Last summer at the Paris Olympics, Mack McConnell experienced firsthand a profound transformation in how people discover information online. Without any guidance, both of his parents independently relied on AI-powered tools to plan their day in the French capital. The AI suggested specific tour operators, dining spots, and attractions-businesses that had suddenly gained unprecedented visibility through this emerging technology.
“It felt like an intuitive interface that older generations could navigate as effortlessly as younger ones,” McConnell shared in an exclusive conversation. “I could clearly see how these businesses were being surfaced in a completely new way.”
This insight laid the groundwork for Geostar, a startup backed by Pear VC, which is rapidly developing solutions to help companies adapt to what may be the most transformative shift in online search since Google’s inception.
Revolutionizing Online Discovery: The Rise of AI-Driven Search
Having recently come out of stealth mode with strong early adoption, Geostar is capitalizing on the explosive growth of AI-powered search technologies. Market forecasts predict that the AI search sector will expand from $43.63 billion in 2025 to an astonishing $108.88 billion by 2032, underscoring the massive opportunity for businesses to reinvent their online presence.
Despite being a lean operation with just two founders and no additional staff, Geostar is already the fastest-growing company in its niche, approaching $1 million in annual recurring revenue within only four months.
Why Traditional Search Traffic Is Set to Decline Sharply
Industry analysts at Gartner forecast a 25% drop in conventional search engine traffic by 2026, primarily driven by the surge in AI chatbot usage. For example, Google’s AI Overviews now appear in over 20% of monthly searches, reshaping how users interact with search results. Research from Princeton University highlights that optimizing for these AI-driven interfaces can significantly boost a business’s online visibility.
“Previously, SEO meant tailoring content to please Google’s algorithms,” McConnell explained. “Now, businesses must optimize for multiple Google interfaces-traditional search, AI Mode, Gemini, and AI Overviews-each with distinct ranking factors. On top of that, AI platforms like ChatGPT, Claude, and Perplexity operate with their own unique mechanisms.”
This fragmentation has thrown a wrench into decades of established SEO strategies. A recent survey revealed that 95% of B2B buyers intend to incorporate generative AI into their purchasing decisions, yet most companies remain ill-equipped to navigate this new terrain.
“Companies not adapting now are falling behind,” said Cihan Tas, Geostar’s co-founder and CTO. “For instance, some law firms are acquiring half their clients through ChatGPT. This is a seismic shift in how business is done.”
Understanding How AI Language Models Interpret the Web
Geostar and other innovators refer to this emerging discipline as Generative Engine Optimization (GEO), marking a fundamental departure from traditional SEO. While classic SEO emphasized keywords and backlinks, GEO demands a deep understanding of how large language models (LLMs) analyze, interpret, and synthesize web content.
The technical hurdles are significant. Each website must effectively serve as a mini-database, comprehensible to a variety of AI crawlers, each with distinct preferences. For example, Google’s AI draws from its existing search index, while ChatGPT relies heavily on structured data and specific content formats. Perplexity, meanwhile, favors authoritative sources like Wikipedia.
“The new strategy is about clarity and precision-directly answering user queries,” Tas noted. “You’re essentially optimizing for an intelligent system that makes decisions much like a human would.”
Take schema markup, a form of structured data that helps AI better understand website content. Although only about 30% of websites currently use comprehensive schema, studies show that pages with proper markup are 36% more likely to be featured in AI-generated summaries. Yet, many businesses remain unaware of schema markup or how to implement it effectively.
Geostar’s Autonomous AI Agents: Continuous Website Optimization
Geostar exemplifies a growing trend in enterprise software: autonomous AI agents that actively manage and optimize digital assets. The company integrates these AI agents directly into client websites, enabling ongoing improvements to content, technical settings, and even the creation of new pages based on insights gleaned from its entire user base.
“When we discover effective content strategies or technical tweaks, we propagate those improvements across all clients, so everyone benefits,” McConnell explained.
For example, a cybersecurity firm using Geostar’s platform saw a 27% increase in AI-related mentions within just three months. In one case, Geostar’s AI identified a lucrative keyword opportunity-“best DMARC vendors”-and swiftly generated optimized content that ranked on the first page of both Google and ChatGPT within four days.
“We deliver agency-level results that typically cost $10,000 per month, but our pricing ranges from $1,000 to $3,000 monthly,” McConnell said. “AI enables businesses to scale optimization efforts like never before.”
The Growing Importance of Brand Mentions Without Links in AI Search
The shift to AI-driven search has also transformed the value of brand mentions. In the traditional SEO world, unlinked mentions were largely ignored. Today, AI systems analyze vast amounts of text to gauge sentiment and context, meaning that brand mentions on platforms like Reddit, news outlets, and social media can significantly influence AI recommendations.
“Even if a major publication like The New York Times mentions a company without linking to it, that mention can positively impact AI-driven search results,” McConnell said. “AI’s ability to process massive text corpora allows it to understand the sentiment behind these mentions.”
However, this also introduces new risks. Research from the Indian Institute of Technology and Princeton University indicates that AI systems often prioritize third-party sources over a company’s own website, making external reputation more influential than ever.
Consequently, traditional SEO metrics like rankings and click-through rates are giving way to new measures focused on impression metrics-how prominently and favorably a brand appears in AI-generated responses, even if users don’t click through.
Market Dynamics: Veteran SEO Firms and New Entrants Compete for AI Optimization
Geostar is part of a burgeoning ecosystem of companies racing to help businesses master AI search optimization. Established SEO giants like Semrush and Ahrefs are rapidly integrating AI visibility tracking, while startups are innovating with autonomous optimization tools.
Having previously founded and sold a Y-Combinator-backed e-commerce optimization startup, Geostar’s founders believe their hands-on AI implementation approach sets them apart. Unlike competitors who mainly offer dashboards and recommendations, Geostar’s AI agents actively execute optimizations.
“Many are simply repurposing old SEO tactics for AI,” McConnell argued. “But AI’s true power lies in its ability to do the work for you.”
This evolution is especially critical for small and medium-sized enterprises (SMEs). While large corporations can afford specialized teams, smaller businesses risk fading into obscurity in AI-mediated search. Nearly half of the 33.2 million small businesses in the U.S. invest in SEO, and among the 418,000 American law firms, many spend thousands monthly to maintain local search competitiveness.
From Humble Beginnings to Pioneering the Future of Search
For Cihan Tas, Geostar’s CTO, the journey from a small Kurdish village in Turkey to Silicon Valley embodies both opportunity and responsibility. After his mother’s illness interrupted his college education, he taught himself programming and eventually partnered with McConnell-whom he collaborated with remotely for a year before meeting in person.
“We’re not just tweaking old solutions,” Tas emphasized. “This is a fundamentally new approach made possible by today’s technology.”
Looking ahead, the evolution of search is accelerating. Experts predict that search capabilities will soon be integrated into productivity software, wearable devices, and augmented reality platforms-each demanding unique optimization strategies.
“Search will soon be embedded in our vision and hearing,” McConnell predicted. “When virtual assistants like Siri evolve, combined with innovations from leaders like Jony Ive and OpenAI, we’ll see truly multimodal search experiences.”
Alongside technical challenges, ethical concerns loom large. As companies vie to influence AI recommendations, issues of fairness, transparency, and manipulation arise. Currently, no regulatory framework governs GEO, creating a “Wild West” environment.
One thing is clear: the era of optimizing solely for Google is ending. Success now requires mastering how AI systems interpret, synthesize, and prioritize information to recommend businesses to users.
For millions of companies dependent on online discovery, adapting to this new paradigm is not optional-it’s vital for survival. The question is no longer whether to optimize for AI search, but whether businesses can evolve quickly enough to stay visible amid rapid change.
McConnell’s parents’ experience at the Olympics was a glimpse of the future: they didn’t sift through search results or click links-they simply asked ChatGPT for recommendations, and the AI determined which businesses earned their attention.
In this emerging landscape, the winners won’t be those with the highest rankings-they’ll be the ones AI chooses to spotlight.
