The 2028 Global Intelligence Crisis⁠↗

Over the past fifty years, the U.S. economy built a giant rent-extraction layer on top of human limitations: things take time, patience runs out, brand familiarity substitutes for diligence, and most people are willing to accept a bad price to avoid more clicks. Trillions of dollars of enterprise value depended on those constraints persisting.

Financial advice. Tax prep. Routine legal work. Any category where the service provider’s value proposition was ultimately “I will navigate complexity that you find tedious” was disrupted, as the agents found nothing tedious.

We had overestimated the value of “human relationships”. Turns out that a lot of what people called relationships was simply friction with a friendly face.

White-collar openings were collapsing while blue-collar openings remained relatively stable (construction, healthcare, trades). The churn was in the jobs that write memos (we are, somehow, still in business), approve budgets, and keep the middle layers of the economy lubricated. Real wage growth in both cohorts, however, had been negative for the majority of the year and kept declining.

In the US, we weren’t asking about how the bubble would burst in AI infrastructure anymore. We were asking what happens to a consumer-credit economy when consumers are being replaced with machines*.*

Displaced white-collar workers did not sit idle. They downshifted. Many took lower-paying service sector and gig economy jobs, which increased labor supply in those segments and compressed wages there too.

In this cycle, the job losses have been concentrated in the upper deciles of the income distribution. They are a relatively small share of total employment, but they drive a wildly disproportionate share of consumer spending. The top 10% of earners account for more than 50% of all consumer spending in the United States. The top 20% account for roughly 65%. These are the people who buy the houses, the cars, the vacations, the restaurant meals, the private school tuition, the home renovations. They are the demand base for the entire consumer discretionary economy.

When these workers lost their jobs, or took 50% pay cuts to move into available roles, the consumption hit was enormous relative to the number of jobs lost. A 2% decline in white-collar employment translated to something like a 3-4% hit to discretionary consumer spending. Unlike blue-collar job losses, which tend to hit immediately (you get laid off from the factory, you stop spending next week), white-collar job losses have a lagged but deeper impact because these workers have savings buffers that allow them to maintain spending for a few months before the behavioral shift kicks in.

It should have been clear all along that a single GPU cluster in North Dakota generating the output previously attributed to 10,000 white-collar workers in midtown Manhattan is more economic pandemic than economic panacea. The velocity of money flatlined. The human-centric consumer economy, 70% of GDP at the time, withered. We probably could have figured this out sooner if we just asked how much money machines spend on discretionary goods. (Hint: it’s zero.)

By the end of 2027, it threatened every business model predicated on intermediation. Swaths of companies built on monetizing friction for humans disintegrated.