How a 2016 accounting rule supercharged Big Tech investments in AI startups
Amazon closed the first quarter of 2026 with a net income of $30.3 billion, a staggering 77% increase compared to the same period the previous year.
Sounds great, right?
But there is a detail that flew under the radar in most headlines: $16.8 billion of that result did not come from sales, services, or any actual business operation.
It came from an accounting revaluation of Amazon’s stake in Anthropic, the Artificial Intelligence startup at the center of one of the most intense movements in the tech market in recent years. That pre-tax gain exceeded the company’s entire operating income growth for the quarter, based solely on Anthropic’s most recent funding round.
Alphabet, Google’s parent company, did the same thing: it booked roughly $28.7 billion in similar gains from non-marketable equity securities in the same quarter, driven primarily by its stake in Anthropic. Nearly half of the company’s record $62.6 billion profit came from updating the value of private-company holdings.
Two of the biggest tech players on the planet posting historic profit records, and in both cases, the largest chunk of that result came from paper gains, with not a single penny actually hitting the bank account. Amazon shares climbed more than 4% after the earnings release.
So it is worth asking: is this real profit, or is this creative accounting operating at the edges of what the rules allow?
The answer runs through an accounting standard created in 2016 that was born with good intentions but may be feeding something few people are willing to name directly: an economic bubble being built brick by brick inside Big Tech balance sheets. 🧱
The accounting standard that changed the game
In 2016, the Financial Accounting Standards Board (FASB), the nonprofit organization authorized by the SEC to set accounting guidelines for publicly traded companies in the United States, published ASU 2016-01. This update began requiring companies that hold equity stakes in other companies to update those holdings to fair value every quarter. Any change flows directly through net income.
Before this rule went into effect in 2018, unrealized gains on equity holdings could sit on the balance sheet as accumulated other comprehensive income, a separate account excluded from net income. In other words, they only hit the bottom line when there was an actual sale. After the rule, every upward revaluation automatically becomes reported profit.
The original intention made total sense. Under the previous regime, financial institutions could keep appreciated assets recorded at historical cost indefinitely, hiding their true economic position from investors and regulators. That treatment delayed the ability of accountants and investors to recognize how much assets had depreciated before and during the 2008 Financial Crisis. By requiring fair-value measurement, the new regime aimed to give the market a more accurate and up-to-date view of a company’s real financial exposure.
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The problem is that the market evolved in a way nobody anticipated in 2016. The explosion of investment in Artificial Intelligence created an ecosystem where startups began being valued at tens of billions of dollars in private rounds, with no real liquidity, no revenue proportional to the valuation, and in many cases, not even a clear business model on the horizon. 💸
The cloud-credit circuit
The January 2025 report from the Federal Trade Commission (FTC) on AI partnerships mapped out how the major cloud providers invest billions in Artificial Intelligence startups. Microsoft has investments in OpenAI, and both Amazon and Google invest in Anthropic. A substantial portion of that investment takes the form of credits for the investor’s own cloud platform.
In practice, the startup spends those credits training models on the investor’s infrastructure. Anthropic spent $1.35 billion on AWS in 2024 and $2.66 billion from January through September 2025 alone. The investor records the resulting usage as revenue. That revenue growth supports the stock price that justifies the next round of investment.
This circuit where Big Tech pours money into AI startups and the startups funnel that money back through cloud services has four steps: invest, spend, record, justify. The first-quarter 2026 results reveal a second parallel loop running on top of the same investment.
The mark-to-market circuit
When Amazon invests $8 billion in Anthropic, and that investment is structured partly as cloud credits for AWS, the money returns to Amazon as revenue. But the investment also buys an equity stake. When Anthropic raises its next round at a higher valuation, as it did in February with its Series G, Amazon’s stake gets revalued upward. The gain flows directly into Amazon’s net income. Amazon’s $8 billion investment in Anthropic is now worth more than $70 billion, according to Amazon itself.
The central question is how independent that valuation change really is. Amazon is simultaneously an investor in Anthropic and one of its primary commercial partners. When Amazon commits additional capital, or deepens its cloud partnership in ways that make Anthropic’s business more viable, it contributes to the conditions that push the valuation, and therefore its reported net income, upward.
As Robert Willens, a tax and accounting consultant who previously served as an adjunct professor at Columbia Business School, pointed out, companies are able to control or influence the value of one of their own assets through commercial transactions with that entity.
To be precise about the causal relationship: new funding rounds for Anthropic and other AI startups are priced by incoming investors, such as venture capital and private equity funds, who conduct their own due diligence. The valuation is not set unilaterally by Amazon or Alphabet. But those incoming investors price the round in a context shaped by the commercial commitments of the existing strategic investors. Anthropic’s revenue trajectory, its access to computing infrastructure, and its competitive position depend substantially on the cloud partnerships that Amazon and Google provide.
The circularity is partial, but it is real, and it is precisely the kind of entanglement that ASU 2016-01 was not designed to address.
In short: the cloud-credit circuit converts investment into revenue. The mark-to-market loop converts the same investment directly into profit, skipping the revenue step entirely. A single dollar invested in Anthropic does double duty: it returns as cloud revenue and simultaneously appreciates as an equity stake. The more Amazon invests, the more revenue it records and the more profit it reports, without Anthropic ever having returned a single dollar on the equity stake itself.
Profit on paper, risk in the real world
Amazon and Alphabet followed Generally Accepted Accounting Principles (GAAP) in their SEC filings for the first quarter. They disclosed the gains clearly, in accordance with the 2016 FASB rule. No fraud was committed. The cloud-credit circuit, along with the profits recorded from investments that boost the value of Anthropic and OpenAI, are perfectly legal.
However, the question is not whether these transactions violate existing rules. It is whether existing rules have become infrastructure for a financial circuit that inflates reported results without a corresponding generation of cash.
Cash flow data confirms this concern. In the same quarter Amazon reported $30.3 billion in net income, its trailing twelve-month free cash flow, which is the money a company generates after covering operating expenses and capital expenditures, dropped 95%, to $1.2 billion. Capital expenditures hit $44.2 billion. The company is spending unprecedented amounts on AI infrastructure while reporting record profits, and those profits are substantially driven by the revaluation of an asset whose value depends on the continuation of that spending.
If Anthropic’s next valuation round comes in flat rather than up, Amazon’s own valuation would plummet. That, in turn, could impact Anthropic’s value if Amazon needs to pull back on its investments in the startup. 📉
The difference from the Berkshire Hathaway case
Some readers might recall that this is not the first time ASU 2016-01 has distorted results. Berkshire Hathaway’s quarterly net income has swung wildly since the rule took effect, driven by mark-to-market movements in its portfolio of public stocks. Warren Buffett went so far as to warn investors to focus on operating results.
But the Berkshire case differs in one critical respect. Berkshire holds shares of publicly traded companies like Apple, Coca-Cola, and Bank of America, whose valuations are set by liquid markets and whose business results are independent of Berkshire’s commercial relationships with them. Berkshire does not sell cloud services to Apple, does not record Apple’s spending as revenue, and then book a gain when Apple’s stock goes up.
The cloud-credit circuit is different because the investor has a material commercial relationship with the entity whose revaluation generates the gain, making the investor simultaneously a beneficiary of and a contributor to the conditions that produce the revaluation. It is this entanglement, and not fair-value accounting itself, that creates the self-referential loop.
What happens if the bubble bursts
The mark-to-market gain does not just sit on Amazon’s income statement. Its inflation propagates to every investment vehicle it touches, and that includes the retirement savings of many American families.
When Amazon’s earnings per share come in at $2.78 against a consensus estimate of $1.64, the stock reacts. Market capitalization goes up. Because the S&P 500 is weighted by market cap, Amazon’s share of the index increases. Every target-date fund, every passively managed 401(k), every ETF that tracks the index adjusts its allocation automatically. More of the money that flows automatically into those funds with every paycheck gets directed toward Amazon.
Since the Pension Protection Act of 2006, U.S. employers have been incentivized to auto-enroll workers in 401(k) plans and designate target-date funds as the default option. By 2025, 69% of participants in plans administered by Vanguard were invested in a professionally managed allocation, the vast majority in a single target-date fund. The overwhelming majority of retirement savers passively funnel contributions into whatever the cap-weighted index contains.
The crucial point is not that passive indexing transmits inflated valuations. It does that with any overvalued stock. The crucial point is that the cloud-credit circuit uniquely generates the inputs on which passive investors rely to assess value. Earnings per share, the denominator of the price-to-earnings ratio, is inflated by mark-to-market gains that originate within the circuit itself. This makes the valuation heuristics that retail investors and automated rebalancing systems use less reliable as signals of underlying economic performance.
The so-called Magnificent Seven trade at roughly 28 to 29 times forward earnings. Elevated, but not in obvious bubble territory by headline metrics. Strip out unrealized investment gains from entities with which the reporting company has commercial relationships, and the multiple shifts considerably. But the headline number is what drives index composition and what shows up on the statement a 401(k) participant checks once a quarter.
Americans do not need to understand the cloud-credit circuit or mark-to-market accounting. They just need to see that the retirement account went up.
What regulators are not seeing
Current regulatory attention focuses on the competitive structure of AI markets. The FTC has documented the cloud-AI partnerships. Senators Elizabeth Warren and Ron Wyden have argued that these partnerships function as de facto mergers. The Department of Justice and the FTC are examining non-traditional deal structures, including investments via cloud credits.
These are important interventions. But they share a common analytical horizon: market power and competitive structure. They do not address the accounting mechanism that converts the cloud-credit circuit’s self-referential dynamics into reported profits.
Three measures would help address the issue:
- First: the SEC should require cloud providers to separately disclose the portion of their earnings derived from mark-to-market revaluations of entities with which they maintain cloud commercial relationships. When the entity whose revaluation generates the gain is also a major customer whose spending constitutes revenue for the investor, the standard disclosure framework proves inadequate.
- Second: the FASB should revisit whether the ASU 2016-01 requirement to pass unrealized gains through net income is appropriate for holdings in entities with which the holder maintains a commercial relationship. The goal should not be a return to historical cost, but to ensure that the transparency gains of fair-value accounting are not undermined by blending commercially entangled revaluations with operating results.
- Third: the Financial Stability Oversight Council (FSOC) should examine whether the interaction among cloud-credit investments, mark-to-market accounting, and passive indexing flows constitutes a systemic risk. The FSOC should assess what happens if the circuit reverses: a flat or down valuation round for a major AI startup would trigger mark-to-market losses that would flow through the same income statements, depress the same earnings per share, reduce the same market capitalizations, and propagate through the same index funds that currently transmit the gains.
What this means for those following the industry
For anyone following the tech market closely, the current landscape calls for a more careful reading of the numbers that arrive each quarter. When a Big Tech company reports impressive profit growth, it is worth going beyond the headline to understand where that result is actually coming from. There is a huge difference between a company that grew because it sold more, served more customers, and expanded its operations, and a company that grew because the assets it holds in its investment portfolio were revalued upward in a private round that generated no real liquidity.
The cloud-credit circuit already converts investment into revenue. The mark-to-market gain converts investment directly into profit. Family retirement savings absorb the inflated valuations through passive indexing. Each step is legal. Each step is individually rational. The aggregate result is a self-referential system in which investment, revenue, profit, valuation, and household wealth mutually reinforce one another without requiring the underlying technology to generate proportional returns.
The accounting standards that enable this circuit were designed for legitimate purposes: transparency, timely disclosure, accurate representation of economic exposure. The argument here is not that fair-value accounting is wrong, but that its application in the context of commercially entangled strategic investments produces outcomes its architects did not anticipate: a loop in which a company’s own commercial commitments generate the valuation gains it then reports as profit.
The Artificial Intelligence market is genuinely transformative, and nobody needs hyperbole to make that case. The real advances in language models, automation, data analysis, and industrial applications are concrete and measurable. But the speed at which valuations have grown, fueled by a cycle of cross-investments booked directly into Big Tech earnings, has created an additional layer of risk that the market has not yet fully priced in.
The question regulators face now is whether the financial architecture supporting the AI industry has become sophisticated enough to generate its own evidence of success, and whether the accounting standards, securities rules, and retirement structures we rely on can tell the difference between manufactured performance and real economic value. 🤔
