An AI Valuation Correction Is Coming and It Will Be Brutal On All Of US

An AI Valuation Correction Is Coming and It Will Be Brutal On All Of US

Most of us have been hyper-focused on the potential risks and rewards of AI over the past 12 months. The fear of cascading job losses has given way to tales of evangelical followers that dumped entire customer service departments only to hire them back after miserable customer backlashes and operational disasters (yes, Starbucks, SAP, IBM and Panera Bread – we’re talking about you). Some anticipated job losses have occurred – but only in specific sectors, concentrated mainly in IT. Having just returned from a long break in Seattle the job loss among programmers has been profound and have impacted the residential and commercial real estate markets. BUT. The Big Kahuna fear that seems to get much less play in the press, and will have the greatest impact on us all, is the looming debt crisis unfolding that has been created by this overhyped gold rush of expectations.

1. The Deliberate Distortions of AI Hype Hugging Face is the most recent “disaster” that has been exploited to cause fear in the general public and ecstatic rapture in the economic markets. Fable 5 started the dance when it was pulled off the market by our government as a clear and present danger until Dario Amodei could convince the administration that taking Anthropic to the woodshed was opening the door to a Chinese victory. Anthropic’s refusal to kowtow to the military combined with their ability to hack any institution was marketing gold and continues to be. Don’t get me wrong, I love what Fable 5 can do but have learned daily why it is not yet ready for a prime-time overthrow of economic and employment markets. The hype has been strategic from the likes of Sam Altman and others. Let’s take a look at what the self-proclaimed soothsayer of AI has to say about all of this. See if you can guess who it is: “AI is the fastest advancing technology that I've ever seen of any kind, and I've seen a lot of technology. You know barely a week goes by without some new announcement, and if you look at the amount of AI hardware, the computers coming online that are dedicated to AI, that is increasing what looks like at least by a factor of 10 every year, if not every 6 to nine months. So when you combine the hardware coming online really an order of magnitude increase every you know—call it at least every nine months—and many, many software breakthroughs, if you look at that curve it looks insane. My guess is that we'll have AI that is smarter than any one human probably around the end of next year, and then AI, the total amount of sort of sentient compute of AI, I think will probably exceed all humans in 5 years.”

That was our very own “I know everything about government” wrecking ball Elon Musk and the man who predicts all great things come forth in “the next five years” who made this statement 2.5 years ago. He just finished addressing the G20 Innovation Summit where he promised an increase in world GDP of 30% ($30 trillion) in two years and urged leaders to institute stripped down regulations for the AI industry to be “default legal” measured by whatever the industry needs to do to be successful. Constituents be damned. His SpaceX IPO has already paid off initial investors $billions at the expense of virtually anyone who is invested in a pension fund and their total addressable market valuation in the prospectus was $28.5 Trillion (that’s Trillion with a “T”). They said this both with a straight face and in print. He’s a real peach, and he and his ilk are leading us off an economic cliff.

At a time when our national debt has increased to $40 trillion, our Secretary of the Treasury has to play shell games to keep our bond market from crashing and our Vice President has stated that it is time for the US dollar to no longer be the world’s primary reserve currency, we are hiding what is perhaps the biggest debt crisis in our history looming on the horizon. While the early AI boom was funded directly out of the deep cash reserves of Big Tech "hyperscalers" (like Microsoft, Google, Meta, and Amazon), capital spending demands have drastically outstripped corporate cash flow. To fund the relentless acquisition of GPUs, massive data center construction, and specialized power infrastructure, tech companies and developers have turned en masse to private credit, specialized project debt, and shadow banking. Key Drivers of the AI Private Debt Explosion

• Off-Balance-Sheet Expansion: Hyperscalers are increasingly avoiding direct corporate debt by leasing facilities and chips through special-purpose vehicles (SPVs). Private credit funds, asset managers (e.g., Blackstone, Apollo, Ares), and real estate investment trusts (REITs) are issuing hundreds of billions of dollars in private loans to non-bank developers to build out data centers. • GPU & Infrastructure Securitization: Private debt funds are now underwriting unconventional loans collateralized directly by AI chips (GPUs) and specialized server rigs, treating them like leased aircraft or heavy machinery. • Concentration Risk: What appears to be a diversified private credit portfolio across real estate, infrastructure, energy, and tech is, in reality, a single giant macro-bet on generative AI cash flows. Why Economists & Regulators are Worried

a. Massive Overcapacity & Valuation Mismatches Global central banks and financial stability watchdogs (including the Financial Stability Board) have flagged growing concern over "stretched valuations" and speculative debt accumulation. If commercial enterprise adoption of generative AI fails to generate the multi-trillion-dollar revenues required to service these loans, developers and private credit vehicles face widespread default risk. b. Rapid Technological Obsolescence Unlike traditional infrastructure (like toll roads or power plants) that amortizes over 30+ years, AI hardware depreciates at a staggering rate. A multi-billion-dollar pool of private debt secured by current-generation GPU clusters risks losing collateral value within 3 to 5 years as next-generation chips render existing hardware obsolete. c. Power & Grid Execution Bottlenecks Data centers cannot generate revenue without massive electricity access. Dozens of heavily leveraged data-center projects have faced stalled completions due to localized power grid bottlenecks, utility interconnection delays, and natural gas permitting hurdles. Delayed operations lead to missed lease payment schedules, putting debt service at risk. d. Opacity in Shadow Banking Unlike public bonds or bank loans, private credit transactions do not require public disclosures or strict capital reserve requirements. Because major pension funds, university endowments, and insurance companies are heavy investors in these private debt funds, defaults or sharp markdowns would directly ripple into institutional portfolios and retirement systems. e. Disruption from Neocloud Counterparties A significant portion of private borrowing is tied to tier-2 "neocloud" startups and middle-tier AI labs that lack the multi-billion-dollar balance sheets of established tech titans. If these venture-backed startups burn through their capital reserves without reaching profitability, their private debt lenders will be left holding underperforming or defaulted assets.

2. CMBS Debt Exposure & Structural Refinancing Risks: It’s Real

Just when everyone was hoping for a settling upswing in the real estate market, this giant shoe drops. Commercial Mortgage-Backed Securities (CMBS) represent a critical vulnerability WHEN the revenue projections of the AI sector fail to materialize. The concentration of capital into AI infrastructure has fundamentally reshaped the underlying collateral mix within CMBS pools, introducing unique risks to both single-asset and multi-borrower debt structures. Single-Asset Single-Borrower (SASB) Data Center Concentration The rapid expansion of high-performance compute requirements has spurred an unprecedented wave of data center construction. To finance these capital-intensive, multi-billion-dollar developments, sponsors have relied heavily on Single-Asset Single-Borrower (SASB) CMBS and specialized Asset-Backed Securities (ABS). • High Loan-to-Cost (LTC) Ratios: Facilities are frequently debt-financed at leverage levels reaching 90% to 95% LTC, predicated on long-term lease commitments from hyperscalers and venture-backed "neocloud" providers. • Tenant Concentration Risk: Unlike traditional diversified office or retail CMBS, data center SASB structures rely on a small pool of high-tech tenants. If non-profitable AI firms default on lease obligations or hyperscalers scale back capital expenditures, debt service coverage ratios (DSCR) for these issuance pools will drop below 1.0x. • Power Grid Interconnection Bottlenecks: Physical infrastructure limitations—such as four-year utility interconnection queues—prevent delayed data center developments from generating cash flow, raising the immediate risk of pre-construction debt defaults. The Looming Refinancing Cliff CMBS issuances in the tech and data center sectors operate on relatively short maturity schedules, often structured with 5-year maturities or 3-to-5-year Anticipated Repayment Dates (ARDs). [2021-2024 Low-Rate CMBS Issuance] ---> [2026-2029 Refinancing Cliff] ---> [Valuation & Yield Shock] As these bonds reach their ARD or maturity dates: a. Higher Cost of Debt: Refinancing must take place in an elevated interest rate environment, significantly increasing debt service obligations. 2. Depreciated Collateral Value: If AI equity valuations collapse, underlying property appraisals for specialized data facilities and tech-heavy office properties will drop. Borrowers will face severe equity gaps, rendering traditional refinancing unfeasible without substantial capital injections. 3. Maturity Default Cascades: Failure to roll over or execute exit financing will force special servicers to extend loans under distressed terms or foreclose on specialized assets that cannot easily be re-tenanted for traditional commercial uses. Contagion across Office CMBS Issuances While traditional office CMBS has struggled with remote-work vacancy rates, major tech hubs rely heavily on AI startups to absorb prime Class-A space. In cities like San Francisco, AI firms have accounted for up to a quarter of new office lease volume. A contraction in AI venture funding will remove this marginal buyer, accelerating delinquency rates across legacy office CMBS pools and expanding distressed asset inventories held by special servicers. 3. Transmission Mechanisms to Private Credit and Broader Markets The risks embedded within CMBS structures interact directly with non-bank financial intermediaries, expanding the overall impact of a potential tech valuation adjustment:

[AI Valuation Adjustment] leads to - [Hyperscaler Capex Reductions & Lease Terminations] leads to - [Data Center & Tech Office CMBS Delinquencies] leads to - [Tranche Downgrades & Private Credit Default Spreads] leads to - [Bank Balance Sheet Impairment & Credit Contraction]

Private Debt & GPU-Collateralized Structures

Beyond public CMBS markets, millions of specialized compute hardware units and physical hosting sites are financed via private credit funds, Business Development Companies (BDCs), and hardware-collateralized loans. Unprofitable AI software companies depend on continuous equity infusions to service high-yield private loans. An equity contraction would trigger immediate default cascades across software-focused private credit portfolios. Institutional Contagion & Banking System Drag Losses in CMBS and private credit extend beyond specialized funds to impact institutional balance sheets: • Regional Banks: Regional financial institutions holding legacy commercial real estate loans face compounded exposure through investments in debt tranches and direct local lending to technology infrastructure projects. • Insurance & Pension Funds: Institutional investors seeking yields have increased their exposure to top-tier CMBS tranches and private debt funds, exposing long-term capital pools to rating downgrades and mark-to-market losses. • Macroeconomic Credit Tightening: As losses materialize across structured debt products, financial institutions will enforce stricter underwriting criteria across all corporate lending, turning a sector-specific correction into a broader credit crunch. 4. Conclusion & Structural Realities

The real threat from AI is not the expected job losses, it’s not that fear of world domination, it’s not the dumbing down of our educational systems. The real threat looms from the snake-oil salesman of Silicon Valley that have built an unsustainable mountain of debt that once again will be paid for by the taxpayer. The aggressive market positioning of AI capabilities has created a gap between speculative valuations and real-world economic output. By linking commercial real estate financing, CMBS debt structures, and private credit to optimistic performance targets, the market has built up concentrated exposure to tech sentiment and another significant downturn is coming. Translation: Wall Street, Politicians, and Silicon Valley bet the farm and American taxpayers are about to wake up to a bailout that could make 2008 look like a PayDay loan. We are discussing how this will impact businesses specifically with individual clients. If you are interested in a more direct discussion about the impacts on your industry I would be happy to speak to you further.