The landscape of online search is undergoing a profound transformation, one that could redefine how businesses connect with consumers in the digital age. According to a recent report by Gartner, traditional search engine volume is projected to decline by 25% by 2026, primarily due to the rapid rise of AI chatbots such as ChatGPT, Claude, and Perplexity. This shift marks a significant departure from the established norms of search engine optimization (SEO), prompting the emergence of new strategies designed to navigate this evolving terrain.
At the forefront of this change is Geostar, a startup backed by Pear VC, which is pioneering a new approach known as Generative Engine Optimization (GEO). Unlike traditional SEO, which has historically focused on optimizing content for keywords and backlinks, GEO emphasizes understanding how large language models interpret, synthesize, and recommend information across the web. This paradigm shift is not merely a trend; it represents a fundamental rethinking of how businesses can enhance their visibility in an increasingly AI-driven world.
Mack McConnell, co-founder of Geostar, recounts a pivotal moment that crystallized his understanding of this shift. During the Paris Olympics last summer, he observed that both of his parents, independently and without any prompting, turned to ChatGPT to plan their daily activities in the city. The AI provided tailored recommendations for tour companies, restaurants, and attractions—essentially conducting what McConnell describes as a “visibility lottery” for those businesses. This experience underscored the intuitive nature of AI interfaces, which have become accessible to users of all ages, and highlighted the need for businesses to adapt to this new reality.
Geostar’s mission is to help businesses navigate what may be the most significant shift in online discovery since the founding of Google. The company recently emerged from stealth mode, boasting impressive early customer traction and rapidly approaching $1 million in annual recurring revenue within just four months of operation. With only two founders and no employees, Geostar is already recognized as the fastest-growing company in PearX’s latest cohort.
The implications of this shift are profound. As AI chatbots gain traction, businesses must now optimize for multiple AI interfaces, including Google’s AI Overviews, Gemini, and various other platforms like ChatGPT and Claude. Each of these systems operates under different criteria, creating a fragmented landscape that poses challenges for companies that have spent years perfecting their Google search strategies. A recent study by Forrester revealed that 95% of B2B buyers plan to incorporate generative AI into their future purchasing decisions, yet many companies remain ill-prepared for this transition.
Cihan Tas, Geostar’s co-founder and chief technology officer, emphasizes the urgency of adapting to this new environment. He notes that some lawyers are now acquiring up to 50% of their clients through ChatGPT, illustrating the massive shift in how potential customers discover services. This trend underscores the necessity for businesses to embrace AI-driven strategies or risk falling behind.
Generative Engine Optimization represents a fundamental departure from traditional SEO practices. While SEO has historically centered on keywords and backlinks, GEO requires a nuanced understanding of how large language models parse and synthesize information. The technical challenges are formidable; every website must function as its own “little database,” capable of being understood by various AI crawlers, each with unique requirements and preferences. For instance, Google’s systems rely on their existing search index, while ChatGPT heavily utilizes structured data and specific content formats. Perplexity, another AI model, shows a marked preference for authoritative sources like Wikipedia.
In this new landscape, the strategy for success involves being concise, clear, and directly answering user queries—attributes that align with how AI systems seek information. Tas explains that businesses must tune their content to meet the expectations of intelligent models that make decisions similarly to human beings. This shift necessitates a reevaluation of traditional metrics of success, as businesses must now consider how prominently and positively they appear within AI-generated responses, even if users never click through to their websites.
One critical aspect of this new optimization strategy is schema markup, a form of structured data that helps machines understand web content. Despite its importance, only about 30% of websites currently implement comprehensive schema. Research indicates that pages with proper markup are 36% more likely to appear in AI-generated summaries, yet many businesses remain unaware of schema markup’s significance or how to implement it effectively.
Geostar’s innovative solution embodies a broader trend in enterprise software: the rise of autonomous AI agents capable of taking action on behalf of businesses. The company embeds what it calls “ambient agents” directly into client websites, continuously optimizing content, technical configurations, and even creating new pages based on patterns learned across its entire customer base. This approach allows Geostar to syndicate successful changes across its network, ensuring that all users benefit from collective insights.
For example, Geostar’s collaboration with RedSift, a cybersecurity firm, resulted in a remarkable 27% increase in AI mentions within just three months. In one instance, Geostar identified an opportunity to rank for the high-value search term “best DMARC vendors” in the email security space. The company’s agents created and optimized content that achieved first-page rankings on both Google and ChatGPT within a mere four days. McConnell highlights that Geostar is effectively performing the work of an agency that typically charges $10,000 a month, while offering its services at a fraction of that cost—ranging from $1,000 to $3,000 monthly.
The implications of this shift extend beyond technical optimizations. In the era of traditional SEO, a brand mention without a hyperlink was often deemed worthless. However, in the age of AI, this calculus has reversed. AI systems can analyze vast amounts of text to discern sentiment and context, meaning that brand mentions on platforms like Reddit, news articles, or social media now directly influence how AI systems describe and recommend companies. McConnell explains that if a reputable source like The New York Times mentions a company without linking to it, that company can still benefit from the mention in an AI system. This ability to conduct mass analysis of text allows AI to understand the sentiment surrounding a brand, creating new opportunities and vulnerabilities.
Research from the Indian Institute of Technology and Princeton University has revealed that AI systems exhibit systematic bias toward third-party sources over brand-owned content. Consequently, a company’s own website may hold less sway in shaping AI perceptions than external commentary. This shift has disrupted traditional success metrics, as businesses must now account for what researchers refer to as “impression metrics”—how prominently and positively a brand appears within AI-generated responses, regardless of whether users click through to the source.
As the SEO industry, valued at approximately $80 billion globally, scrambles to adapt to this new reality, Geostar is not alone in recognizing the opportunity presented by AI optimization. Startups like Brandlight, Profound, and Goodie are entering the fray, while established players such as Semrush and Ahrefs rush to integrate AI visibility tracking features into their offerings. However, Geostar’s founders believe their technical approach gives them a competitive edge. Unlike competitors that primarily provide dashboards and recommendations, Geostar’s agents actively implement changes, allowing businesses to leverage AI’s capabilities fully.
The stakes are particularly high for small and medium-sized enterprises (SMEs). While larger corporations can afford to hire specialized consultants or build internal expertise, smaller businesses risk becoming invisible in an AI-mediated search landscape. Geostar identifies this as a primary market opportunity, noting that nearly half of the 33.2 million small businesses in America invest in SEO. Among the approximately 418,000 law firms in the U.S., many allocate between $2,500 and $5,000 monthly on search optimization to maintain competitiveness in local markets.
The journey of Geostar’s co-founders is also noteworthy. Cihan Tas, whose path to Silicon Valley began in a tiny Kurdish village in Turkey with just 50 residents, views the current moment as both an opportunity and a responsibility. His mother’s battle with cancer prevented him from completing college, leading him to teach himself programming and eventually partner with McConnell—whom he worked with for an entire year before they met in person. Tas emphasizes that Geostar is not merely replicating existing solutions but is instead creating something uniquely possible in today’s technological landscape.
Looking ahead, the transformation of search functionality appears to be accelerating rather than stabilizing. Industry observers predict that search capabilities will soon be embedded in productivity tools, wearables, and even augmented reality interfaces. Each new platform will likely introduce its own optimization requirements, further complicating the landscape for businesses seeking visibility.
McConnell envisions a future where search will be seamlessly integrated into our daily lives, stating, “Soon, search will be in our eyes, in our ears.” He anticipates that when Siri breaks free from her current limitations, the collaboration between Jony Ive and OpenAI will yield a multimodal search interface that fundamentally alters how we interact with information.
However, the technical challenges posed by this evolution are matched by ethical considerations. As businesses scramble to influence AI recommendations, questions arise regarding manipulation, fairness, and transparency. Currently, there is no oversight body or established best practices for GEO, leading some critics to describe the environment as a “Wild West.”
As businesses grapple with these changes, one thing is clear: the era of simply optimizing for Google is over. In its place is a complex ecosystem where success hinges on understanding not only how machines index information but also how they think, synthesize, and ultimately decide what to recommend to users seeking answers.
For the millions of businesses whose survival depends on being discovered online, mastering this new paradigm is not just an opportunity; it is an existential imperative. The question is no longer whether to optimize for AI search but whether companies can adapt quickly enough to remain visible as the pace of change accelerates.
The experience of McConnell’s parents at the Olympics serves as a harbinger of what is becoming the norm. They did not search for tour companies in Paris, scroll through results, or click on links. Instead, they simply asked ChatGPT what to do, and the AI determined which businesses deserved their attention. In this new economy of discovery, the businesses that succeed will not necessarily