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Big Tech cannot simply cut spending on AI infrastructure as demand for computing power continues to surge, CNBC’s Mad Money host Jim Cramer argued recently. He said investors who doubt the durability of AI spending are underestimating how quickly customers are moving to secure the compute capacity needed for large-scale AI workloads.
Cramer said the market is still skeptical of tech stocks, with some investors viewing the current buildout as a “build it and they will come” strategy. He countered that the AI race has moved beyond speculation, pointing to Amazon’s AWS business as an example of how infrastructure investment is tied directly to customer demand.
He also emphasized that major AI customers are already seeking partners with the ability to handle massive workloads, naming OpenAI, Anthropic, and Meta. In his view, firms that slow investment risk losing those customers to rivals that continue expanding capacity.
Cramer cited Amazon’s plans to spend around $200 billion this year, largely to expand data-center capacity to compete with other cloud providers. He reiterated CEO Andy Jassy’s message that continued heavy investment is necessary, arguing that if a company does not build capacity, customers will go elsewhere.
He added that Amazon expects its in-house Trainium and Graviton chips to generate more than $20 billion in annual revenue. Cramer said the broader strategy reflects both demand for AI compute and efforts to reduce dependence on external suppliers while preserving margins.
Reuters reports that the AI investment wave remains very strong, with Microsoft, Meta, and Amazon forecast to spend over $600 billion on data centers in 2026.
Other supply-chain indicators also point to sustained demand. TSMC raised its revenue outlook, and ASML lifted growth forecasts, both attributed to record AI chip demand.
The investment cycle is also colliding with energy supply needs. The Wall Street Journal reported that 51 private electricity utilities in the U.S. plan to spend up to $1.4 trillion in the next five years, up 20% from previous plans, to meet AI-driven demand.
U.S. electricity prices rose 4.6% in March year over year, underscoring that the AI buildout depends on addressing energy availability as a prerequisite to scaling.
Cramer warned that if companies cut back on data-center funding, the financial outcome would likely move in the wrong direction—shifting capacity and related payments to competitors. He argued that the market has not yet fully appreciated the scale and urgency of the current AI infrastructure investment cycle, and that firms reducing spending could lose customers to those expanding capacity.
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