Herbert Simon’s warning about information overload reshapes the attention economy

The origins of the attention economy

In the mid-20th century, American economist Herbert A. Simon wrote about the growing tension between information and attention. He argued that while data could be abundant, human attention was a finite resource—and its scarcity would shape the future of information consumption. His insights predated the digital revolution but anticipated the challenges of an era dominated by data.

Simon’s ideas gained traction as the internet expanded, but it was British mathematician Clive Humby who later compared data to oil, calling it the fuel of a new industrial revolution. Unlike oil, however, data is neither finite nor scarce. Its exponential growth has instead intensified the competition for attention, a dynamic Simon had foreseen decades earlier.

How AI is accelerating the competition for attention

The attention economy, where human focus is treated as a tradable commodity, has matured alongside technological advancements. Today, AI and large language models (LLMs) are amplifying its effects by lowering the barriers to content creation. The result is a surge of synthetic data—text, images, and media generated at scale—that further strains human attention.

AI is also changing how people access information. While search engines and social platforms once acted as gatekeepers, AI-driven systems now curate, summarize, and even generate responses on behalf of users. This shift means enterprises and creators must compete not only for visibility but for the algorithms that control how information is distributed.

For businesses, the challenge is twofold: extracting actionable insights from vast datasets while ensuring their messages break through the noise. As Simon predicted, the wealth of information has not made decision-making easier—it has made attention the scarcest resource of all.

Related challenges in the digital economy

The strain on attention is not the only pressure point in the digital economy. Earlier reporting by LazyFounder highlighted how enterprises struggle with other hidden costs of data-dependent operations. For instance, an investigation into European data centers revealed a lack of transparency around energy and water consumption, complicating sustainability efforts for companies reliant on cloud infrastructure.

Cyber resilience is another critical concern. Research shows that nearly half of organizations experience operational shutdowns, data loss, or revenue decline following cyber incidents. As AI lowers the cost of generating content, it also increases the risk of misinformation and automated attacks, forcing businesses to invest in defenses that protect both their data and their audience’s trust.

Cheaper hosting and AI solutions may offer short-term savings, but they often introduce long-term risks. Companies must weigh the trade-offs between cost and reliability, as downtime, poor support, or security gaps can erode the initial benefits of scaling quickly.

What this means

Lazyfounder analysis — our interpretation, not reported fact.

Simon’s warning about the poverty of attention was not just a critique of information overload—it was a prediction of how value would shift in the digital economy. Today, his thesis is playing out at scale: attention, not data, is the bottleneck for enterprises, creators, and platforms. AI has made content production nearly frictionless, but it has also made attention more fragmented and fleeting.

For founders and operators, this means two things. First, strategies that rely on volume—more ads, more posts, more notifications—are less effective in a world where attention is the limiting factor. Second, the ability to filter, synthesize, and deliver high-value insights is now a competitive advantage. The enterprises that thrive will be those that respect their audience’s attention, not just their data.

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