Nurik explains how AI is transforming search, brand discovery, reputation management, and the role of marketing.
Summary: Brandi AI CEO and Co-Founder Leah Nurik answers questions about AI visibility strategy for brand discovery, Generative Engine Optimization (GEO), brand intelligence, and the future of marketing. Marketing, PR, and brand leaders face a shift from keyword-based search toward AI-generated answers that shape discovery, reputation, and buyer decisions. Nurik explains how brands can measure visibility, analyze sentiment, trace influential sources, and optimize human-created content for AI. The discussion draws on her June 13, 2026 Bald Ambition podcast appearance and Brandi AI’s patent-pending Sentiment Hub. Credible third-party validation, authentic storytelling, and measurable AI perception are becoming core drivers of brand growth.
Key Takeaways
- AI-generated answers are changing brand discovery by shifting search from keyword matching toward intent, context, and synthesized recommendations.
- AI answer engines like ChatGPT, Perplexity, and Claude require brands to manage how they are understood, described, compared, and cited in AI-generated answers.
- Third-party validation can influence AI visibility because brand perception is shaped beyond a company’s own website.
- AI visibility measurement should go beyond brand mentions.
- Human-created strategy and content remain essential in AI-mediated discovery.
On June 13, 2026, Leah Nurik, CEO and co-founder of Brandi AI, joined Mookie Spitz on the Bald Ambition podcast to discuss artificial intelligence (AI), Generative Engine Optimization (GEO), AI visibility, and the future of marketing.
The conversation focused on a fundamental shift in digital discovery: Search is moving beyond blue links and keyword matching toward AI-generated answers that synthesize information, interpret intent, and shape brand perception before a buyer reaches a company website.
Leah also discussed third-party validation, AI sentiment measurement, human-created content, reputation management, and the expanding role of marketing as a source of business intelligence.
The full episode can be viewed here.
The following Q&A has been edited for clarity and length.
How is AI changing the way consumers and B2B buyers discover brands across traditional search and AI-powered platforms such as ChatGPT and Perplexity?
Leah Nurik: We describe Brandi AI as a brand intelligence, GEO, and an AI visibility platform. Our technology helps companies measure, monitor, track, and optimize how their brands appear in AI search results across models such as ChatGPT, Perplexity, and Claude.
But traditional search is changing, too. Even when someone goes to Google or Bing, they increasingly receive a synthesized summary rather than simply a list of blue links.
The systems returning information have fundamentally changed, and that requires a new approach. Companies need to understand how their brands appear in those environments, identify where they are absent or misrepresented, take action, and measure the impact.
How does Generative Engine Optimization (GEO) differ from traditional Search Engine Optimization (SEO) as search shifts from keyword-based blue links to intent-driven AI-generated answers?
Leah Nurik: The algorithms have shifted toward intent.
Traditional search focused heavily on keyword matching: Does this keyword match this domain? The engine returned a blue link, and the researcher clicked through.
AI-generated answers create a very different experience because they synthesize context, explanation, and recommendations.
For marketers, that is incredibly exciting. My background is in marketing, PR, product marketing, and brand strategy. The nuanced work marketers have always done — defining a market, explaining differentiation, shaping a category, and building a compelling story — can now be reflected directly in the answer.
When done correctly, the consumer or B2B buyer can experience a brand’s story, differentiation, and market position before ever reaching the company’s website.
How can authentic brand strategy and third-party sources affect how AI systems describe and recommend companies?
Leah Nurik: I believe the companies that will win are the ones that are mission-driven and genuinely focused on delivering products and services that fulfill their brand promise.
This is not about tricking AI for a short-term gain. It is about long-term strategic messaging and brand consistency across the places where people encounter a company.
Companies need a coherent message, but it also has to be authentic, credible, and supported by third-party validation. The information feeding AI does not come only from a company’s own domain. It can come from media coverage, influencers, social networks, and many other external sources.
That creates an enormous opportunity for brand strategists and communications professionals. Building credible stories and meaningful reputations can now directly affect discovery, buyer perception, and growth.
How can AI visibility, brand perception, and sentiment data give marketing, PR, and brand teams more measurable indicators of business impact?
Leah Nurik: AI visibility is bringing new KPIs and measurement capabilities to parts of marketing that historically had fuzzy metrics.
You could walk into the CFO’s office and struggle to demonstrate the through line to return on investment. Now we have new ways to measure how brands appear, how they are positioned, and how that changes over time.
That creates evidence for work that was previously difficult to quantify. For marketers, that is enormously exciting, and it drives much of what we are doing at Brandi AI.
Why does you recommend human-generated content optimized for AI understanding instead of large-scale automated AI content production?
Leah Nurik: Humans are still the ones who buy. AI is not going to buy your product.
I strongly believe in human-generated content optimized for AI — not content written entirely by AI and published at scale.
Generative AI synthesizes what already exists. What makes a brand interesting is what is unique about it and how it connects emotionally with the people who may buy its products.
At Brandi AI, we use workflows to make humans more efficient, surface customer pain points, identify information gaps, flag misinformation, and make suggestions. But the process remains human-led.
Brands should not simply press a button and generate dozens of pieces of content to fill perceived AI visibility gaps. AI can provide insight and improve structure, but humans still need to make the strategic and creative decisions.
Build brand equity. Optimize with AI and for AI. But keep it human-generated.
Beyond basic brand mentions, what should companies measure to understand how they are positioned in AI-generated answers?
Leah Nurik: The first question is simple: Am I appearing?
But appearing is not enough. Companies also need to ask: How am I appearing? Is it good or bad? Is it right or wrong? How do I compare with competitors?
Suppose a company has defined five core brand pillars. It should be able to understand how its position against those pillars compares with competitors or adjacent brands.
At Brandi AI, we developed a patent-pending solution called Sentiment Hub. It allows companies to configure how they define their category, measure sentiment accordingly, and identify where those perceptions come from.
Is positive sentiment coming from media coverage? Company blogs? An influencer on Instagram or TikTok?
Once you know, you can decide where to double down. If something is wrong, you can identify where to address it.
What process should companies use to identify AI visibility gaps and improve brand perception over time?
Leah Nurik: I think about it as a loop: identify, analyze, act, and continue learning.
Measurement is table stakes. A company needs to know where it appears and where it is absent.
Then it needs to understand what that visibility means. Is the brand being positioned positively or negatively? Is the information accurate? How does it compare with competitors?
Then comes action. What should we put into the market? What do customers need? Is the website communicating clearly? Is a blog addressing the right issue? Is a contributed article useful? Is a press release structured appropriately?
Those are core brand intelligence questions in the age of AI.
How can AI visibility and sentiment insights inform operational decisions beyond marketing
Leah Nurik: Sentiment and competitive intelligence can inform actions outside marketing.
We have used Jeep as an example in a demo environment. Suppose the data shows negative sentiment around reliability or dealer service compared with other automotive brands in the SUV and off-road market.
That information could influence decisions in supply chain, dealer relations, or other operational areas.
AI-generated answers can become a research touchpoint because they reflect a version of market perception. A company can insist that its parts are reliable or its service is great, but if the market perception says otherwise, leadership needs to understand that reality and act.
Marketing can then communicate what changed and measure whether perception improves. That creates a through line between the business problem, the operational action, the communications strategy, changing sentiment, and outcomes such as customer retention or repeat purchases.
How can gaps in accurate public information cause misinformation or negative brand positioning in AI-generated answers?
Leah Nurik: If you do not provide a good answer, AI may fill in the gap.
A lot of misinformation can originate from a lack of available information.
We had a situation where a company was being positioned very negatively on pricing, even though the description did not reflect reality. The company had gated its pricing so extensively that AI systems had little reliable information available.
The company made a strategic decision to publish at least some pricing information so it would not continue to be positioned inaccurately.
That matters because buyers are conducting extensive research in AI environments. By the time they reach a website, ecommerce experience, or dealer, they may already be highly qualified.
That changes how we think about the funnel and the buyer journey.
How can companies trace negative AI sentiment to specific sources and improve inaccurate or harmful brand perceptions over time?
Leah Nurik: The first answer is fundamental: Do the right thing. Have genuinely good products and services.
But companies also need to know where negative sentiment comes from. Within Brandi AI, companies can examine sources influencing sentiment down to the domain and link level.
Once you identify the source, you may not always be able to remove or correct it. But you can address the underlying business problem, correct misinformation when possible, and develop credible storytelling supported by better evidence.
Even if a company is in a hole, that does not mean it will remain there forever. The important thing is understanding why the perception exists and then measuring how it changes after action is taken.
For brand marketing and communications, being able to demonstrate that progression is incredibly valuable.
Why can outdated information across the web continue influencing AI-generated answers after a company rebrands?
Leah Nurik: We had a customer that had completed around 10 acquisitions over several years and invested heavily in rebranding. Yet old brand names continued appearing and, in some segments, were outperforming the new brand.
By tracing the sources, the company discovered outdated information on partner pages and other sites across the web.
Those partners wanted the company to succeed, but old pages had never been updated. Once the sources were identified, the company could ask partners to correct them.
That is why visibility alone is not enough. Companies need to understand which information sources are shaping AI answers.
How does analyzing brand perception inside AI-generated answers differ from traditional social listening, media monitoring, and conventional sentiment analysis?
Leah Nurik: Historically, many market research and social listening projects have been elaborate, expensive, and slow. Companies could wait months for a massive presentation and still struggle to extract an actionable conclusion.
The opportunity now is to understand how a brand is semantically positioned across AI-generated answers and trace the sources influencing those perceptions.
If you can identify what is driving positive or negative perception, develop a strategy based on that intelligence, and measure how perception changes, you have something much more actionable.
Why does authentic brand strategy become more important as AI systems shift from keyword matching toward semantic understanding?
Leah Nurik: The shift is from keywords toward meaning.
All the work marketers have historically done around mission, differentiation, positioning, market definition, and emotional connection becomes highly relevant.
Brands should not abandon strategy and simply automate content production. They should build credible companies, develop differentiated stories, create authentic human content, and structure that information so AI systems can understand it.
AI is a tool. It can help companies listen, measure, analyze, and optimize. But the human work of defining what a brand stands for and creating real connections remains essential.
How does Brandi AI combine AI technology with communications and brand strategy expertise to support marketing teams?
Leah Nurik: We have embedded communications and brand strategy expertise into the platform.
We want the experience to support people across the organization — from an individual contributor monitoring analytics or writing blogs to the CMO of a Fortune 500 company.
The larger point is that AI should help people do better work. It should provide intelligence, improve efficiency, and create stronger connections.
But AI is still a tool. The human connection remains essential.
See How Your Brand Appears in AI-Generated Answers
AI visibility is now part of how buyers discover, compare, and evaluate companies.
Brandi AI helps marketing, PR, and brand teams measure where their companies appear across AI-generated answers, understand how they are positioned against competitors, trace the sources influencing sentiment, and identify opportunities to improve visibility and perception.