{"id":68048,"date":"2026-02-12T06:59:01","date_gmt":"2026-02-12T06:59:01","guid":{"rendered":"https:\/\/crowdfundjunction.com\/blog\/inside-big-techs-700b-ai-spend-in-2026-bullish-leaders-split-markets\/"},"modified":"2026-02-12T06:59:01","modified_gmt":"2026-02-12T06:59:01","slug":"inside-big-techs-700b-ai-spend-in-2026-bullish-leaders-split-markets","status":"publish","type":"post","link":"https:\/\/crowdfundjunction.com\/blog\/inside-big-techs-700b-ai-spend-in-2026-bullish-leaders-split-markets\/","title":{"rendered":"Inside Big Tech\u2019s $700B AI spend in 2026: bullish leaders, split markets"},"content":{"rendered":"

(Originally posted on : Microsoft News, Latest Stories & Analysis | Invezz )<\/b>
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The latest earnings season has revealed a dramatic turning point in the global technology industry.<\/p>\n

America\u2019s largest technology companies have announced plans to spend more than $700 billion on artificial intelligence-related capital expenditure in 2026, underlining how fiercely they are competing to dominate the infrastructure of the AI era.<\/p>\n

Microsoft, Meta Platforms, Alphabet\u2019s Google, Amazon and Oracle are collectively ramping up investments in data centres, cloud platforms and AI models as demand for computing power surges.<\/p>\n

The magnitude of the numbers is striking.<\/p>\n

Combined AI-related spending by these companies is set to exceed $700 billion in 2026, surpassing the expected size of Israel\u2019s entire economy, projected at around $610 billion.<\/p>\n

Meta, Amazon and Alphabet alone account for more than $500 billion of the total, with Amazon\u2019s plan to invest $200 billion<\/a>\u2014almost 60% higher than last year and far above Wall Street estimates\u2014emerging as the most startling figure.<\/p>\n

Markets split over Big Tech\u2019s spending surge<\/h2>\n


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Investor reactions have varied sharply across companies, revealing how sensitive markets have become to the balance between growth and capital discipline.<\/p>\n

Amazon\u2019s shares plunged more than 10% in extended trading after it reported mixed quarterly earnings and unveiled its aggressive spending forecast.<\/p>\n

The stock remained under pressure in pre-market trading the following day, reflecting concerns that the scale of investment could weigh on near-term profitability.<\/p>\n

Alphabet also faced market turbulence<\/a> after raising its projected 2026 spending to between $175 billion and $185 billion, nearly double its earlier estimate of over $90 billion.<\/p>\n

Despite beating earnings expectations, its stock fell about 8% intraday before stabilising by the close<\/p>\n

Meta, by contrast, was rewarded by investors after it nearly doubled its AI-related capital expenditure forecast to between $115 billion and $135 billion.<\/p>\n

Its stock surged as much as 10% in after-hours trading following its results, suggesting that markets were more comfortable with its strategic narrative.<\/p>\n

Microsoft\u2019s experience was less forgiving.<\/p>\n

The company reported quarterly capital expenditure of $37.5 billion, up about 65% from a year earlier, and signalled continued heavy spending on AI infrastructure.<\/p>\n

Investors focused instead on Azure\u2019s growth, which came in slightly below expectations.<\/p>\n

The stock fell around 10% in after-hours trading, even though Microsoft indicated that capital expenditure could decline in the current quarter.<\/p>\n

Oracle also faced investor scepticism, punished both for disappointing results and for its plan to increase capital expenditure to $50 billion, a 40% rise largely aimed at expanding data centre capacity.<\/p>\n

Analysts say these reactions reflect a broader shift in market sentiment.<\/p>\n

\u201cA recurring theme is emerging: both Alphabet and Amazon delivered strong underlying business performance, driven by better-than-expected growth in cloud. But that hasn\u2019t been enough to distract markets from their ballooning capital investment plans,\u201d said Aarin Chiekrie, equity analyst at Hargreaves Lansdown.<\/p>\n

Neil Wilson, UK investor strategist at Saxo, echoed those concerns:<\/p>\n

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Fresh AI bubble fears are surfacing after big tech companies massively increased their capex spending for the year \u2013 about $650 billion across the four hyperscalers who have reported earnings over the last fortnight.<\/p>\n<\/blockquote>\n

The cloud question<\/h2>\n


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For some of the companies, at the heart of the debate lies the cloud business, which has become the primary battleground for monetising AI.<\/p>\n

Amazon chief executive Andrew Jassy has sought to reassure investors that the company\u2019s spending is deliberate and tied to long-term returns.<\/p>\n

He told analysts that Amazon plans to spend $200 billion in 2026, with most of the investment directed toward AWS.<\/p>\n

Demand for AWS is so strong that the company is monetising capacity as fast as it can install it, Jassy said.<\/p>\n

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We have deep experience in understanding demand signals in the AWS business and then turning that capacity into a strong return on invested capital.<\/p>\n<\/blockquote>\n

On an earnings call, Jassy argued that the spending is intentional and directly linked to long-term value creation.<\/p>\n

He said AWS demand is accelerating, large enterprise and government contracts are expanding, and Amazon is monetising AI through services such as Bedrock as quickly as infrastructure allows.<\/p>\n

Several analysts have backed this view.<\/p>\n

Morgan Stanley said Amazon\u2019s strength in AWS growth justifies its spending, while Citigroup argued that, \u201cgiven the demand trends and potential future opportunity of AI, we believe this investment is the right thing to do in the long term.\u201d<\/p>\n

MoffettNathanson also expressed confidence in Amazon\u2019s strategy but warned that \u201cthe margin of error is shrinking.\u201d<\/p>\n

The competitive dynamics of the cloud market are also evolving, adding another layer of complexity to the AI spending debate.<\/p>\n

D.A. Davidson analyst Gil Luria<\/a> warned that Amazon\u2019s leadership in cloud computing is under pressure, downgrading the stock and lowering his price target.<\/p>\n

\u201cWhile AWS accelerated slightly to 24 percent growth, Google Cloud accelerated to 48 percent growth and Azure grew an allocation-constrained 39 percent,\u201d he said.<\/p>\n

Luria argued that Amazon\u2019s lack of a strong position with a frontier AI lab is hurting its competitive standing, while Google\u2019s in-house TPU chips are outperforming Amazon\u2019s Trainium, \u201calso contributing to customer preference.\u201d<\/p>\n

These shifts highlight how AI is reshaping not just technology products but also the hierarchy of cloud providers.<\/p>\n

Alphabet\u2019s Gemini, AI Overviews, Cloud brings gains<\/h2>\n


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Alphabet executives have emphasised that their AI investments are already translating into tangible benefits across the business.<\/p>\n

Google users are increasingly using AI-powered search features and spending more time on the company\u2019s platforms, while enterprise customers are adopting Google Cloud\u2019s AI capabilities and expanding their use of its product portfolio.<\/p>\n

\u201cIt\u2019s already delivering results across the business,\u201d chief financial officer Anat Ashkenazi said during an earnings call.<\/p>\n

At the same time, Alphabet warned that overall expenses in 2026 are expected to \u201cmeaningfully increase\u201d due to higher depreciation and energy costs associated with data centres.<\/p>\n

Wall Street analysts have pointed to cloud growth as evidence that Alphabet is successfully monetising its AI strategy.<\/p>\n

The company\u2019s cloud backlog grew 55% quarter-on-quarter to $240 billion.<\/p>\n

\u201cCloud revenue growth in 4Q25 was a standout, driven by accelerating demand, improving profitability, and a backlog that implies a multi-year revenue runway,\u201d Needham analyst Laura Martin wrote, raising her price target on the stock and maintaining a buy rating.<\/p>\n

Alphabet\u2019s AI strategy has been anchored by its Gemini model, which has been integrated across search, YouTube and cloud services.<\/p>\n

Gemini-powered AI Overviews are increasing user engagement, while YouTube has benefited from improved content discovery driven by AI.<\/p>\n

Google Search revenue rose 17% to $63 billion in the quarter, accounting for more than half of Alphabet\u2019s total revenue.<\/p>\n

YouTube\u2019s sales increased 9 percent to $11.4 billion, with annual revenue surpassing $60 billion.<\/p>\n

Google Cloud sales climbed 48% to $17.7 billion, although the company continues to face a backlog of potential customers.<\/p>\n

Microsoft\u2019s balancing act<\/h2>\n


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Microsoft has framed its AI investments as part of a long-term transformation of its business, even as investors scrutinise the gap between spending and growth.<\/p>\n

The company acknowledged that Azure\u2019s performance was influenced by internal capacity decisions, saying cloud results could have been stronger if more data centre infrastructure had been allocated to external customers rather than internal needs.<\/p>\n

\u201cWe are only at the beginning phases of AI diffusion and already Microsoft has built an AI business that is larger than some of our biggest franchises,\u201d said Satya Nadella, chairman and chief executive officer of Microsoft.<\/p>\n

\u201cWe are pushing the frontier across our entire AI stack to drive new value for our customers and partners.\u201d<\/p>\n

Amy Hood, Microsoft\u2019s chief financial officer, highlighted the scale of demand for its cloud services, saying:<\/p>\n

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Microsoft Cloud revenue crossed $50 billion this quarter, reflecting the strong demand for our portfolio of services. We exceeded expectations across revenue, operating income, and earnings per share.<\/p>\n<\/blockquote>\n

Bubble fears versus structural transformation<\/h2>\n


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The unprecedented scale of Big Tech\u2019s spending has revived comparisons with previous technology booms, from the dot-com era to the rise of mobile computing.<\/p>\n

Sceptics argue that the industry risks overbuilding infrastructure in anticipation of demand that may take years to fully materialise.<\/p>\n

Supporters counter that AI represents a structural transformation of the economy, making such investments inevitable rather than speculative.<\/p>\n

What is clear is that the rules of investor evaluation are changing.<\/p>\n

Markets are no longer satisfied with strong earnings alone; they are demanding evidence that massive capital expenditure will translate into sustainable growth and competitive advantage.<\/p>\n<\/p><\/div>\n

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