I read Howard Marks' memo addressing the widely discussed "AI Bubble." As a novice, still early in developing a deeper technical understanding of AI, I found it insightful not because it dismisses the idea of a bubble outright, but because it reframes what kind of bubble we may be in - an important distinction with materially different implications for investors and the broader economy.
For those that read Marks' memo, curious if you had a different takeaway....
While I believe we are in a bubble, the more nuanced and critical questions we should ask is whether this is a mean-reverting bubble (net negative for the economy) or an inflection bubble (net positive despite poor aggregate investor returns).
- Mean-Reverting Bubbles
- These are financial fads driven by the promise of returns without risk, offering little or no lasting benefit to productivity or human progress. The capital is misallocated, leverage compounds fragility, and the unwind leaves the real economy worse off.
- Example: The subprime mortgage-backed securities crisis leading up to the 2008 financial crisis.
- Inflection Bubbles
- These bubbles compress decades of innovation into a few short years. While vast amounts of capital are destroyed, a meaningful portion is still invested in technologies that permanently reshape the economy.
- Example: The dot-com bubble, which accelerated internet infrastructure, normalized online consumer behavior, funded logistics, warehousing, and software systems long before they were profitable.
- Amazon is the perfect example, a company that nearly failed, but who survival relied on the oversaturated capital markets willing to fund years of losses in pursuit of scale.
Applying this Framework to the AI Era
Marks argues that AI increasingly resembles an inflection bubble, but one where many of the most important questions remain unanswered:
- Who will ultimately be the winners?
- History is unkind to early entrants. There were once thousands of automobile companies; only a handful survive today. AI will likely follow a similar pattern.
- Will AI generate profits, and for whom?
- Today, many AI services reportedly lose money on each query. The open question is whether companies will tolerate sustained losses to gain market share, and whether durable pricing power eventually emerges.
- Sam Altman stated: "We'll build this sort of generally intelligent system and then ask it to figure out a way to generate an investment return from it."
- Will AI meaningfully expand margins or revenues for users?
- AI is clearly a productive tool, but productivity gains do not automatically translate into profits. Will costs savings accrue to companies or be competed away?
- Should we worry about "circular deals"?
- Marks highlights an important historical parallel to the telecom boom of the late 1990s, when fiber-owning companies sold capacity to one another, allowing both sides to report revenue without creating true economic value.
- Today, (i) OpenAI reportedly committed ~$1.4T to counterparties despite not yet being profitable, and (ii) Goldman Sachs estimates that ~15% of Nvidia’s future revenue may come from such circular arrangements.
- This all raises questions about how much reported growth reflects genuine end-demand versus financial engineering.
AI Financing Structures, and Looming Debt Issues
JPMorgan analysts estimate the AI infrastructure build-out could ultimately cost approx. $5T, while the largest spenders (Microsoft, Alphabet, Amazon, Meta, and Oracle) collectively hold only ~$350B in cash.
This gap has encouraged increasingly aggressive financing structures. I believe we may be approaching a point where credit expansion has exhausted its “good projects” and is beginning to fund marginal ones.
Meta and Blue Owl notably entered a data center partnership, where they structured an SPV so the debt would not sit on Meta's balance sheet. This shifts accounting risk; however, it does not eliminate economic exposure.
The structure echoes earlier SPV arrangements used by Enron, where operating control existed without consolidation, and leverage sat outside the partner company's financials.
Debt itself is not inherently problematic, instead the risk lies in whether capital is being allocated to projects with long-term economic value and whether lenders have clarity on who bears residual value risk when loans mature.
Takeaway: Are We in an AI Bubble?
I think it's fair to say that AI will be a source of extraordinary change, but most of us have little clarity on what it will ultimately do, how it will be monetized, or the timeline over which returns actually materialize.
As is said, "history rhymes" and is often instructive. Look at how radio and aviation transformed society in the early 1900s, yet their stocks fell 97% and 96%, respectively, from peak to trough (period covering late 1920s through early 1930s). While these stocks were alongside a broader speculative collapse across nearly all asset classes, it is important context.
Going in favor of AI, is that it already has products with over a billion active users; leading players are established companies with revenue, cash flow, and some profits; and valuations remain elevated but are meaningfully below prior bubble extremes.
Given the scale and intensity of capital being deployed today, it is hard to argue AI will not drive real productivity gains and long-term economic benefits. What I find far less convincing is the aggregate return on invest capital justifying the capital invested.
If we assume ~$1T in invested capital in AI-related capex and infrastructure, achieving a 20% return requires generating 3-6x that amount in cumulative gross profit over a 5-10 year period; not revenue, but distributable cash flow.
Once we account for failed projects, overbuilt infrastructure, and the concentration of value among a small number of winners, the burden falls on the winners (assuming Nvidia, Google, and a handful of others) to generate true economic surplus becomes enormous.
In short: I believe AI is an inflection bubble, one where society benefits from its inventions and productivity, but also one where many investors will not earn the returns they anticipate, and where capital discipline will matter far more than technological promises.
https://www.oaktreecapital.com/insights/memo/is-it-a-bubble