That is a 36% year‑on‑year increase from 2025, making this one of the fastest capital expenditure (CapEx) booms in modern corporate history. 

So, let’s discuss. Is this exceptional AI CapEx surge cycle driving productivity in the economy, or are we inflating another technological asset bubble?

The AI CapEx Scale: What’s Happening Now

Across the largest tech firms, the hyperscalers and cloud giants, capital spending is now structural. Amazon, Google, Meta and Microsoft are expected to put hundreds of billions into new infrastructure in 2026, much of it dedicated to specialised computing clusters, advanced networking and data centre capacity. 

The focal point of this spending is not mere servers or office upgrades. It’s data centres built specifically for high‑power compute workloads, facilities optimised for parallel processing at scale. 

These require specialised hardware like GPUs and high‑bandwidth memory, and they draw massive amounts of energy. 

One recent example shows just how strategic these moves have become. Nebius Group signed a multi‑year deal with Meta Platforms worth up to $27 billion to supply dedicated AI computing capacity by 2027, a contract driven by extreme demand and limited supply for high‑performance computing systems. 

Productivity: What the Investment Could Bring

No doubt that enhanced computing capacity enables economic value. Faster processing, more reliable inference workloads, and greater cloud availability can drive:

• Higher labour productivity by automating routine tasks.
• Faster research and development cycles in sectors from healthcare to manufacturing.
• Lower costs for compute‑intensive services, once infrastructure matures and utilisation improves.

For context, the semiconductor industry, a cornerstone of this infrastructure build‑out, is forecast to approach nearly $1 trillion in sales in 2026, with AI‑specific chips maintaining strong annual growth. 

From a macro perspective, such CapEx adds directly to aggregate demand and GDP in the short term. Data centre construction, advanced chip manufacturing, and supporting supply chains all contribute to economic activity that wouldn’t exist without this cycle. 

Bubble Territory: Where the Risks Begin

But there are strong arguments that we are edging into asset inflation rather than productive investment.

First, the pace of spending vastly outstrips current revenue realisation in the economy. Many of these specialised facilities operate at negative operating margins early in their life, requiring ongoing funding before they generate sustainable returns.

Second, a lot of the valuations attached to tech infrastructure assets incorporate lofty future earnings expectations. If those earnings don’t materialise, because adoption slows or competition increases, we could face rapid repricing. 

We’ve already seen some tension in the market, with certain historic investment commitments being scaled back. 

Third, hyperscalers are relying more on external financing even as their own cash flows get tighter. That’s a classic hallmark of an investment boom that may not be fully backed by near‑term productive returns. 

Semiconductors and Data Centres: The New “Oil”?

The analogy of compute as “the new oil” captures two truths:

1. Dependency: Modern AI workloads require massive compute capacity, just as 20th‑century industry relied on petroleum.
2. Infrastructure bottlenecks: Scaling compute, even with unlimited capital, is limited by semiconductor supply, power delivery, and cooling technology.

Already, suppliers like TSMC have posted strong revenue outlooks, showing reliance on advanced chips across the industry.

In parallel, smaller specialist data centre operators, such as CoreWeave, have expanded at a rapid clip. CoreWeave now operates dozens of facilities globally and has become a major supplier for bespoke compute capacity. 

But then, this infrastructure is expensive and energy‑intensive. Many facilities find it hard to break even without long‑term contracts or guaranteed utilisation.

Investment Implications: Winners and Fragilities

From an investment standpoint, certain firms appear ready to benefit if demand holds:

• Nvidia is at the centre of the compute supply chain. Its recent San Jose GTC 2026 forecast shows at least $1 trillion in chip revenue by 2027, driven by demand for next‑generation chips at scale. 
• Other chip designers and foundries stand to gain from backlogged orders and long production lead‑times.
• Data centre REITs and infrastructure funds may see longer‑term cash returns as contracts mature.

On the risk side, overcapacity, falling prices for older hardware, and slower adoption outside of hyperscale use cases are still substantive challenges.

So, Growth Engine or Asset Bubble?

Standing here in March 2026, we see both sides.

On the productivity side, this spending wave is building infrastructure that will underpin major advances in how industries operate. It’s tangible investment in capacity, not just speculation in intangible assets.

On the asset inflation side, the pace and scale of spending go beyond today’s revenue reality. Markets have priced future growth aggressively, which increases the risk of repricing if adoption deviates from expectations.

Now, are we financing a foundation for long‑term productivity, or are we inflating the price of future earnings prematurely?

The focus is tougher this time because Alphabet’s recent surge has challenged long-held beliefs about first mover advantage.

Across Big Tech, spending plans are expanding at a rate the sector has never seen. Microsoft, Meta, Amazon and Alphabet are expected to raise their combined investment in AI by about 30% this year, pushing total outlay beyond $500 billion. 

This explains the unease on Wall Street. Investors are no longer impressed by scale; they want results from these Big Tech earnings.

Microsoft, once viewed as the early winner after backing OpenAI, is now being questioned. Its shares and Meta’s have both fallen more than 6% over the past three months of 2025. 

Amazon, helped by its November deal with OpenAI, edged up 5.1%, while Alphabet’s stock climbed nearly 29%, driven by strong feedback on Google’s Gemini 3 model and its deal to power Apple’s revamped Siri.

“Alphabet has the upper hand in the AI race as investors recognize that proprietary ecosystems, such as Apple and Search in Google, are tough to penetrate,” said David Wagner, head of equities at Aptus Capital Advisors. “Like in the internet boom, the first-mover advantage doesn’t always win the marathon.”

Microsoft and Meta will report their earnings on Wednesday, with other Big Tech companies like Alphabet and Amazon following next week.

Forecasts note Google Cloud growth picked up to about 35% in the last quarter of 2025, while Microsoft’s Azure is expected to slow slightly to 38.8%. Amazon Web Services is seen growing just over 21%, still modest by historical standards.

The concern is whether companies using this technology are actually seeing benefits. A recent PwC survey of 4,454 chief executives found that more than half reported no revenue gains or cost savings from their investments so far.

“For this not to be a bubble by definition, it requires that the benefits of this are much more evenly spread,” Microsoft chief executive Satya Nadella said at Davos.

Microsoft’s own challenges are increasing. Analysts at Morgan Stanley describe sentiment around the company as a “wall of worry,” noting stronger competition in cloud services and its reliance on OpenAI, where it holds a 27% stake. 

The company has also warned that shortages in AI capacity will last until at least June, while high memory chip prices are weighing on the wider PC market, a key part of its Windows and Xbox business. 

Revenue growth for the quarter is expected to slow to about 15.3%, the weakest in three quarters.

Alphabet, by contrast, is benefiting from tighter links between AI and its core search business, alongside a steadier advertising market. It is also opening new ground by supplying its Tensor Processing Units to Anthropic, a move worth tens of billions of dollars and a break from its long-standing policy of keeping those chips for internal use.

Stronger ad targeting and recommendations are expected to lift Meta’s revenue by more than 20%, but heavy spending on elite AI hires is set to drag profits to their lowest level in almost three years. 

Meanwhile, growth in Amazon’s North American retail arm is slowing, but AWS is showing gradual improvement, helped by renewed confidence in its AI strategy.