Borrowed Time in Big Tech
The market loves the story of unstoppable tech. It loves the AI narrative, the “future is here” euphoria, and the trillion-dollar valuations. What it conveniently ignores is that the greatest technology boom of our time is being propped up not by innovation, but by debt - cheap, complex, and increasingly desperate debt. Beneath the glowing charts lies something far less futuristic: distressed companies, Ponzi-like private lending schemes, and the quiet, familiar echoes of 2007–2008.
Debt Masquerading as Growth
Tech firms have raised $157 billion in bond debt this year - a 70% increase
over 2024 and up 134% from 2023. Total sector debt now stands at $1.35 trillion,
quadruple what it was a decade ago. The five U.S. giants - Amazon, Microsoft,
Apple, Meta, and Alphabet - owe $457 billion combined. Oracle, freshly crowned
as one of the AI winners, watched its stock jump 54% in 2025, then immediately
issued $18 billion in new bonds, with more debt on the way. There is an
unmistakable pairing: record valuations and record borrowing always arrive
together, like a matched set.
The AI
boom is not being financed by profits. It is being financed by leverage - through
AI-themed junk bonds, private credit deals, leverage-linked ABS instruments,
and loans backed by theoretical future income from data centers and cloud
infrastructure. It looks modern but behaves prehistoric.
The Revenue That Never Arrives
Less than 5% of AI products currently generate real value. Meanwhile,
debt-funded spending on chips, data centers, and “AI infrastructure” continues
to accelerate far beyond actual earnings. The mismatch between investment speed
and revenue reality is no longer subtle; it mirrors the behavior of markets
right before the dot-com crash and the 2008 collapse. The common trait is
denial.
Receivables,
Fiction, and the Familiar Smell of Fraud
One of the most reliable signs of late-stage financial stress is abuse of receivables
financing - where companies use unpaid invoices to secure new loans. When those
invoices are inflated, misrepresented, hidden, or simply fabricated, the entire
structure becomes fraudulent. Broadband Telecom and Bridgevoice collapsed in
2025 for that reason: the invoices simply didn’t exist.
Now the problem is systemic. These risky loans are being packaged, securitized,
and sold into the private credit market - just like subprime mortgages before
2008. Contagion is built into the design.
How to Mitigate the Risk Before It Detonates
For the
U.S. Government:
×
Stop
subsidizing moral hazard disguised as innovation.
×
Demand
transparent reporting on AI-linked debt structures, especially ABS tied to data
center revenues and cloud contracts.
×
Establish
minimum disclosure rules for private credit vehicles financing AI and
infrastructure plays.
×
Track
leverage concentration in strategic supply chains - AI chips, cloud hosting,
hyperscale computing - before it becomes systemic, not after.
For
Corporations and Institutional Investors:
×
Stress-test
portfolios for overexposure to debt-fueled AI infrastructure - especially where
revenue projections are hypothetical or based on “expected adoption curves.”
×
Separate
real AI utility (productivity gains, proprietary models, defensible IP) from
speculative AI theater (storytelling wrapped in GPU invoices).
×
Demand
audited proof of revenue - not just GPU
burn rate, valuation size, or “runway compression.”
×
Avoid
receivables-based financing structures in the AI sector unless invoice chains
are verifiable, audited, and traceable.
For
Individuals and Private Investors:
×
Don’t
confuse “AI-themed” with “AI-profitable.” Most startups are GPU resellers
wearing software costumes.
×
Be
cautious with AI-linked ETFs, structured products, and private credit offerings
marketed as “next-generation tech fixed income.”
×
Do
not buy the story. Buy the cash flow.
Conclusion
Every major tech boom claims it is different. Every bubble insists it is built
on “fundamentals.” Every cycle believes the rules have changed.
And
every time, the numbers disagree.
