Vincentas Grinius is a tech entrepreneur and cofounder of IPXO, with a focus on internet infrastructure and sustainable digital innovation.

In the early 2010s, online growth mainly relied on media buying discipline. Banner placements, impression counts, click-through rates and conversion metrics were not just abstract marketing ideas but practical tools. Companies that knew how to attract attention effectively and convert it into results could grow confidently. The internet favored those who mastered distribution.

That model worked because the web was fundamentally page-centric. Content resided on websites, and monetization depended on attracting human readers to specific digital locations where ads could be displayed. Traffic was the main currency, and impressions were the unit of exchange.

When Content Detached From The Page

That logic is now breaking down at a structural level. Content consumption is detached from the website itself, as users rely on AI-driven systems to aggregate, summarize and contextualize information without visiting the original source. Instead of researching across multiple tabs, readers ask an AI system to do the work for them. Given the choice between hours of manual research and a digital assistant available for a modest monthly fee, this shift in behavior is rational.

The consequence is a direct break in the impression-based business model. If an AI system extracts the relevant insights from an article and delivers them directly to the user, the banner ad embedded on the original page becomes economically irrelevant. While the page may technically be accessed by a crawler, the human attention advertisers pay for is no longer present. As this behavior becomes mainstream, large portions of the web are turning into ghost inventory, active in analytics dashboards but detached from real commercial impact.

The numbers are already telling the story. “The proportion of news searches in Google where people didn’t click on a single link rose from 56 percent to nearly 69” in the year following the May 2024 launch of AI Overviews. Meanwhile, CNN’s website traffic dropped roughly 30% year-on-year, and both Business Insider and HuffPost saw declines of around 40% over the same period. According to The Digital Bloom, “the median publisher experienced a 10% year-over-year traffic decline in the first half of 2025, with … non-news content sites down 14%.” The impression counts in the analytics dashboards haven’t disappeared, but the humans behind them have.

Why Content And Authors Regain Value

What’s paradoxical is that this collapse in traffic hasn’t diminished the value of content—it has enhanced it. As distribution becomes automated and mediated by machines, economic value shifts from the container back toward the substance itself. Credibility, originality and usefulness become more important than layout, traffic volume or page design.

This marks a reversal of the past two decades. Platforms and distribution channels captured most of the value, while creators focused on reach and frequency. In an AI-mediated environment, what truly matters is whether content is worth consuming, referencing and trusting. The author becomes the key asset rather than the website hosting the work.

This change is already affecting monetization models. Instead of selling ad space, publishers and creators are starting to sell access, licensing rights and structured data feeds. The transaction shifts from hoping a reader notices a banner to ensuring that trusted information can be legally and reliably used by downstream systems. Attribution and usage become more significant than impressions and clicks.

The deals are already being signed. The Associated Press, News Corp and the Financial Times have each struck licensing agreements with AI developers, trading structured access to their archives for recurring revenue that has no dependency on human page visits. Reddit restructured its data licensing terms specifically to capture value from AI training pipelines. These are not experimental arrangements; they are early signals of what a post-impression revenue model looks like in practice.

What Past Crashes Tell Us About What Comes Next

The dot-com crash is instructive here. Pets.com burned through hundreds of millions of dollars chasing traffic and brand impressions. Amazon, which survived by focusing relentlessly on transaction utility rather than attention, went on to define the next era. Each major correction tends to eliminate inefficiencies and shift value toward more essential capabilities.

The parallel is not exact, but the direction is similar. Businesses whose economics depend primarily on aggregating attention may find that model under increasing pressure, while those that provide trusted information, unique expertise or embedded utility are likely to define what comes next.​

The impression economy is ending not because content has lost importance but because the way we monetize attention no longer matches how information is consumed. For executives, investors and publishers, metrics designed for a page-based web will mislead. Traffic numbers and impression counts will matter less than influence, trust and reuse.

Having run Host1Plus in that era, the discipline was simple: Buy attention efficiently, convert it reliably and optimize the funnel. That playbook made sense when the web rewarded it. What’s changing now is not the need for discipline—it’s the entire surface on which that discipline operates. ​​

The companies and creators who succeed will not be those chasing shrinking ad budgets but those who understand that content has become infrastructure. To this end, I recommend executives begin evaluating which parts of their business create information that is difficult to replicate and valuable to reuse.

As AI reshapes distribution, the most resilient companies will not necessarily be those with the largest audiences, but those with expertise, data and intellectual property that become embedded in the systems that power decision-making. In a world where machines mediate attention, value goes to information that is reliable, attributable and integrated into the systems that consume it.

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