Magnificent Seven Debt Hits $578 Billion, SBI Warns of Risk

The combined debt of the seven largest US technology companies, collectively known as the Magnificent Seven, has surged nearly 45% to $578 billion by mid-2026, raising concerns about the financial risks associated with the rapid expansion of Artificial Intelligence infrastructure. A report by SBI Research has warned that rising borrowing costs and US Treasury yields could put significant pressure on the companies’ market valuations.

The Magnificent Seven includes Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. According to the report, their combined debt increased from approximately $399 billion in 2025 to $578 billion by mid-2026, reaching nearly 1.7 times its 2023 level.

SBI Research estimates that a rise in bond yields could potentially reduce the group’s combined market capitalisation by $1.67 trillion to $2 trillion. The seven companies have an estimated combined market value of around $23 trillion, making even a relatively small percentage decline significant for global equity markets.

AI Infrastructure Expansion Drives Technology Companies’ Borrowing

The increase in debt comes as major technology companies accelerate investment in artificial intelligence, data centres and computing infrastructure. Developing and operating advanced AI systems requires substantial spending on specialised chips, servers, networking equipment, electricity and data-centre facilities.

While these investments are intended to strengthen companies’ long-term technology capabilities and support new revenue opportunities, they also increase financing requirements. Companies may need to rely on borrowing and other funding sources to support infrastructure expansion while continuing their existing business operations.

The SBI Research report also highlighted significant off-balance-sheet commitments, including obligations related to purchases and investments. Such commitments can create additional financial responsibilities even when they do not immediately appear as conventional debt on corporate balance sheets.

The growing scale of borrowing and future spending obligations has brought greater attention to the financial sustainability of the AI investment cycle. Investors are increasingly examining whether future earnings and commercial demand will be sufficient to justify the infrastructure expenditure.

Rising US Treasury Yields Could Put Pressure on Big Tech Valuations

SBI Research warned that higher borrowing costs and rising US Treasury yields could affect the valuations of the Magnificent Seven companies by increasing the discount rate applied to their expected future earnings.

In equity markets, investors assess companies partly on the basis of the profits they are expected to generate in the future. Those projected earnings are discounted to calculate their present value. When interest rates and bond yields rise, the discount rate used in valuation models can also increase, reducing the present value of future cash flows.

This effect can be particularly important for companies whose valuations depend heavily on expectations of substantial earnings growth over many years.

Using an equity duration approach, SBI Research estimated that higher yields could result in a potential market capitalisation decline of between $1.67 trillion and $2 trillion for the seven companies.

The estimate represents a potential valuation impact rather than a confirmed loss. The actual effect would depend on the scale and duration of any increase in yields, company earnings, investor expectations and broader market conditions.

Magnificent Seven’s $23 Trillion Market Value Raises Stakes

The combined market capitalisation of Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla was estimated at approximately $23 trillion in the report.

Their large size means movements in these stocks can have a substantial influence on major US equity indices. Several of the companies also have significant representation in widely tracked benchmarks, including the Nasdaq 100 and S&P 500.

Consequently, a broad correction across these stocks could affect not only technology-focused portfolios but also investors holding diversified US equity funds.

The debt increase also adds another dimension to the market’s assessment of the AI boom. Investors must consider both the potential revenue opportunities created by artificial intelligence and the financing costs associated with building the infrastructure needed to support it.

Anthropic’s Expected Public Market Entry Could Test AI Investment Appetite

The SBI Research report also pointed to the expected entry of artificial intelligence company Anthropic into public equity markets, likely around November 12, with a target valuation of $1.5 trillion to $2 trillion.

The report described the proposed listing as a “high-stakes litmus test” for the financial viability of the AI boom. A public-market debut would give investors another opportunity to assess whether the commercial revenues generated by AI businesses can justify the substantial costs of computing infrastructure and technology development.

Enterprise demand and revenue growth will be important considerations in evaluating the company’s business model. Investors will also examine infrastructure costs, capital requirements and the ability to turn growing AI adoption into sustainable profitability.

The proposed valuation range, if pursued, would place considerable attention on how public investors assess the long-term financial potential of AI companies. However, the eventual market response would depend on the final offering details and prevailing investment conditions.

Federal Reserve’s Unrealised Treasury Losses Also Increase

Beyond the technology sector, SBI Research highlighted the impact of rising bond yields on the US Federal Reserve’s holdings of government securities.

The report said unrealised losses on the Fed’s Treasury holdings increased by $26.3 billion, from $535.3 billion in December 2025 to $561.5 billion in June 2026.

During the same period, the yield on the US 10-year Treasury note rose from 4.18% to 4.44%.

Bond prices generally move in the opposite direction to yields. When market yields increase, the prices of existing fixed-interest securities typically decline because their previously issued coupon payments become less attractive compared with newly available bonds.

As a result, the market value of Treasury securities held by the Federal Reserve can fall when yields rise, increasing their unrealised losses.

Quantitative Tightening and Treasury Valuation Losses Are Different

SBI Research also clarified that the decline in the Federal Reserve’s total assets largely reflected securities runoff under its quantitative tightening programme. It was not an automatic write-down caused by higher Treasury yields.

Quantitative tightening involves reducing the size of a central bank’s balance sheet, generally by allowing securities to mature without fully reinvesting the proceeds. This is different from the change in the market value of bonds caused by movements in interest rates.

The distinction is important when assessing the financial impact of higher yields on the Federal Reserve. Changes in total assets reflect balance-sheet operations, while unrealised valuation losses relate to the difference between the value of securities and their market prices.

AI Spending, Debt and Interest Rates Become Key Market Risks

The SBI Research findings highlight the growing connection between technology investment, corporate borrowing and global interest-rate movements.

The Magnificent Seven companies remain major participants in the development of artificial intelligence, but their expanding infrastructure commitments have increased investor attention on financing costs and future returns.

If Treasury yields continue to rise, higher discount rates could place pressure on valuations, particularly for companies whose share prices depend on expectations of strong future earnings. At the same time, weaker-than-expected AI monetisation could raise questions about whether current investment levels are financially sustainable.

For investors, the central issue is no longer simply how quickly artificial intelligence is developing, but whether the revenue generated by the technology can support the scale of investment required. The combination of rising debt, substantial future commitments and changing bond yields will remain important factors in assessing the outlook for the world’s largest technology companies.