The Macro Shift · established evidence

A Wealth of Information, A Poverty of Attention: Herbert Simon and the Economics of the Answer Economy

Last reviewed 2026-07-20. Written by Chandranshu Kumar, Founder, Raveneye Global. · 10 min read

The phrase attention economy is not a marketing coinage. It comes from the economist and Nobel laureate Herbert Simon, who wrote in 1971 that "a wealth of information creates a poverty of attention." His point was structural: once information becomes abundant, the scarce resource is no longer the information but the attention needed to consume it. That single sentence, written before the web existed, is the most precise account of why content abundance now makes buyer attention the real competitive currency of search. When an engine answers a question with a few named sources instead of a page of links, it is allocating a buyer's scarce attention on the buyer's behalf, and the businesses that win are the ones present at the point where that allocation happens. This is the root reason a visibility measure must treat reputation and attention as a first-class pillar, not an afterthought bolted onto a ranking number.

The sentence that named the attention economy

In 1971 Herbert Simon contributed an essay titled "Designing Organizations for an Information-Rich World" to a volume on computers and the public interest. In it he set out the argument that has since been shortened, paraphrased, and occasionally misattributed, but rarely improved on: "in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it."

Two things are worth noticing about the provenance. First, this is economics, not commentary. Simon was reasoning about scarcity and allocation, the core of the discipline, and applying it to information as a resource. Second, he was describing a condition that was still theoretical in 1971 and is now the default state of every market a buyer researches online. The essay is the correct theoretical anchor for the answer economy precisely because it does not depend on any particular technology. It depends only on abundance, and abundance has arrived.

Content abundance and information overload marketing

Simon's inversion is easy to state and hard to internalize. In a world of scarce information, producing more information is straightforwardly valuable, and for most of commercial history that was the correct instinct: publish more, list in more places, say more. In a world of abundant information, producing more of it can be self-defeating, because the constraint has moved. The bottleneck is no longer supply. It is the fixed, non-expandable budget of attention on the other side.

This reframes a great deal of ordinary marketing practice. The reflex to publish more pages, chase more keywords, and add more surface area assumes the old scarcity. Under Simon's account, that effort competes for a resource that does not grow, and it competes against every other source doing the same thing. The practical question stops being "how much can we produce" and becomes "how do we earn a share of a resource that is fixed and contested." Information overload is not a temporary annoyance to be engineered away; in Simon's framing it is the permanent economic weather in which all findability now operates.

Bounded rationality: buyers cannot evaluate everything

Simon is not only the source of the attention-economy idea. He is also the author of the two concepts that explain what buyers actually do when attention is scarce, and both earned him the Nobel Memorial Prize in Economic Sciences in 1978. The first is bounded rationality: the recognition that real decision-makers do not have unlimited time, information, or cognitive capacity, and so they cannot behave like the perfectly rational, fully informed agent of classical theory.

A buyer choosing a local service does not, and cannot, evaluate every provider in the market. They operate inside limits, and those limits are exactly the scarce attention Simon described. Bounded rationality means the decision is made from a small, manageable subset of options that the buyer can actually hold in mind, and whatever shapes that subset shapes the outcome. When an engine returns a synthesized answer naming a few businesses, it is not merely convenient. It is fitting itself precisely to the bounded, attention-limited way people were always going to decide.

Satisficing: why buyers act on the first adequate answer

The second concept is satisficing, Simon's term for the strategy bounded agents actually use. Rather than searching for the optimal option, which would require the unlimited attention they do not have, people accept the first option that clears a threshold of "good enough." They stop searching when they find something adequate, not when they find the best.

This is the mechanism that makes a single synthesized answer disproportionately powerful. If buyers satisfice, then the answer presented first, framed as sufficient, and requiring no further search is not competing on the merits against the alternatives. It is competing against the buyer's willingness to keep looking, and satisficing theory predicts that willingness is low. The behavioral trace of this is now visible in primary data. Pew Research Center, tracking the real browsing of 900 US adults across 68,879 Google searches in March 2025, found that when an AI summary appeared, users clicked through to a traditional result in only 8 percent of searches, versus 15 percent when no summary was present, and clicked a link inside the summary itself only about 1 percent of the time. The synthesized answer is treated as adequate, and the search ends. That is satisficing, measured.

The consideration set is the scarce resource

Marketing has its own name for the small subset a bounded, satisficing buyer actually chooses from: the consideration set. Simon's economics explains why that set, rather than the total field of competitors, is the real object of competition. Attention is scarce, so the buyer holds only a few options in mind; they satisfice, so they rarely expand the set once it is adequate; and whoever controls how the set is assembled controls the outcome without having to win a fair comparison.

For thirty years the ranked list of links was a generous consideration set. It presented many options and left the assembling of the shortlist to the buyer, whose scarce attention did the filtering. A synthesized answer performs that filtering itself and hands back a set of two or three. The competitive question changes accordingly. It is no longer "where do we rank among many" but "are we inside the small set the engine assembled on the buyer's behalf," because being absent from that set is not the same as ranking poorly within it. It is being outside the decision entirely.

Why attention deserves a first-class pillar, not an afterthought

If attention is the scarce resource and reputation is much of what earns a place in a bounded buyer's consideration set, then a serious visibility measure cannot treat either as a footnote to ranking. This is the load-bearing conclusion of Simon's argument for how a business should be scored. A single ranking number measures position in a list, an artifact of the old, information-scarce era. It does not measure whether a business commands attention or whether its reputation carries it into the set an engine assembles.

This is why the Machine-Readiness Score is built as four pillars, classic search, the local map pack, AI answers, and reputation, rather than one ranking figure. The structure is a direct response to Simon's economics: attention is not collapsing to a single channel, it is fragmenting across several structurally different surfaces where buyers now spend it, and reputation is the pillar that most directly governs whether a business is chosen once found. Treating attention and reputation as first-class measures is not a stylistic preference. It is what follows once you take seriously that the scarce resource is attention and that bounded buyers satisfice on reputation-laden shortlists.

An evolution, not an apocalypse

Simon's framing also disciplines the conclusion. Attention being scarce and reallocated is not the same as search collapsing, and the record matters here. The rise of zero-click behavior is real and measured across independent windows: SparkToro's clickstream analysis found 58.5 percent of US Google searches ended without a click in 2024, rising to roughly 68 percent by early 2026. The pressure on the click is genuine. So is the reallocation of attention across AI answers, the map pack, and reputation.

What has not happened is the widely forecast collapse of search itself. Gartner's 2024 prediction that traditional search volume would fall 25 percent by 2026 has not materialized as stated; Google still holds the large majority of the search market. The reading Simon's economics supports is that attention is being reallocated across more surfaces rather than vanishing from search. That is precisely why the right response is a multi-surface measure you check against evidence over time, not a single number and not a panic. Abundance is the permanent condition. Where the scarce attention goes is the thing to measure.

The evidence

Key findings, with their sources

Herbert Simon's 1971 essay is the origin of the attention economy: "a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it."

established Simon, H. A., "Designing Organizations for an Information-Rich World", in Greenberger (ed.), Computers, Communications, and the Public Interest, Johns Hopkins University Press, 1971 (pp. 37-52).
Simon is also the source of bounded rationality and satisficing, the theory that decision-makers act on the first adequate option rather than the optimal one; he received the Nobel Memorial Prize in Economic Sciences in 1978.

established Simon, H. A., Nobel Memorial Prize in Economic Sciences, 1978; bounded rationality and satisficing as summarized in the seminal-source record.
When an AI summary appeared, users clicked a traditional result in about 8% of searches, versus 15% without a summary, and clicked a link inside the summary only about 1% of the time, the behavioral signature of satisficing on the first adequate answer.

established Pew Research Center, "Do people click on links in Google AI summaries?", 2025-07-22 (browsing panel, 900 US adults, 68,879 searches).
Zero-click searches rose from 58.5% of US Google searches in 2024 to roughly 68% by early 2026, evidence that attention is being reallocated away from the outbound click.

established SparkToro / Datos (2024 Zero-Click Search Study) and SparkToro / Similarweb (2026), covered by Search Engine Land.
A 2024 forecast that traditional search volume would drop 25% by 2026 has not materialized as stated; Google still holds the large majority of the search market.

contested Gartner, Inc. press release, 2024-02-19; reality-check reporting, Future Factors, "Gartner Said Search Would Drop 25% in 2026. It Didn't."

Calibration

What is proven, what is promising, what is unproven

Evidence tier	Tactics	What the evidence says
established	Treat attention as the scarce, fixed resource and reputation as a first-class visibility pillar; measure standing across multiple surfaces rather than a single rank.	Simon (1971) attention economics and bounded rationality/satisficing; Pew (2025) primary click data; SparkToro (2024, 2026) zero-click studies.
emerging	Aim to be the cited, adequate answer inside AI-synthesized results, on the premise that satisficing buyers stop at it.	Aggarwal et al. (2024) GEO paper is peer-reviewed, but its interventions are recent and still being replicated across engines.
contested	Reallocating budget as if classic search volume were collapsing to AI chatbots.	Gartner's 25%-by-2026 volume-collapse forecast did not materialize as stated; the pattern is reallocation across surfaces, not collapse.

Reference

Glossary

Attention economy: The idea, originating with Herbert Simon in 1971, that when information is abundant the scarce resource is the attention required to consume it, so attention must be allocated efficiently.
Bounded rationality: Simon's concept that real decision-makers have limited time, information, and cognitive capacity, and therefore cannot evaluate every option or behave as perfectly rational agents.
Satisficing: Simon's term for accepting the first option that is good enough rather than searching for the optimal one; the strategy bounded, attention-limited buyers actually use.
Consideration set: The small subset of options a buyer actually chooses from. Under bounded rationality and satisficing, whoever shapes this set shapes the outcome.
Machine-Readiness Score: A visibility measure built as four pillars, classic search, the local map pack, AI answers, and reputation, designed to track where a business stands as attention fragments across surfaces.

Straight answers

Frequently asked questions

Who coined the term attention economy?

The economist and Nobel laureate Herbert Simon, in a 1971 essay titled "Designing Organizations for an Information-Rich World." He argued that a wealth of information creates a poverty of attention, meaning that once information is abundant, attention becomes the scarce resource that has to be allocated.

What does Simon's attention economy have to do with AI search?

AI answers are the clearest example of Simon's argument in practice. When an engine returns a synthesized answer naming a few sources, it is allocating a buyer's scarce attention on their behalf. Simon's bounded rationality and satisficing also explain why buyers act on that first adequate answer instead of evaluating alternatives.

What is satisficing, and why does it matter for getting chosen?

Satisficing is accepting the first option that is good enough rather than searching for the best. Because attention is limited, buyers satisfice, which is why the answer presented first and framed as sufficient captures a disproportionate share of action. Pew's 2025 data shows users clicked through in only about 8% of searches when an AI summary was present.

Why should reputation and attention be measured as a pillar rather than an afterthought?

Because attention is the scarce resource and reputation is much of what earns a place in a bounded buyer's consideration set. A single ranking number measures position in a list, not whether a business commands attention or is trusted enough to be chosen. That is the root reason a visibility measure treats reputation and attention as a first-class pillar.

Does the attention economy mean search is dying?

No. Simon's framing points to reallocation, not collapse. Zero-click behavior has risen and AI answers absorb attention, but a 2024 forecast of a 25% search-volume drop by 2026 did not play out as stated and Google still holds most of the market. Attention is fragmenting across surfaces, which is exactly why a multi-surface measure is the right response.

Provenance

Sources

Simon, H. A., "Designing Organizations for an Information-Rich World", in M. Greenberger (ed.), Computers, Communications, and the Public Interest, Johns Hopkins University Press, 1971 (pp. 37-52) (established)
Simon, H. A., bounded rationality and satisficing; Nobel Memorial Prize in Economic Sciences, 1978 (established)
Pew Research Center, "Do people click on links in Google AI summaries?", pewresearch.org, 2025-07-22 (primary panel, 68,879 searches) (established)
SparkToro & Datos, "2024 Zero-Click Search Study", sparktoro.com (established)
SparkToro & Similarweb, "In 2026, Less than One Third of Google Searches Still Send a Click", sparktoro.com, covered by Search Engine Land (established)
Gartner, Inc., "Gartner Predicts Search Engine Volume Will Drop 25% by 2026, Due to AI Chatbots and Other Virtual Agents", press release, 2024-02-19 (contested, used as a forecast-accuracy check)gartner.com
Aggarwal et al., "GEO: Generative Engine Optimization", KDD 2024, arXiv:2311.09735 (peer-reviewed, established)arxiv.org

Every figure above is attributed to a real, dated source and tagged with its evidence tier. Where a claim could not be verified to a primary source, it is not stated as fact.