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The Citrini essay posits that as firms replace labor with AI, spending shifts from wages (fueling consumption) to data centers. This inflates GDP metrics without creating broad economic circulation, resulting in a hollowed-out 'ghost GDP' that doesn't reflect real consumer health.

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Instead of a universal productivity boom, AI will eliminate repetitive white-collar jobs. This will shrink the consumer base, reducing overall demand and creating a powerful deflationary force, further entrenching a feudal economic structure with fewer 'lords' and more 'serfs.'

The U.S. economy is entering an 'efficiency era' where AI-driven productivity allows GDP to grow without a proportional increase in jobs. This structural decoupling makes traditional economic health assessments obsolete and fuels recession fears.

Widespread AI-driven job loss will reduce consumer spending. In response, businesses will be forced to cut costs further by accelerating AI adoption, which in turn leads to more job losses and even lower consumption, creating a vicious cycle.

Beyond simple productivity gains, AI will eliminate the need for entire service-based transactions, such as paying for basic legal documents or second medical opinions. This substitution of paid services with free AI output can act as a direct deflationary headwind, a counterintuitive effect to the typical AI-fueled growth narrative.

A paradox of powerful AI is that it can be 'GDP-destroying.' When AI substitutes for a service you would have paid for (e.g., hiring a contractor), it creates immense personal value but removes a transaction from the economy. This makes GDP a poor metric for AI's true economic contribution, which may be understated.

Contrary to the consensus view of explosive AI-driven growth, AI could be a headwind for near-term GDP. While past technologies changed the structure of jobs, AI has the potential to eliminate entire categories of economic activity, which could reduce overall economic output, not just displace labor.

While AI is often viewed abstractly through software and models, its most significant current contribution to GDP growth is physical. The boom in data center construction—involving steel, power infrastructure, and labor—is a tangible economic driver that is often underestimated.

The tangible economic effect of the AI boom is currently concentrated in physical capital investment, such as data centers and software, rather than widespread changes in labor productivity or employment. A potential market correction would thus directly threaten this investment-led growth.

Even if AI drives productivity, it may not fuel broad economic growth. The benefits are expected to be narrowly distributed, boosting stock values for the wealthy rather than wages for the average worker. This wealth effect has diminishing returns and won't offset weaker spending from the middle class.

The massive capex spending on AI data centers is less about clear ROI and more about propping up the economy. Similar to how China built empty cities to fuel its GDP, tech giants are building vast digital infrastructure. This creates a bubble that keeps economic indicators positive and aligns incentives, even if the underlying business case is unproven.