America’s Biggest Macro Bet Is AI. And There’s No Plan B.

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The US economy has quietly become a single, highly concentrated wager.

Strip away the headlines, and the story is simple. Outside of artificial intelligence, there is visible weakness across the American economy. Manufacturing is soft. Interest rates are biting. Housing affordability is broken. Consumer spending is increasingly bifurcated. Yet GDP growth keeps surprising on the upside.

Why? Because AI is carrying far more weight than most people realize.

By some estimates, close to 40 percent of US economic growth this year has come from capital expenditure tied directly to AI. Add the wealth effect from soaring AI-linked equities, and the number rises further. Roughly 80 percent of stock market gains have been driven by AI-related companies. That, in turn, is powering spending by the top 10 percent of households, which now account for the majority of discretionary consumption.

Put differently, you can make a credible argument that 60 percent of US economic growth today traces back to AI. That is not diversification. That is concentration risk.

What makes this moment tricky is the disconnect between financial impact and real economic output.

AI is clearly moving markets. It is reshaping capex budgets. It is inflating balance sheets. It is driving hiring in specific technical roles and freezing it elsewhere. But in terms of measurable productivity gains across the economy, the evidence remains thin.

There has been a modest uptick in productivity over the past two to three years. How much of that can be attributed to AI? Probably very little so far.

That is not unusual. The internet followed a similar path. Massive investment came first. Tangible productivity gains followed years later, peaking only after the dot-com crash forced efficiency onto the system. AI will likely follow the same arc. The difference this time is speed. The investment ramp-up has been breathtakingly fast.

Two years ago, AI capex barely registered in GDP growth. Today, it is doing the heavy lifting. This is the fastest tech investment cycle buildup the US has ever seen.

That speed matters, because it compresses both upside and risk.

There is a second, underappreciated channel through which AI is shaping the economy: asset inflation.

When equity markets surge, spending follows. But not evenly. In the US, consumer demand is now overwhelmingly driven by the wealthiest households. The top 10 percent spend freely when their portfolios rise. Everyone else tightens belts.

AI stocks have become the engine of that wealth effect. When shares of Microsoft, Amazon, and Meta climb, high-income consumption follows. Travel, luxury goods, services, and experiences all benefit.

This masks weakness elsewhere. Middle- and lower-income consumers face higher costs, stagnant wages, and growing insecurity. But as long as the asset-rich keep spending, headline growth holds up.

That is fine until markets wobble.

There is another key difference between AI and past technological waves, and it has nothing to do with code or compute.

This is the most disliked tech revolution in modern history.

When electricity spread, people were optimistic. When cars arrived, society adapted eagerly. Even during the internet boom, surveys showed widespread excitement about what the web could enable.

AI is different. Public sentiment is dominated by fear.

Only about a third of people report feeling positive about AI. Most want it regulated. Many see it less as a tool and more as a threat. And the messaging has not helped. For years, techno-optimists have framed AI’s primary benefit as labor displacement. That might be economically rational, but socially it is radioactive.

People hear one message repeatedly: use AI or lose your job.

That creates anxiety, not adoption. It also slows the translation of investment into productivity. Fear is a poor accelerant.

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Financial historians tend to agree on a few recurring signals when markets enter bubble territory. Call them the four O’s.

The first is overinvestment. Today, tech investment as a share of GDP is around 5 percent, roughly where it stood in 2000. That box is checked.

The second is overvaluation. Depending on the metric, valuations are either approaching or already exceeding historical extremes. Price-to-free-cash-flow and long-term earnings multiples suggest we are closer to the edge than many would like to admit.

The third is overownership. Americans now hold about 52 percent of their financial wealth in equities. That is higher than during the dot-com peak. Retail trading volumes remain elevated. Crowding is real.

The fourth is overleverage. This one is more nuanced. AI leaders initially funded expansion with internal cash flows. But that is changing. Over the past year, some of the largest issuers of corporate debt have been AI leaders racing to stay ahead.

This is where fear enters the equation.

The dominant mindset in boardrooms today is not return optimization. It is existential defense.

A comment by Sundar Pichai captured it succinctly when he said the biggest risk is not investing too much in AI, but investing too little. That sentiment has become doctrine across big tech.

No CEO wants to explain why their company missed the AI wave. That fear accelerates spending, compresses decision cycles, and pushes companies to finance expansion with debt rather than patience.

In the 1990s, tech investment rose gradually. This time, it has exploded almost overnight. That makes the system more fragile, even if adoption ultimately proves faster.

There is a popular argument making the rounds that this is a “good bubble.”

The logic is sound. Technology bubbles tend to leave behind useful infrastructure. Fiber optics survived the dot-com crash. Data centers and cloud platforms emerged stronger. Real estate bubbles, by contrast, leave debt and rubble.

AI investment will almost certainly produce lasting benefits. Tools will improve. Productivity will eventually rise. Society will adapt.

But calling it a good bubble does not eliminate risk. It simply reframes the outcome. Even good bubbles hurt when they deflate. Capital misallocation still destroys value. Timing still matters.

Here is the uncomfortable conclusion.

The US economy has tied too much of its near-term performance to AI for failure to be painless. If AI adoption delivers productivity gains over the next two to three years, the bet pays off. Growth broadens. Wages catch up. Markets stabilize.

If it does not, the downside is not confined to tech stocks. The wealth effect reverses. High-end consumption slows. Corporate capex pulls back. Debt burdens feel heavier. Political pressure intensifies.

For now, everything points in one direction. Investment is accelerating. Markets remain confident. Optimism among capital allocators is intact, even if public sentiment lags.

America is all in on AI. There is no hedged position. No parallel engine waiting in the wings.

That does not mean the bet is wrong. But it does mean the margin for error is thinner than markets are pricing in.

And in macro, concentration is never free.

Interested in learning more about AI? Check out our previous coverage here:

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Peeyush and Mohit

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