. Those factors were not nearly as important before.
Q: What is the difference between SEO, AEO, and GEO?
Leah Nurik: SEO is Search Engine Optimization: the technical structure that helps a search engine find a page and return a blue link.
There is more overlap between Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). Some people use AEO and GEO interchangeably. We are in the GEO camp, but I define them differently for clarity.
Answer Engine Optimization asks, “How do I optimize the answer?” It focuses on how the answer itself comes back. Generative Engine Optimization asks, “How do I optimize my brand for answers and for generative engines in general?” I look at GEO as the umbrella, with AEO underneath it.
Those terms may eventually combine. Analysts and companies are using different language right now, and you will hear AEO and GEO used interchangeably. For our purposes, however, there is a useful nuance between them.
Q: How is AI changing consumer and business buyer behavior?
Leah Nurik: People are increasingly using large language models, but that does not mean everyone is going directly to a standalone AI platform. My 83-year-old father is not using ChatGPT; he is still using the Google search bar. But he is still using AI because AI is built into that experience.
Even if someone remains in the preexisting paradigm of a Google or Bing search bar, that person is likely receiving an AI-generated response. People can argue about who is adopting which large language model or say they will never adopt one. It does not matter. AI is here to stay in consumer behavior regardless of the model or search bar being used. The algorithm is different. Full stop.
People may have doubts about the AI responses they receive, but research shows they also tend to trust those answers to a certain extent. A user might take the response with a grain of salt, but will still accept much of it at face value and continue researching within that experience. Wherever people go, they are increasingly receiving summaries generated by a different kind of algorithm, and that changes how they discover and evaluate brands.
Q: If AI reduces website referral traffic, are the visitors who still arrive more qualified?
Leah Nurik: We hear horror stories from customers about traffic dropping by around 30 percent on average across business-to-business and business-to-consumer companies. But if a company has a good presence in AI search, the traffic it does receive can convert at a much higher rate because those people are already educated. They have done their research before they arrive.
I have been in the software business my entire career. Historically, if 15 percent of demo requests turned into an actual conversation, that could be considered a good bottom-of-the-funnel conversion. Now, when we receive demo requests, more than 50 percent convert into conversations.
Before, somebody might click 10 or 12 links, request several demos, and then attend only the first one. Now people come to the website highly qualified. They may request only two or three demos because a large language model has already helped them get closer to the answers they want.
Q: How should marketers rethink budgets and attribution as discovery shifts from clicks to AI-generated answers?
Leah Nurik: Marketing spend is going to have to spread out. It will not be only about ads. There are many ways to invest in optimizing for AI.
The traditional path was an ad, a landing page, and a conversion. Marketers could optimize that clickstream and measure a relatively low conversion rate. Now the people who do arrive may convert at a higher rate. The question becomes: How do I optimize my presence in the response?
That could mean investing with a public relations firm that earns media coverage. Earned media can build authority, generate mentions, reinforce credibility, and help shape how the brand’s story appears in answers. That is more of a brand-awareness play than a last-click play.
The source of an AI answer is not always obvious, and AI referral traffic is not replacing all the traffic brands once received from Google or paid ads. Many companies are instead seeing a spike in direct traffic. Someone researches the best mouse, decides which product is right, and then types the company’s address directly into the browser or goes straight to Amazon to buy it. That is a fundamentally different path.
Q: What does AI-powered discovery mean for publishers and the open web?
Leah Nurik: Publishers are asking how to change their monetization models. Trade publications once sold cost-per-lead programs, webinars, ebooks, email marketing, and forms because they had a dedicated audience in a technical or niche market. Many assumed declining traffic meant they were losing that business.
Now data can show which domains are authoritative in each market. Some are not household-name publishers. A long-tail publication—or even an individual writing a specialized blog—might once have been considered a tier-three outlet or an afterthought in media relations. That source may now drive brand mentions and authority in AI answers.
Publishers need to ask how to monetize content in ways they may not have considered. Forbes, for example, has monetized contributed articles through its council programs for years. That content supported thought leadership and backlinks, but it can now also influence AI visibility. Will other publishers develop similar programs? Will marketplaces emerge that resemble buy-side and sell-side advertising platforms, but for content? Those models are still to be determined, but they are in play.
Q: Should publishers block AI crawlers to protect their content?
Leah Nurik: My advice is: Do not make your content unreadable. If publishers want to monetize in this new environment, being readable is part of the way forward. It also helps create a connection between the publication’s brand and its credibility. When content is cited, the publisher still has an opportunity to receive referral traffic from an AI response.
The New York Times, for example, sued AI companies and blocked crawlers, while The Wall Street Journal formed partnerships with large language models. Some Wall Street Journal material behind the paywall can still be read and cited. An AI response can say, “The Wall Street Journal reports…” That repeated exposure creates a connection in a consumer’s or business buyer’s mind between the publication and credibility.
If a publication is absent from the core way buyer discovery now occurs, it is missing those touchpoints. Over time, that could mean lower subscriber revenue and a loss of relevance or stature compared with publications that appear in AI-generated answers.
I think it is extremely myopic to look only at a year or 18 months when the market is shifting this dramatically. Publishers that refuse to participate are already losing visibility, brand connection, and opportunities to build credibility in the new discovery paradigm. In my opinion, they risk lasting damage because potential subscribers are not forming that emotional connection with the publication inside AI search results.
Q: Why are citations so important to AI visibility?
Leah Nurik: Citations are what it is all about. A cited source informs the answer.
Imagine that I have created a mouse that disrupts the market. It is sustainable, ergonomic, rechargeable, and easy to connect. AI might cite my company’s blog, an article in Forbes, customer reviews, and other unpaid sources. Together, those citations help define the market and influence how people understand the product.
That is brand advertising in a different form. Citations provide the evidence that helps an AI system explain a category, describe a company, and decide which brands to include in the answer.
Q: How do AI-generated recommendations reflect judgments about brands?
Leah Nurik: AI gives users a curated list of what it determines to be credible and authoritative, but it is often difficult to get an AI system to take a clear stand. If you ask, “What is the best mouse?” or “What is the best allergy medicine for this situation?” it will usually provide several options and say each is good for something different.
You often uncover what it really thinks when you ask directly how one company compares with another. A question such as “How does Acme Corporation compare with Beta Corporation?” reveals the substance hidden in the model’s logic.
That is where marketers need to look. A brand should not focus only on whether it was mentioned or cited. It needs to know whether the answer is accurate or inaccurate, positive or negative. That deeper content of the answer is critically important.
Q: What can marketers do when AI misrepresents a brand or uses outdated information?
Leah Nurik: Inaccuracy can happen for different reasons. The AI might cite information that is outdated, perhaps from training data, or it may be unable to find an answer and simply make something up. It can be both.
Brand marketers therefore need to understand what is being said about the brand and where the information is coming from. Then they must take action—by producing content or otherwise addressing the issue in a way that answers the questions people are asking.
If an AI system can find a recent, credible, and authoritative answer to a question, it will bring that information back. If it cannot, it may make something up or rely on very old training data.
Q: How do the sources influencing AI answers vary by industry and product category?
Leah Nurik: It depends on the market. Nobody likes to hear that, but the domains cited for a company such as HubSpot are different from those cited for an automotive brand such as Jeep.
People may say that 90 percent of citations come from social media and earned media. That may be true in some markets, but not in all of them. Marketers have to understand what is happening in their specific sector or product category: Where does the information come from? Is Reddit important? Is LinkedIn important? Which publishers and other sources influence the answers?
For automotive and other consumer categories, we have seen more than 90 percent of citations come from earned media and social sources rather than owned corporate websites. In the customer relationship management market, corporate sites play a larger role. HubSpot and Salesforce are among the most cited sources, while LinkedIn also appears and Reddit is further down the list.
The right AI visibility strategy therefore depends on the sources that carry authority in the particular market.
Q: Can brands game AI algorithms to improve their visibility?
Leah Nurik: There are ways to influence AI visibility—that is why we have a business—but marketers should not try to game the system or trick the algorithm.
For us, that is partly an ethical position, but it is also good business. Everybody remembers how search-engine updates wiped out tactics designed to manipulate rankings. If you genuinely want to win your category, you cannot trick Reddit; you will get banned. You cannot flood review platforms with fake reviews and expect that strategy to work over the long term.
Instead, publish credible, authoritative content and bring a good product to market. If you have a crisis because there is a problem, address the crisis through content and earned media.
I have spent my career urging brands to be mission-driven, live their brand promise, and live the truth. AI is regulating that without regulation. If a company is not fulfilling its promise, AI will find the evidence in sources such as Reddit, Trustpilot, or G2. The brand will be found out.
Q: Why does GEO require collaboration across marketing disciplines?
Leah Nurik: That message is resonating, although it depends on the organization. Many digital marketers need to shift their mindset.
GEO or AEO may start with a digital team, but it evolves to involve brand, communications, product marketing, and growth marketing. People who are already thinking across disciplines understand the shift.
We are still at the beginning, so some organizations will experiment early while others wait to see how everything develops. Waiting may make sense to a risk-averse company, but it also means missing an opportunity to define a category. The knowledge, authority, and credibility being established in AI engines today could shape those engines over the long term.
Q: How should brands evaluate paid tactics and content created specifically for AI systems?
Leah Nurik: It is early. ChatGPT is just beginning to roll out and experiment with ads. There are also questions about sponsored content and text-based or “markdown” pages designed for readability by AI.
The underlying idea is similar to creating owned content or earning media that reinforces authority and credibility, shapes the brand narrative, and increases mentions in AI answers. A company might pay a publisher to post a readable page containing accurate positioning, product information, or a current offer. You can call that a markdown ad or sponsored content; the intent is the same.
The question is how the models will respond. Could they penalize a publisher or brand for trying to manipulate them? We do not know yet. Brands need to decide whether to risk becoming the JCPenney of the AI world—penalized for gaming a system—or publish authoritative content that tells the true story, supports the brand promise, and remains valuable as models change.
Organic authority future-proofs the brand. It reduces the risk that an optimization tactic will become a liability after the next model update.
Q: Do marketing organizations need to hire dedicated GEO specialists?
Leah Nurik: What an organization needs is a strong marketing leader who can create a team of collaborators. Public relations plays a role. Digital, content, product marketing, brand, and growth marketing all play roles. Outside agency partners also contribute.
The organization should be able to connect those disciplines and measure their impact. If the paid team is creating landing pages, are those pages being read and informing AI? If the company pays a public relations agency to earn media coverage, is that work increasing AI visibility?
One person cannot do all of it. Public relations and SEO are highly specialized disciplines. If you could find one person who could pitch The New York Times, explain complex stories simply, optimize every page for technical SEO, and write great content, that would be extraordinary. In practice, no one person possesses every one of those talents.
You need a leader who understands the disciplines and the different personalities behind them, creates collaboration, and empowers the team with technology.
Q: Will AI eliminate the need for specialized marketers and human-created content?
Leah Nurik: Our data shows that well-written human content—optimized for GEO, structure, and readability—is sticky. It lasts longer. You cannot press a button and make everything good. I do not think we are heading toward a world in which an agent replaces all of those specialized skills.
Part of the art of marketing and storytelling is the uniqueness of the point of view. AI, by definition, synthesizes what already exists. If you want to stand out and connect emotionally and empathetically with prospective buyers and customers, you need that uniqueness. AI cannot be unique in that way. It may be able to think and solve problems, but it cannot create the same empathetic and emotional connection.
That human connection is central to advertising. It is why people buy.
Q: Which will matter more in five years—SEO or GEO?
Leah Nurik: GEO, absolutely—100 percent. SEO is not going extinct, but it becomes a tactic within GEO and AEO that helps ensure findability and indexability.
Q: What widely accepted AI marketing advice do you reject?
Leah Nurik: The idea that search and brand discoverability are about tactics rather than strategy. People are always trying to trick the algorithms and game the system. I cannot stand it. It gives me all the ick.
Q: What AI visibility signal should every brand monitor?
Leah Nurik: Deep sentiment and brand narrative. It is not only about whether the brand is mentioned. Is it being represented accurately? Is the portrayal positive or negative? The ability to mine that deeper sentiment and narrative is at the core of understanding AI visibility.
Q: Which marketing discipline becomes more important in the AI discovery era?
Leah Nurik: Public relations and earned media, without a doubt. PR was down and out for a while, and now it is back—collaborating with its digital counterparts.
PR is not just press releases. Public relations professionals are storytellers. They are the people who explain complex ideas in easy-to-understand ways. It is a unique, sophisticated discipline. PR professionals have to persuade reporters and other independent people to act even though they have no power over them, so they must be creative and smart.
The storytelling still has to be backed by substance. But when brands need authoritative third-party sources to help AI systems find, understand, trust, and describe them, the value of credible earned media becomes clear.
How Brands Can Earn AI Recommendations
AI is becoming a new front door to brand discovery. The brands that succeed will not simply rank highest or attract the most clicks. They will provide enough clear, credible, and current evidence for AI systems to find them, understand their position, represent them accurately, cite authoritative sources, and recommend them with confidence.
For marketers, the immediate task is broader than adding another optimization tactic. AI visibility requires coordination across technical SEO, content, brand, product marketing, digital strategy, public relations, and earned media. The goal is to build a coherent and trustworthy public narrative—one that holds up wherever buyers ask AI what to consider next.
Schedule a free Brandi AI demo to see how Brandi AI can help your organization understand how its brand appears in AI-generated answers and identify opportunities to improve its visibility, citations, sentiment, and narrative.