INTRODUCTION
This article is Part III of a three-part series on AI Data Centers. These articles are a response to a reader who asked these three questions:
1. Which public issues are impacting AI Data Centers?
2. A few of us believe their expansion is limited by physics. Is that so?
3. And how long will this last? Is an AI bubble forming?
In response, I am answering in three parts, as follows:
· Part III: AI Bubble
COMPLIANCE SOLUTIONS
AI POLICY PROGRAM FOR MORTGAGE BANKING™
Policies and procedures for artificial intelligence related to mortgage banking compliance administration, mortgage loan origination compliance, mortgage servicing compliance, and industry best practices—including, but not limited to, applicable federal and state banking and consumer lending laws. Currently, it consists of nine policies, with more planned.
AI FOR MORTGAGE LOAN ORIGINATION - SALES MANUAL
The Sales Manual provides 9 chapters covering the full AI-powered origination funnel in a 90-day implementation roadmap, with clear team roles and fair lending, FCRA, and advertising compliance guidance built into every chapter. It includes sample AI prompts, an ROI tracking framework, and a compliance glossary.
RESPONSE
AI BUBBLE: Promises, Panics, and Economics
I want to commence this discussion with probably the most famous quote describing the Dutch tulip bubble (also known as the Tulip Mania). The quote comes from Scottish journalist Charles Mackay in his 1841 book, Extraordinary Popular Delusions and the Madness of Crowds:
"A golden bait
hung temptingly out before the people, and one after the other,
they rushed to the tulip-marts, like flies around a honey-pot."
Parts of this article are technical. If that's not for you, skip ahead to the What to Watch and Conclusion sections at the end.
Are data centers a symptom of an AI bubble?
Short answer: data centers show the classic financing signs of a bubble – spending racing ahead of revenue, a shift from cash to debt, off-balance-sheet structures, and circular deals – but not yet the classic demand sign of one, because the capacity being built is still being used. In layperson's terms, the industry is building the plane while flying it.
Or, a better metaphor: this is a case where the grasp exceeds the reach!
The poet Robert Browning wrote, "a man's reach should exceed his grasp" – we should aim beyond what we can already hold. Here, it is the reverse. The industry has already grabbed – committed, signed, and borrowed for – more than its revenue can reach today.
So, whether this becomes a bubble depends on one question: does AI revenue close the gap before the debt comes due?
The spending has outrun the spenders' own cash
The five hyperscalers – Microsoft, Amazon, Alphabet, Meta, and Oracle – are the giant cloud companies building most of this capacity. Their capital expenditure (capex), meaning spending on buildings, chips, and equipment, rose from about $256 billion in 2024 to $443 billion in 2025, and is projected at $602 billion in 2026. Later estimates run higher: the Swiss private bank Union Bancaire PrivĂ©e (UBP) puts 2026 near $820 billion and 2027 at $1.0–1.3 trillion.
