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Alphabet posted negative free cash flow of $5.9 billion in its latest quarter, the first such shortfall in at least 10 years, after capital spending on AI servers and data centres accelerated sharply. The company projected total capital expenditure for 2026 could reach as high as $205 billion, according to its earnings release, with $45 billion already deployed in the second quarter alone. That outlay split 60 percent toward servers and 40 percent on data centre construction, building on $36 billion of capital expenditure logged in the first quarter. Combined quarterly revenue climbed to $119.8 billion, a 23 percent increase from the same period a year earlier, yet the stock fell about 4 percent in after-hours trading as investors weighed the pace of outlays.
Chief Executive Sundar Pichai told analysts the technological shift toward AI tools still feels like early innings across multiple areas. “What I see with what you can do with frontier capabilities, there is still a lot of work left to do to translate that into experiences for our users,” Pichai said. “So that looks like extraordinary opportunities with extraordinary returns.” Chief Financial Officer Anat Ashkanazi added that demand for AI capacity continues to outpace investment. “As long as we see these attractive opportunities to invest, we will continue to invest,” Ashkanazi stated in the earnings call.
Investor reaction reflected some unease over the scale of planned spending. Rachel Winter, a partner at Killik & Co, noted surprise at the updated guidance of between $195 billion and $205 billion for the year. Winter said the share price drop of around 3.5 percent in after-hours trading pointed to concern about those elevated levels. The results have prompted some coverage to characterise the trend as Google burning through cash with spiralling AI costs.
A Goldman Sachs assessment published in May 2026 projected baseline annual AI capital expenditure across the sector at $765 billion for 2026, rising to $1.6 trillion by 2031 for a cumulative total of roughly $7.6 trillion over the six-year period. The investment bank separately estimated consensus capital spending among leading AI hyperscalers could exceed $527 billion in 2026. McKinsey research cited in industry analysis placed the required outlay for AI-related data centre infrastructure at $5.2 trillion by 2030, driven by demand for 156 gigawatts of specialised capacity.
Alphabet stands among the largest spenders alongside Amazon, Microsoft and Meta, which together plan more than $400 billion in data centre investments for 2026 according to the same McKinsey-linked projections. The outlays reflect a broader industry race to secure compute resources as AI training and inference workloads expand. Power consumption for data centres is forecast to rise 165 percent between 2023 and 2030, Goldman Sachs data show, underscoring infrastructure bottlenecks that have accelerated capital commitments.
Tesla experienced a parallel squeeze, recording negative free cash flow of $1.1 billion in the same period while signalling capital spending as high as $25 billion for the year, more than double 2025 levels. Tesla Chief Financial Officer Vaibhav Taneja described the company as in a big investment cycle that will see further increases over the next three years. The paired results from the two technology groups illustrate how the pursuit of next-generation AI capabilities has shifted cash-flow profiles even at companies with robust revenue growth.
