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Tech Giants’ AI Investment Surge Rattles Markets
Investor concerns have resurfaced across global markets following revelations that major technology companies plan to spend a combined $660 billion on artificial intelligence (AI) investments this year, triggering a sharp sell-off in tech stocks.
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The pullback comes after Amazon, Google, Microsoft and Meta disclosed aggressive capital expenditure plans focused on data centres and specialised AI chips—representing a nearly 60% increase from last year’s $410 billion and an amount comparable to the annual economic output of some mid-sized countries.
Amazon Leads AI Capital Expenditure Push
Among the big tech players, Amazon has emerged as the most ambitious spender, projecting capital expenditure of up to $200 billion in 2026, around $50 billion higher than market expectations. This level of spending eclipses even the already substantial commitments announced by Google and Microsoft.
The scale of the investments has unsettled shareholders despite robust cloud revenue growth, wiping hundreds of billions of dollars off market valuations and reigniting fears of an emerging AI investment bubble.
Are Investors Right to Be Concerned?
According to Nigel Green, CEO of deVere Group, one of the world’s largest independent financial advisory organisations, these fears—while understandable—are largely short-sighted.
“The sheer size of the spending has spooked investors. It has revived familiar concerns that the AI arms race may be drifting from strategic investment into excess without clear performance justification,” Green said.
However, he argues that such concerns fail to fully grasp the nature of AI investment.
AI Infrastructure Is a Long-Term Foundation
Green emphasised that the market is framing the issue incorrectly.
“This is not capital being poured into a single product that must quickly pay for itself. What’s being built is a foundational layer that will underpin everything these companies do for years to come,” he explained.
Much of the AI spending, he noted, is front-loaded but directed at long-lived infrastructure, with accounting impacts spread across multiple years even though cash commitments occur upfront.
AI Returns Go Beyond Direct Revenue Streams
Expectations that AI must immediately generate standalone revenues also miss the bigger picture, Green said.
“AI doesn’t need to appear as a separate line item to deliver returns. Its value shows up in stronger customer retention, increased pricing power and reduced churn across existing platforms,” he added.
At the scale of global cloud platforms, even marginal improvements can translate into substantial and recurring financial gains.
Cloud Economics Strengthen the AI Case
The economics of AI become clearer within cloud businesses. As AI workloads mature, customers become more deeply embedded, leading to higher-value, longer-term contracts. Over time, this dynamic supports stronger margins, rather than eroding profitability.
“These cloud platforms already deliver exceptional margins,” Green said. “Advanced AI capabilities only deepen that advantage.”
Defensive Spending in a Competitive Landscape
Green also pointed out that a portion of the AI investment is defensive by necessity.
“Maintaining relevance in today’s tech landscape requires scale. The market may dislike the escalation, but for these companies, standing still simply isn’t an option,” he said.
Long-Term Value Versus Short-Term Volatility
In conclusion, Green believes current market volatility reflects uncertainty around timing, not flaws in the underlying investment logic.
“Similar doubts surrounded earlier waves of infrastructure spending, which ultimately proved foundational. This phase of AI investment is laying the groundwork for sustained earnings power over the long term. In fact, underinvesting may be the greater risk for big tech,” he said.
