American tech giants are heavily investing in artificial intelligence (AI), allocating billions of dollars to data centers and model development, but investor reactions have been mixed. While these companies anticipate substantial profits from their AI ventures, the massive expenditures raise concerns among some analysts about potential financial risks and inflated stock prices.

Microsoft and Meta, despite their AI investments, experienced a drop in stock prices following their announcements, with Meta’s shares falling nearly 10%. Investors are questioning the scale of the financial commitments, particularly in Meta’s case, where AI spending accounted for over two-thirds of the company’s income for the quarter. Similarly, Microsoft devoted over three-quarters of its revenue to AI-related initiatives and plans to double its data center capacity.

Alphabet, on the other hand, saw its stock price rise by 7% after reporting a quarterly turnover of $100 billion and investing about half of its available income in AI. This more conservative approach seemed to inspire greater confidence among investors.

The tech companies are driving up the stock prices of related businesses, such as Nvidia and ASML. Nvidia recently surpassed a valuation of $5 trillion.

The actual earnings generated by AI services remain somewhat unclear. Google CEO Sundar Pichai mentioned billions of dollars in quarterly revenue from AI services for businesses.

Concerns have also been raised about circular investments within the AI sector. For instance, Nvidia’s investment in OpenAI, which relies on Nvidia’s chips, and Microsoft’s involvement as a major shareholder in OpenAI and a customer of Nvidia, have led to worries about artificially inflated stock prices and a potential bubble. Google’s agreement to supply computing power to Meta, despite both companies competing in the chatbot market, adds to these concerns.

Despite these reservations, investor optimism remains high, supported by record-breaking stock prices. The general sentiment is that significant investment and long-term commitment are necessary to succeed in the AI race, presenting both opportunities and potential risks.