AI is changing everything in search, except what matters most
Imagine searching the web twenty years ago. You typed a few keywords, and Google gave you a neat list of blue links. You clicked, scrolled, skimmed, and eventually found your answer—or didn’t. Today, the experience feels different. You ask ChatGPT or Google's AI-enhanced search a question, and it delivers a neatly summarized, conversational answer. It feels revolutionary, intuitive, even magical. But beneath this shiny new surface, something foundational hasn't changed.
At its heart, the core problem of web search is still exactly what it was in 1998: figuring out what information is trustworthy. And that’s still done primarily through an old trick—PageRank.
The Heart of Web Search: Authority
When Larry Page and Sergey Brin invented PageRank, their insight was both simple and profound: Links are votes. The more reputable the linking website, the more valuable the vote. This effectively crowdsourced a judgment about which pages mattered most. Rather than merely counting keywords, PageRank leveraged the entire internet’s implicit knowledge about authority.
That fundamental challenge—deciding who to trust—is still the core problem of search. It doesn't matter how flashy the AI interface becomes; beneath the surface, trustworthiness and relevance are still judged largely by this same mechanism.
Why? Because authority isn't easily measurable without some external cue. PageRank cleverly leveraged what millions of website creators implicitly knew: Good sources link to good sources. AI hasn’t solved the fundamental challenge of deciding trust without those human signals.
AI Summaries Are Built on Old Foundations
ChatGPT, Google’s Bard, and other AI assistants seem revolutionary. You ask a detailed question, and instead of blue links, you get a clean, authoritative-sounding paragraph. But peel back a layer, and you see these AIs aren’t independently evaluating every webpage on the internet—they still rely heavily on existing search results to form their answers.
These AI systems synthesize and repackage information sourced from webpages ranked by Google's traditional algorithms. If the underlying ranking is flawed, AI-generated responses amplify those flaws. If it’s robust, the AI appears intelligent. In other words, AI hasn't fundamentally disrupted web search—it has put a conversational, polished face on the old infrastructure.
The Quiet Dominance of PageRank
Despite impressive leaps in machine learning, nothing has yet displaced PageRank's underlying logic. That's because authority, as a concept, is stubbornly resistant to technical solutions. Determining trust is inherently a human-like judgment. Algorithms can approximate it, but not easily replace the fundamental wisdom embedded in link-based authority.
AI models are great at language, summarization, and reasoning, but they’re still relatively naive at evaluating factual accuracy or credibility without reference points provided by human judgment. As smart as ChatGPT seems, its strength currently lies in repackaging trusted information, not independently discovering new authoritative sources.
The Traffic Shift: AI Changes Everything but Ranking
Yet, while the fundamentals remain intact, the way users interact with search results is shifting dramatically. AI search interfaces—where an immediate, concise answer is served up—significantly reduce the incentive to click on individual links. Publishers who once relied on search traffic find fewer visitors reaching their sites.
This traffic shift has profound implications for businesses, advertising, and even how we build websites. But don’t mistake this surface-level disruption for a deeper change. AI hasn’t overturned the web’s underlying architecture; it’s just shifting the way we interact with it.
Imagining a World Beyond PageRank
Could AI ever truly replace PageRank? Imagine a "DeepRank," a hypothetical future AI model sophisticated enough to independently evaluate and rank webpages by deeply understanding their content, not just their incoming links. Such a model could identify genuinely expert sources without relying solely on external signals. But getting there is hard.
Today's AI, while impressive, regularly struggles with nuance, context, and—critically—factual accuracy. The complexity of trust goes beyond checking claims; it involves reputation, timeliness, and community consensus. Fully AI-driven authority evaluation must surpass simple comprehension—it must develop nuanced judgment.
Google is undoubtedly experimenting with such approaches, but thus far, no credible alternative to PageRank has emerged at scale. Trust remains stubbornly human.
New Interface, Same Game
Yes, AI has changed how we interact with search—but not the fundamental principles underneath it. The core challenge of web search is still what it was twenty years ago: judging what’s trustworthy.
PageRank, for all its simplicity, remains central to solving this problem. As entrepreneurs, investors, and creators, we’d do well to recognize that beneath AI’s shiny new interface, the rules remain largely unchanged. Authority is still king. Until AI genuinely cracks the code of measuring trust in a fundamentally new way, expect evolution, not revolution, in search.
The game hasn’t changed—at least not yet.