Big Tech’s AI Spending Surge Drains Cash as Alphabet Shares Slide 7%

Big Tech’s race to dominate artificial intelligence is starting to pressure cash flow. Revenue tied to AI is rising quickly, but spending on data centers, semiconductors and power infrastructure is climbing even faster.

Alphabet shares fell $24.40, or 7.13%, to $317.69 on the New York Stock Exchange on July 23 after the company released second-quarter results. The earnings report itself was not weak. Revenue sustained double-digit growth, while Google Cloud sales surged 82% from a year earlier. Demand for AI infrastructure and AI solutions drove that growth.

The problem was cash flow. Alphabet posted a $5.9 billion free-cash-flow deficit in the second quarter as spending on AI infrastructure surged. Cash outflows for investment exceeded the cash it generated. Alphabet also raised its capital spending outlook for this year to $195 billion to $205 billion.

That is where Big Tech’s dilemma begins. AI is generating revenue. Cloud usage is rising, and companies are adopting AI more quickly. But operating AI services requires massive data centers, high-performance chips and power facilities. Even as sales increase, investment spending is rising faster.

Tesla showed a similar pattern. Second-quarter capital expenditures jumped 142% from a year earlier to $5.8 billion. Free cash flow swung to a deficit of $1.1 billion. Tesla is expanding from an electric-vehicle maker into robotaxis, humanoid robots and AI infrastructure, but those investment costs are weighing on near-term performance.

Oracle also illustrates the burden of AI spending. In fiscal 2026, the company posted strong cloud revenue growth but a free-cash-flow deficit of $23.7 billion. Expanded investment in AI data centers increased cash outflows. Its order backlog and cloud growth prospects improved, but investors have started asking not only how much money these companies can make, but how much they must spend to make it.

In the past, Big Tech could fund new businesses with strong cash generation. Cash from search, software, advertising and e-commerce was channeled into the next growth engine. The AI race looks different. The scale of investment is much larger, and the payback period is longer. Some companies are turning to debt sales and stock issuance to finance those investments.

Investors are divided. Bulls see AI infrastructure spending as a necessary cost of long-term growth. By that logic, companies that fail to pour money into data centers and semiconductors now risk falling behind in the AI market later. Demand for AI is already showing up in cloud revenue and growth in enterprise services.

More cautious investors worry that spending is rising faster than monetization. As capital expenditures increase, depreciation and operating costs follow. Even if AI revenue keeps growing, cash-flow improvement may be delayed if that revenue fails to outpace investment costs, operating expenses and depreciation.

Lee Song-ryeol, Hankyung.com reporter yisr0203@hankyung.com