The way customers discover businesses is undergoing its biggest shift since the smartphone era began. Traditional search engines that display a list of blue links are rapidly being replaced by AI-powered recommendation systems that synthesize information and deliver a single, definitive answer. For brands accustomed to competing for rankings on Google, this transformation presents both a crisis and an opportunity.

What Is Generative Engine Optimization, and Why Should Brands Care?

Generative Engine Optimization, or GEO, is the emerging practice of optimizing how brands appear in AI-generated responses across platforms like ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Unlike traditional search engine optimization (SEO), which focuses on ranking for keywords, GEO is about whether an AI system mentions your brand, cites your website as a source, and recommends you to users asking relevant questions.

The stakes are significant. With Apple's integration of Google's Gemini into Siri, iPhone users now have a generative agent in their pocket that doesn't want to give them a list of websites; it wants to provide a single, authoritative answer. This shift toward what experts call "Zero-Click Commerce" means customers may never visit your website at all. Instead, the AI books the appointment, compares your services to competitors, and makes the recommendation without the user ever seeing a search results page.

Pepper, a San Francisco-based company, has launched a platform designed to address this visibility gap. Built through work with over 250 enterprises, Pepper's GEO platform analyzes more than 10 million prompts across major generative search engines to show where brands appear in AI-generated answers, why competitors win, and what actions to take next.

How Does AI Decide Which Brands to Recommend?

The algorithm behind AI recommendations is fundamentally different from traditional search ranking. AI models evaluate authority through a broader lens than keyword density or backlinks. They look for expertise signals across multiple sources, including professional profiles, industry publications, expert commentary, and recognized credentials. Consistency and credibility have become just as important as visibility itself.

Kevin Williams, founder of Park City-based Ascend AI Labs, describes a phenomenon he calls the "Snap-To." Because AI models are designed to make users happy and avoid doubt, they want to provide the best possible recommendation to keep the user in the app. "If your data is incomplete or your reputation is messy, the AI won't 'snap' to you. It will move to the next business where it has the highest correlation of trust," Williams explained. Once the AI decides a competitor is the winner, it becomes a self-reinforcing cycle that is very hard for others to break.

"The LLM wants to get the best answer to the person as fast as it possibly can. If your data is incomplete or your reputation is messy, the AI won't 'snap' to you. It will move to the next business where it has the highest correlation of trust," said Kevin Williams, founder of Ascend AI Labs.

Kevin Williams, Founder of Ascend AI Labs

AI models are now scraping Reddit, local forums, Google Maps reviews, and earned media mentions to find what experts call "sentiment" signals. If your customers are evangelizing you online, the AI sees that as a high-trust indicator. This means that authenticity and genuine customer relationships have become competitive advantages that large corporations struggle to replicate.

What Metrics Matter Most in AI Search Visibility?

Pepper's platform evaluates three primary dimensions of AI search visibility. The first is whether an AI model mentions the brand in response to a relevant query. The second is whether the model cites the brand's owned website as a source. The third is whether the brand appears consistently across multiple engines, prompt variations, and buyer contexts. These signals help enterprises distinguish between isolated visibility and sustained presence across generative search.

The platform includes several core areas of analysis:

• Brand Visibility: Measures how often a brand is mentioned in AI-generated responses across relevant buyer prompts and search engines.
• Domain Coverage: Tracks how often the brand's owned pages appear as cited sources in AI responses, rather than competitor or third-party websites.
• Competitive Positioning: Identifies which third-party websites, competitor pages, and review platforms are being cited by AI engines, showing which sources shape how your brand is represented.
• Buyer Journey Mapping: Organizes queries by persona, topic, and stage of the buyer journey to identify which conversations the brand is winning and where competitors are more visible.
• Optimization Recommendations: Translates findings into a ranked set of recommended actions, with each metric traceable back to the underlying AI-generated response.

One real-world example demonstrates the power of these metrics. Awardco, a Lindon-based employee recognition platform, saw its AI visibility skyrocket almost overnight. When tracking began across 150 AI-related prompts, the company appeared in just 14% of them, well behind competitors. The catalyst for change wasn't a technical tweak to the company's website; it was a major public relations breakthrough surrounding its billion-dollar valuation. The day after that news broke and high-authority publications picked it up, the AI started referencing those articles immediately. Within months, Awardco's AI visibility climbed from 14% to 46%.

How Should Legal Firms and Other Professionals Adapt to AI Search?

The legal industry offers a particularly instructive case study. For years, law firms have focused on operational efficiency, adopting AI for contract analysis, legal research, and document review. But a quieter transformation is beginning to emerge. As search behavior evolves, people are increasingly turning to AI platforms to find answers before they visit a website or speak to a lawyer. Instead of comparing multiple search results, users receive direct recommendations and explanations generated by AI systems.

Unlike many industries, law firms already produce the type of content AI systems value. Legal websites contain explanations, FAQs, case commentary, regulatory analysis, and educational resources. This information is inherently knowledge-driven and aligns closely with how AI engines generate responses. However, simply publishing content is no longer enough.

Educational content, expert analysis, research-backed insights, and commentary on emerging legal developments are becoming critical visibility assets. Data privacy lawyers can analyze evolving AI legislation. Employment law experts can interpret regulatory changes affecting workplaces. Corporate lawyers can publish practical guidance for startups and investors. Technology law specialists can explain compliance challenges created by new digital technologies. The objective is not to promote services; it is to become a trusted source of information.

Steps to Improve Your Brand's Visibility in AI Search

• Audit Your Transaction Friction: If you operate a transactional business like a dentist, dry cleaner, or restaurant, assess whether an AI agent can "handshake" with your booking system. If there is too much friction, the AI will recommend the competitor who makes booking easier.
• Measure Your LLM Presence: Use tools like Google Analytics to track how much referral traffic is coming from ChatGPT, Perplexity, or Gemini. Even if it is only 1%, remember this is the "research layer" where your future customers are making up their minds.
• Become a Verified Entity: Stop chasing keywords and start chasing authority. Earned media, local community engagement, and responding to every single review, positive or negative, are no longer just "nice-to-haves." They are the data points AI uses to decide if you are the best answer.
• Invest in Expertise-Led Content: Focus on publishing authoritative and useful content that educates your market rather than traditional promotional messaging. Build recognizable expert profiles around your leaders and increase visibility across trusted third-party publications and industry platforms.

Tyler Brown, head of SEO at the Lehi-based agency Big Leap, argues that GEO is actually an invitation for brands to find their soul again. "AI has done a really good job at finding brands that have a personality, brands that are genuine," Brown stated. "We tell our clients: you can't just do a technical audit and optimize a website anymore. You have to ask: Who are you? Why should people care? People notice different, align to genuine and evangelize delight".

"PR and SEO have merged. To be found in 2026, you have to be a 'verified entity' that the AI trusts," said Tyler Brown, head of SEO at Big Leap.

Tyler Brown, Head of SEO at Big Leap

Can Small Businesses Compete in the AI Search Era?

In a world dominated by data-heavy giants like Expedia or Amazon, the question of whether a local Utah shop or small business can compete in AI search is urgent. Williams is cautiously optimistic, but warns that the "little guy" has to lean into what the giants cannot: sentiment and authenticity. "Expedia can't really be authentic; it is too big," Williams noted. "But a local business has the ability to add an opinion and a community connection. AI models are now scraping Reddit, local forums and every single Google Map review to find 'sentiment.' If your customers are evangelizing you online, the AI sees that as a high-trust signal".

Brown goes a step further. He has watched AI search begin to expose the operational weaknesses of large, privately funded companies that cannot adapt quickly and surface the smaller businesses that simply do good work. "It is almost leveled the playing field," Brown observed. "It is a bit of a Cinderella story for the locally owned businesses that always did it right but never had the marketing budget to compete".

The shift toward AI-powered discovery is still in its early stages, but the implications are becoming clear. As AI continues to reshape how people seek information and make decisions, visibility will be influenced not only by rankings but by recommendations. The brands that invest today in expertise, authority, and trust will be better positioned for a future where discovery happens through conversations rather than clicks.