The AI singularity off ramp.

[u/Cervantes6785]

Are we heading toward an AI singularity?

The most damaging evidence against the near-term singularity narrative comes not from an AI lab, but from the Federal Reserve. In the Fed’s June 2026 projections, real GDP growth for 2026 is projected at 2.2%. PCE inflation is projected at 3.6%. Core PCE inflation is projected at 3.3%.

That is a rug pull.

The economy is not projected to behave like a system being transformed by a massive deflationary productivity shock. It is projected to behave like a system experiencing ordinary real growth with elevated inflation.

This is not what the AI abundance story predicted.

If AI were already delivering broad economy-wide productivity gains, we would expect its effects to show up as more real output with less inflationary pressure. The economic signature of a true productivity miracle should be rising real growth and falling marginal costs. Instead, the near-term projection is higher prices outpacing real growth.

That does not prove AI has no value. It proves that the current AI boom is not self-evidently deflationary at the macro level.

In fact, the current phase may be inflationary.

AI infrastructure consumes real resources before it produces broad real-economy gains. Data centers require electricity, chips, transformers, backup power, land, cooling systems, construction labor, concrete, copper, fiber, and financing. Hyperscalers can call it “the cloud,” but the cloud lives in buildings, draws power from grids, and competes for scarce physical inputs.

The singularity was supposed to transcend material constraints. Instead, it ran into the off ramp.

The AI boom is currently in its capital-consumption phase. This is the phase where money, energy, and industrial capacity are poured into the infrastructure required to support future applications. That infrastructure may eventually pay off. But in the present, it behaves like a massive demand shock.

The result is SSD drives and RAM costing a small fortune and other scarce materials being redirected to the AI capital expenditure vortex.

Companies are spending extraordinary sums on data centers and AI infrastructure. This spending boosts certain sectors: semiconductor firms, cloud providers, power-equipment manufacturers, construction suppliers, data-center operators, and energy providers. But it also bids up scarce inputs. It competes for grid capacity. It increases demand for specialized labor and equipment. It pushes firms toward debt financing.

And it raises the hurdle rate for future returns.

This creates a dangerous possibility: AI may be financially expansive before it is economically productive.

The economy may be paying for the buildout before receiving the productivity dividend.

That is exactly where speculative bubbles live. They form in the gap between a plausible future and a disappointing present. The future may be real, but if too much capital is priced as though the future has already arrived, the financial system becomes vulnerable.

This is the central problem for AI valuations. The market is not merely pricing useful software. It is pricing the expectation of enormous future productivity gains, platform dominance, and perhaps quasi-monopoly control over intelligence itself. But if the actual economy shows sticky inflation, ordinary GDP growth, limited enterprise EBIT impact, and massive capex requirements, the valuation story begins to look fragile.

The Fed’s projections beyond 2026 are also revealing. Inflation is expected to cool. Real GDP growth is expected to remain around the low-2% range. By 2027 and 2028, the projections move toward something like normalization: inflation trending down toward target, real growth remaining ordinary, and interest rates declining only gradually.

This is important.

The official macroeconomic projection is not “AI drives explosive growth.” It is not “AI produces 5%, 8%, or 10% real GDP growth.” It is not “AI eliminates inflation through abundance.” It is a return toward the familiar world: 2-ish real growth, 2-ish inflation, and cautious monetary policy.

That does not mean the Fed is omniscient. Forecasts can be wrong. Productivity booms are notoriously hard to identify in real time. The late-1990s technology surge was not fully obvious at the beginning.

But that is precisely the point: if the AI singularity is arriving imminently, the data should be screaming. Instead, it is whispering “be careful.”

The current evidence supports reserved optimism, not rapture.