There’s a number worth paying attention to this year, and it isn’t a stock price or an interest rate. It’s capital expenditures, the money the “Magnificent Seven” tech giants are pouring into building out artificial intelligence (AI) infrastructure, and the scale of it is genuinely historic.
The numbers behind the buildout
As this year’s earnings reports have rolled in, the “Magnificent Seven”—Apple, Microsoft, Alphabet, Amazon, Meta, Nvidia, and Tesla—have collectively guided toward AI-related capital spending that could exceed $700 billion in 2026, up from roughly $400 billion just last year. Some of the individual numbers are striking on their own:
- Amazon guided for approximately $200 billion in capex this year, up from $131 billion in 2025, with CEO Andy Jassy citing “very high demand” for AI to compute as the driver.
- Alphabet raised its capex guidance to around $180 billion—nearly double what it spent the year before, and well above what Wall Street analysts had initially expected.
- Microsoft is on pace to spend roughly $144 billion in its current fiscal year, largely on the chips and infrastructure needed to power its cloud and AI services.
- Meta guided $125 billion to $145 billion, citing both higher component costs and the need for additional data centre capacity to support future growth.
- Tesla plans to more than double its capex to around $20 billion, largely tied to robotaxi and Optimus robot production.
- Apple, by comparison, continues to spend more conservatively, guiding for roughly $13 billion this year.
Put together, this represents one of the largest sustained capital spending commitments by a group of companies in corporate history.
Where the money is going and who benefits
This spending isn’t abstract. It’s flowing into physical construction: data centres, power infrastructure, semiconductor fabrication, high-performance chips, and networking equipment. That means the beneficiaries extend well beyond the tech giants themselves.
Chipmakers like Nvidia, Broadcom, and Taiwan Semiconductor are seeing enormous demand for the processors that power AI workloads. Electric utilities are seeing rising demand from the sheer power requirements of large data centres. Construction and industrial companies are benefiting from the physical buildout of these facilities, and memory chip manufacturers are seeing tighter supply and stronger pricing as a result of the demand surge.
A genuine tailwind for the broader economy
This level of spending has real macroeconomic significance. Business investment is one of the core components of economic growth, and AI-related capital spending has become one of the more meaningful contributors to stronger GDP this cycle. It supports construction jobs, manufacturing activity, and demand for electricity and industrial materials—effects that extend well beyond Silicon Valley into communities where these data centres are actually built.
It’s also creating a self-reinforcing cycle in the markets: strong AI-related capital spending has helped drive some of the outsized earnings growth we’ve seen from the tech sector this year, which in turn has helped fuel the broader stock market rally.
The other side of the ledger
Of course, spending on this scale invites a fair question: will it pay off? Investors have grown increasingly attentive to whether the returns on this investment will justify the cost, and some prominent voices have raised concerns about the risk of overbuilding AI infrastructure ahead of demand. None of the Magnificent Seven have fully deployed their allocated 2026 capex yet, which means guidance could still shift if conditions change.
This is a legitimate risk to watch, and it’s one reason diversification remains important even amid an exciting growth story. But it’s also worth noting that companies of this scale don’t commit hundreds of billions of dollars lightly. This level of investment reflects genuine confidence in sustained demand for AI compute over the years ahead.
The bottom line
Whatever your view on where AI ultimately lands, the capital being deployed right now is already having a measurable, positive impact on economic activity—supporting jobs, investment, and growth well beyond the technology sector itself. We’re watching this trend closely as it continues to shape portfolios, and we’re happy to discuss how it factors into your own investment strategy.
The Advisor and/or members of the Advisor’s team may hold positions in securities discussed in this commentary. This commentary is for informational purposes only and does not constitute investment advice. Please speak with your advisor to discuss how these themes apply to your individual financial situation.
Commentary
The AI buildout: why big tech’s record spending is rippling through the whole economy
There’s a number worth paying attention to this year, and it isn’t a stock price or an interest rate. It’s capital expenditures, the money the “Magnificent Seven” tech giants are pouring into building out artificial intelligence (AI) infrastructure, and the scale of it is genuinely historic.
The numbers behind the buildout
As this year’s earnings reports have rolled in, the “Magnificent Seven”—Apple, Microsoft, Alphabet, Amazon, Meta, Nvidia, and Tesla—have collectively guided toward AI-related capital spending that could exceed $700 billion in 2026, up from roughly $400 billion just last year. Some of the individual numbers are striking on their own:
Put together, this represents one of the largest sustained capital spending commitments by a group of companies in corporate history.
Where the money is going and who benefits
This spending isn’t abstract. It’s flowing into physical construction: data centres, power infrastructure, semiconductor fabrication, high-performance chips, and networking equipment. That means the beneficiaries extend well beyond the tech giants themselves.
Chipmakers like Nvidia, Broadcom, and Taiwan Semiconductor are seeing enormous demand for the processors that power AI workloads. Electric utilities are seeing rising demand from the sheer power requirements of large data centres. Construction and industrial companies are benefiting from the physical buildout of these facilities, and memory chip manufacturers are seeing tighter supply and stronger pricing as a result of the demand surge.
A genuine tailwind for the broader economy
This level of spending has real macroeconomic significance. Business investment is one of the core components of economic growth, and AI-related capital spending has become one of the more meaningful contributors to stronger GDP this cycle. It supports construction jobs, manufacturing activity, and demand for electricity and industrial materials—effects that extend well beyond Silicon Valley into communities where these data centres are actually built.
It’s also creating a self-reinforcing cycle in the markets: strong AI-related capital spending has helped drive some of the outsized earnings growth we’ve seen from the tech sector this year, which in turn has helped fuel the broader stock market rally.
The other side of the ledger
Of course, spending on this scale invites a fair question: will it pay off? Investors have grown increasingly attentive to whether the returns on this investment will justify the cost, and some prominent voices have raised concerns about the risk of overbuilding AI infrastructure ahead of demand. None of the Magnificent Seven have fully deployed their allocated 2026 capex yet, which means guidance could still shift if conditions change.
This is a legitimate risk to watch, and it’s one reason diversification remains important even amid an exciting growth story. But it’s also worth noting that companies of this scale don’t commit hundreds of billions of dollars lightly. This level of investment reflects genuine confidence in sustained demand for AI compute over the years ahead.
The bottom line
Whatever your view on where AI ultimately lands, the capital being deployed right now is already having a measurable, positive impact on economic activity—supporting jobs, investment, and growth well beyond the technology sector itself. We’re watching this trend closely as it continues to shape portfolios, and we’re happy to discuss how it factors into your own investment strategy.
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