At times, the AI sector appears locked in a contest to outspend everyone on data centers. The prevailing belief is that the company with the most data centers will command the greatest computing power, enabling it to develop superior AI products and secure long-term dominance. While this logic has its flaws—businesses typically thrive by increasing revenue and controlling costs—it has nonetheless captivated major technology firms. If this is indeed the race, Amazon currently holds the lead.

In its recent earnings report, Amazon forecasted $200 billion in capital expenditures for 2026, allocated across “AI, chips, robotics, and low earth orbit satellites.” This marks a substantial increase from the $131.8 billion planned for 2025. It would be easy to assume this entire budget is dedicated to AI, but Amazon operates extensive physical infrastructure, including facilities being upgraded for advanced robotics, so non-AI investments cannot be easily dismissed.

Google is not far behind. The company projected capital expenditures between $175 billion and $185 billion for 2026, up sharply from $91.4 billion the previous year. This figure significantly exceeds both its own past spending and the investments of most competitors.

Meta, reporting last week, estimated its 2026 capex between $115 billion and $135 billion. Oracle, once seen as a leader in AI infrastructure, now anticipates a comparatively modest $50 billion. Microsoft has not yet released an official 2026 projection, but its most recent quarterly spend of $37.5 billion annualizes to roughly $150 billion if maintained. This notable increase has drawn investor scrutiny toward CEO Satya Nadella, yet it still positions Microsoft in third place among its peers.

From an industry perspective, the reasoning is straightforward: AI’s transformative potential is expected to make high-performance computing a scarce future resource, and only firms controlling their own supply will endure. However, while companies like Google, Amazon, Microsoft, Meta, and Oracle rush to prepare for this anticipated compute shortage, their investors remain skeptical.

Each company saw its stock price decline as the market reacted to these massive financial commitments, with heavier spenders generally experiencing steeper drops. Importantly, this concern isn’t limited to firms still refining their AI product strategies—it applies across the board. Even companies like Microsoft and Amazon, with established cloud businesses and clear monetization paths for AI, face investor unease simply due to the scale of these expenditures.

While investor sentiment is influential, it may not alter the industry’s trajectory. If one believes AI is poised to reshape everything—a compelling case at this stage—changing course due to Wall Street nerves would seem shortsighted. Nonetheless, moving forward, major tech companies will likely face growing pressure to soften the narrative around just how costly their AI ambitions truly are.