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Source document· March 7, 2026

Google, Meta and the AI ‘hyperscalers’ are on a $1 trillion borrowing binge after years of printing cash. Here’s why Big Tech’s pivot to debt matters

View original at finance.yahoo.com
Google, Meta and the AI ‘hyperscalers’ are on a $1 trillion borrowing binge after years of printing cash. Here’s why Big Tech’s pivot to debt matters Almost every major capital spending boom during the past 200 years has ended in bankruptcies, consolidations, and tears—but also wins for the victors…
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  • The NC pension system expects the wave of issuances to be well absorbed in 2026, much like it was in 2025

    80% confidence
  • Oracle pledged to raise $45 billion to $50 billion more this year, split between debt issuance and equity

    80% confidence
  • Any kind of large capital expenditure cycle that we have seen over history at some point leads to the risk of overinvestment

    80% confidence
  • The fact that investors are comfortable taking down 30-and 40-year debt, in some cases 100-year debt, certainly suggests that investors are very comfortable that this is a balanced risk-reward opportunity

    80% confidence
  • There may be some form of over investment over the next two years that leads to a correction or a growth slowdown

    80% confidence
  • The yields for the hyperscalers' bonds are near 5%, which is attractive on its own before factoring in the strong balance sheets and corporate profitability

    80% confidence
  • The issue for us is the spreads are very, very tight. And as you go longer, there's not much of a yield pickup at all

    80% confidence
  • It's different this time, which is obviously a bit of a cliché, but for now at least, this is being approached quite prudently

    80% confidence
  • We are incorporating these obligations and making those adjustments, particularly given the size of the leases and their growth potential. Because ultimately, in our mind, these are commitments that they have to honor. We have to effectively view them as debt when we're reviewing the credit quality of these companies

    80% confidence
  • Every company will be quite different. There will be winners and losers in this environment

    80% confidence
  • On-balance sheet debt as well as economic debt related to not-yet-begun leases should be on investors' radar as they think about risk

    80% confidence
  • You only find out after the fact. If you start to see it ahead of time, then others see it too, and investment starts to slow down on its own

    80% confidence
  • In an asset-light model, you tend to have higher equity multiples, and in an asset-rich model, you have multiples that are a little lower

    80% confidence
What we know · the intelligence behind this page
Live from the substrate
What we're seeing
AI Moves Into Devices, Security and Platforms: Physical AI Data, On-Device Compute and Agent Governance Drive a Late-October Product Wave
In late October 2026, vendors across hardware, enterprise software and security launched products built around AI moving out of the cloud and into devices, workflows and physical systems. Examples include NVIDIA RTX Spark laptops with Adobe, ASUS and Windows support for local and hybrid AI, and Harvest Praxis and Encord on embodied or physical AI. Enterprise software and security vendors (Salesforce–Braze, Fortinet, ServiceNow, Cisco, Intuit) are consolidating AI-driven customer data, adding inline AI security and agent governance, and embedding AI in financial and accounting workflows. The finance link is indirect: it rests on M&A, fintech-adjacent AI tooling and the capital flowing into physical AI. No regulatory driver appears in the facts.
Our read on the data ›
Signals we're tracking
EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
Patterns we're watching ›
Where sources disagree
Ford Motor Company
Both facts give cash for Ford Motor Company at the same point in time (2025-12-31; FY 2025 year-end and Q4 2025 year-end are the same date). Both are labelled USD, but the values are 23,356,000,000 and 23.356, which cannot both be true in USD. The two numbers agree once the second is read as billions (23.356 bn = 23,356,000,000), so the economic content is consistent and the conflict is a unit/scale error in the Q4 2025 record. The period is not the reason for the conflict: a Q4 and an FY figure at the same year-end date should match.
We flag conflicts openly ›
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