For 2026, massive capital expenditure on AI infrastructure like data centers and semiconductors will fuel economic demand and inflation. The widely expected productivity gains that lower inflation are a supply-side effect that will take several years to materialize.

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The rapid construction of AI data centers is creating a huge surge in electricity demand. This strains existing power grids, leading to higher energy prices for consumers and businesses, which represents a significant and underappreciated inflationary pressure.

Morgan Stanley frames AI-related capital expenditure as one of the largest investment waves ever recorded. This is not just a sector trend but a primary economic driver, projected to be larger than the shale boom of the 2010s and the telecommunications spending of the late 1990s.

A recent Harvard study reveals the staggering scale of the AI infrastructure build-out, concluding that if data center investments were removed, current U.S. economic growth would effectively be zero. This highlights that the AI boom is not just a sector-specific trend but a primary driver of macroeconomic activity in the United States.

While economic principles suggest AGI will be hugely deflationary, Sam Altman points out a paradox. The massive, urgent investment required to build AI compute could drive a strange, inflationary period where capital is extremely valuable, creating profound uncertainty about interest rates.

For 2026, AI's primary economic effect is fueling demand through massive investment in infrastructure like data centers. The widely expected productivity gains that would lower inflation (the supply-side effect) won't materialize for a few years, creating a short-term inflationary pressure from heightened business spending.

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.

Before AI delivers long-term deflationary productivity, it requires a massive, inflationary build-out of physical infrastructure. This makes sectors like utilities, pipelines, and energy infrastructure a timely hedge against inflation and a diversifier away from concentrated tech bets.

Unlike the speculative overcapacity of the dot-com bubble's 'dark fiber' (unused internet cables), the current AI buildout shows immediate utilization. New AI data centers reportedly run at 100% capacity upon coming online, suggesting that massive infrastructure spending is meeting real, not just anticipated, demand.

The rapid build-out of data centers to power AI is consuming so much energy that it's creating a broad, national increase in electricity costs. This trend is now a noticeable factor contributing to CPI inflation and is expected to persist.

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.