As Bloomberg News reported Thursday (Jan. 29), the decline is happening as investors shed the stock over fears about the artificial intelligence (AI) market and the company’s ties to OpenAI.
The downturn wiped out around $463 billion in market value from a record reached in September, after the company’s outlook for its cloud unit signaled steep demand for AI. Oracle’s valuation jumped to $933 billion, the report added, making it the 10th most valuable publicly-traded American company at the time.
The report noted that this decline has been boosted by rising concern among investors about AI spending among tech giants without an obvious path to return on investment. There are also worries about the “circular deals” between the unprofitable startup OpenAI and companies like Oracle and Nvidia, Bloomberg added.
“There’s some assumptions built in here about what OpenAI is going to spend and where are they getting that money and, you know, is this really going to happen,” Eric Diton, president and managing director of investor advisory firm Wealth Alliance, told Bloomberg. “Maybe Oracle stock got way ahead of fundamentals and now the market’s saying, alright, show me, I wanna see it.”
The news comes weeks after Oracle was sued by bondholders who claim the company made false and misleading statements in the offering documents for an $18 billion debt sale.
The proposed class action lawsuit includes investors who purchased $18 billion of notes and bonds issued by Oracle in September after the company announced it had landed a $300 billion, five-year contract to supply computing power to OpenAI.
The suit alleges these investors suffered losses when — weeks later — Oracle sought $38 billion of loans to fund data centers to support that agreement. This caused prices to drop and yields to climb as investors perceived greater credit risk, the suit said. Oracle has declined to comment on the litigation.
Writing about the Oracle/OpenAI deal last year, PYMNTS argued it was the most visible example of how the AI boom’s second act is being funded not just by venture capital but also by borrowing, as companies scramble to build the data centers and acquire the chips required to train and operate large language models.
