Keyword Search Is Stuck in the Past: How AI Forces Us to Rethink Keywords, Data Ownership, and Monetizationy

- Barry Boatner

Jason Bosarge and Barry Boatner, CEO of SkyRocket (source SkyRocket)

I believe we are standing at the same inflection point that shaped the modern internet two decades ago. Back then, no one quite knew how to monetize digital attention. Eventually, keywords and contextual advertising became the economic backbone of search. Today, artificial intelligence is dismantling that old framework. The index-based model that powered search for years is becoming obsolete, and the question every major platform is quietly wrestling with is simple: how does AI actually make money without exploiting users or flooding them with noise?

For most of the internet’s history, search engines have relied on a simple economic formula. Capture attention, monetize intent, and sell access to advertisers. That model generated extraordinary scale, but it also locked the ecosystem into an outdated structure that prioritizes sponsored placements over user experience. What once felt innovative now feels cluttered, slow, and increasingly disconnected from how people actually want to interact with information.

My late business partner, Jason Bosarge, the original inventor of contextual advertising, helped lay the foundation for the monetization layer that still powers much of today’s internet. His work demonstrated how keywords could translate human intent into economic value, transforming search into one of the most profitable business models ever created. But even the most successful systems eventually reach their limits. The same architecture that fueled early growth is now constraining the next phase of technological evolution.

What troubles me most is not just inefficiency, but imbalance. The modern internet runs on user behavior. Every query, every click, every scroll generates value that is packaged and sold to advertisers. According to reports, global digital advertising spending is expected to reach $1.25 trillion in 2026, underscoring just how much economic power flows from user activity into centralized platforms. Yet the people creating that value, everyday users, receive none of it. We have normalized a system where personal data fuels massive profits, while individuals are treated as raw material rather than stakeholders.

At the same time, global data creation is projected to reach roughly 230 to 240 zettabytes by 2026, a scale so vast that it stretches the limits of everyday comprehension. This explosion of information should represent an opportunity, but instead it has produced overload, privacy erosion, and diminishing trust. AI only accelerates this dynamic. Without new economic structures, the next generation of intelligent systems risks inheriting the same flawed incentives that defined the last one.

I believe the answer lies in rethinking what a keyword actually represents. Words are not just search inputs; they are expressions of intent. They signal needs, interests, and decisions in motion. What we need is to transition from a surveillance economy to an intent economy. If intent drives economic value, then ownership of intent should not belong exclusively to platforms. We should be exploring models where language itself becomes a digital asset that individuals and businesses can own, trade, and benefit from.

In the work my team and I have been developing at SkyRocket, we have begun experimenting with tokenized keywords, essentially turning words into blockchain-based assets. The concept is simple in theory but transformative in practice. Instead of bidding endlessly for placement inside obscure ad systems, individuals and companies can directly acquire ownership rights to specific keywords or phrases. When someone searches for that term, the owner receives priority placement, and built-in royalty mechanisms distribute value across the ecosystem.

This is not about replacing organic content or hiding information behind paywalls. In fact, it does the opposite. The primary result surfaces first, while surrounding content remains visible and accessible. What changes is who benefits from that visibility. Instead of centralized platforms capturing nearly all economic upside, value flows to the participants who invest in and maintain these digital assets.

Critics often ask whether this simply recreates advertising in another form. I would argue it represents a shift from advertising to what I call “offertizing.” Rather than bombarding users with irrelevant promotions, intelligent systems can proactively match people with offers that align with their actual interests. When AI understands preferences, with privacy controls that put users in charge, it can negotiate on behalf of individuals, bringing relevant options directly to them. The website becomes the destination, not the advertisement itself.

This approach also aligns with how younger generations interact with information. Visual discovery, instant answers, and social sharing are already redefining engagement. Search is no longer about typing a query and scrolling endlessly. It is about speed, clarity, and action. That is why we have focused on five pillars that reflect real human behavior: instant answers, intelligent agents, proactive feeds, privacy-first personalization, and inherently social interaction. Together, they form a framework where information flows naturally into outcomes.

Mobile will play a decisive role in this transition. As AI becomes embedded directly into mobile interfaces, search will move from reactive behavior to proactive assistance. Instead of hunting for information, people will receive curated insights, automated task execution, and real-time recommendations tailored to their needs. This is where the next generation of search will live, not in static result pages, but in dynamic, adaptive experiences.

Perhaps the most important implication of all is what this means for AI monetization. Large language models are extraordinarily powerful, yet many struggle to establish sustainable revenue streams without reverting to traditional ad models. Tokenized keyword systems offer a new layer of economic infrastructure. Through standardized APIs, AI platforms can integrate language-based assets and create transparent, scalable monetization without compromising user trust.

We are not talking about incremental improvement. We are talking about restructuring the foundation of the digital economy. Just as domain names once introduced ownership to the web, language assets can introduce ownership to intent itself. The opportunity is not simply financial; it is cultural. It redefines who controls value creation online.

Search is no longer about finding links. It is about understanding intent, respecting users, and building economic systems that reward participation rather than exploitation. If we want AI to serve people instead of mining them, we must redesign the rules of engagement now. The future of search depends on it.

About the Author:

Barry Boatner is the founder and CEO of SkyRocket, a technology company focused on reimagining how search, artificial intelligence, and digital monetization intersect. With decades of experience in digital infrastructure and platform development, Boatner has worked at the intersection of emerging technology, data economics, and user-centered design, advocating for new models that prioritize transparency, ownership, and sustainable innovation.