Oracle Corporation may be contemplating significant internal restructuring, including job reductions ranging between 20,000 and 30,000 roles, alongside the potential sale of its Cerner subsidiary, according to a recent research note from TD Cowen. This analysis stems from increasing skepticism among equity and debt investors about Oracle’s capacity to finance its ambitious, multi-year data center construction program.
The core of the financing challenge revolves around the massive capital expenditure required to fulfill large AI contracts, particularly the five-year, $300 billion agreement with OpenAI. TD Cowen estimates this single commitment will necessitate approximately $156 billion in capital spending, requiring roughly 3 million GPUs and associated IT infrastructure.
TD Cowen noted that investor confidence has waned, evidenced by widening credit default swap (CDS) spreads for Oracle, signaling a perceived increase in default risk. The cost of five-year CDS instruments insuring against Oracle defaults reportedly tripled in the latter months of last year, indicating mounting financial scrutiny.
Further complicating matters, the report claims that US banks have become hesitant to underwrite lending for Oracle’s data center projects, and private leasing operators are also struggling to secure necessary financing. While Asian banks appear less concerned about Oracle’s risk profile, the hesitation from US institutions casts doubt on the viability of the current building trajectory.
To generate necessary liquidity, the analysts suggest that workforce reduction could free up between $8 billion and $10 billion in annual cash flow. Additionally, divesting Cerner, which Oracle acquired for $28.3 billion in 2022, presents another avenue for asset realization to support capital needs.
Oracle is reportedly evaluating multiple financing strategies, including vendor financing options, as it addresses investor queries about its substantial $523 billion total commitment across AI infrastructure projects for Meta and Nvidia as well. The company is also tightening payment terms, now requiring 40% upfront deposits from most customers, excluding major AI partners.
These potential cost-saving and asset-disposal measures underscore the immense financial pressure associated with executing hyperscale AI infrastructure projects. The firm's ability to maintain momentum on these critical build-outs hinges on successfully navigating this current financing environment.
