Google is structuring a multibillion-dollar financing arrangement with Broadcom, Apollo, Blackstone, and Morgan Stanley to supply Anthropic with AI chips and data centers while removing most of the financial risk from its own balance sheet. The deal channels hardware and infrastructure to the AI startup while keeping Google's exposure limited.
The arrangement leaves approximately $200 billion in contracts contingent on Anthropic's sustained growth and its ability to meet lease obligations. This financing model allows Google to maintain its investment in Anthropic, a competitor to its own AI efforts that Google has already backed with billions, without consolidating the associated liabilities on its financial statements.
The structure reflects how major tech companies are managing the enormous capital requirements of AI infrastructure development. Rather than directly purchasing and owning the chips and data centers Anthropic needs, Google partnered with financial institutions and hardware suppliers to distribute the risk. Broadcom manufactures the processors, while Apollo and Blackstone provide capital infrastructure through lease arrangements. Morgan Stanley structured the overall transaction.
This approach lets Google support Anthropic's operations while keeping debt obligations off its balance sheet, a technique common in project financing and infrastructure deals. However, the arrangement creates a dependency chain. If Anthropic fails to generate sufficient revenue or defaults on lease payments, the financial burden falls on the structured entities rather than Google directly. The $200 billion commitment underscores the scale of capital required to compete in AI development, where training and inference infrastructure costs have become the primary expense driver.
For Anthropic, the arrangement provides access to cutting-edge hardware without negotiating directly with chipmakers or data center operators. For the financial partners, it offers returns tied to Anthropic's success. For Google, it maintains leverage over a key AI competitor while preserving balance sheet flexibility. The structure highlights how traditional finance institutions are embedding themselves into AI infrastructure, effectively betting on startup growth and operational viability.