Long-dated bonds linked to artificial intelligence companies are under pressure as investors grow wary of funding long-term AI infrastructure amid mounting costs and uncertain technological returns, signalling a shift in confidence in the sector’s future profitability.
Long-dated bonds tied to the artificial intelligence boom are coming under pressure as investors grow less willing to finance what they see as an increasingly expensive race for data-centre capacity and computing power.
According to the Financial Times, debt linked to AI companies with maturities of more than 10 years was among the weakest parts of the investment-grade market this week, with prices falling and yields rising. The move suggests that while investors still accept the credit quality of the sector’s biggest names, they are demanding more compensation for lending over longer horizons, when the payoff from AI spending is far harder to judge.
The latest warning sign came in the bond market. SpaceX’s 30-year bond yield rose from 6.7% to 7.3% in less than two weeks, while Bank of America Global Research said debt issued by Amazon, Alphabet, Meta, Microsoft and Oracle was trading at about 0.6 percentage points above comparable high-grade corporate bonds. Shorter-dated paper has held up better, indicating that the market is willing to fund near-term needs but is increasingly uneasy about locking money away for decades.
Portfolio managers say the concern is not simply about credit quality, but about technology risk. Marija Entina of DoubleLine told the Financial Times that investors prefer nearer-term exposure and usually want long-dated bonds from companies with a clearer long-run earnings profile. She said there is scepticism about whether the huge sums being poured into AI infrastructure will generate enough returns over time. Pramod Atluri of Capital Group said the speed of technological change makes long-term lending risky because no one can be sure what the industry will look like in 10 years.
That anxiety is building against the backdrop of a historic spending surge. Tom’s Hardware reported that Google, Microsoft, Meta and Amazon are projected to spend a combined $725 billion on capital expenditure in 2026, driven largely by AI infrastructure and higher chip costs. Axios also reported in February that investor sentiment was becoming more cautious, with a Bank of America fund manager survey showing 35% of respondents believed companies were overspending on AI, a record share.
The financing burden is increasingly shifting from equity markets to debt markets. Axios said Alphabet, Amazon, Meta, Microsoft and Oracle had already issued $45 billion of US bonds early in 2026 to help fund AI-related infrastructure, especially energy-hungry data centres. Bank of America has argued that the largest hyperscalers still generate enough cash to support near-term investment, but are using debt to preserve flexibility and improve their cost of capital.
Even so, appetite for the longest maturities appears to be weakening. Amazon’s latest $25 billion bond sale reportedly drew much less demand for its 30-year tranche than for its five-year notes, with investors favouring shorter maturities and higher certainty. The Financial Times said total orders for the deal were only a little above $60 billion, well below the more than $120 billion of demand seen in Amazon’s March issuance.
The pressure is being amplified by broader market unease. Some investors already have substantial exposure to big technology groups through equities and are reluctant to add the same names in credit. Short-term US rates also remain relatively attractive, making the extra risk of long-dated AI bonds harder to justify while inflation stays above the Federal Reserve’s target and policy rates are expected to remain elevated for longer.
For now, the message from bond investors is not that they doubt the balance sheets of the big AI names. It is that they are far less certain the sector’s vast capital spending will prove durable, profitable or technologically relevant far into the future.
- https://www.edaily.co.kr/News/Read?newsId=01439926645513864 – Please view link – unable to able to access data
- https://www.tomshardware.com/tech-industry/big-tech/big-techs-ai-spending-plans-reach-725-billion – In 2026, major tech companies—Google, Microsoft, Meta, and Amazon—are projected to collectively spend $725 billion on capital expenditures, a 77% increase from the previous year. This surge is driven by the escalating demands of AI infrastructure and rising memory chip prices. Google leads with a 63% year-over-year increase in Google Cloud revenue, while Microsoft and Meta also report significant revenue growth. Despite these gains, investors express concerns about the sustainability of such heavy investments and their long-term returns.
- https://www.tomshardware.com/tech-industry/big-tech/big-tech-stocks-take-a-usd1-trillion-tumble-as-projected-ai-spending-continues-to-outweigh-revenue-investors-antsy-about-long-term-planning-becoming-never-ending-spending – Major tech companies have collectively lost nearly $1 trillion in market value amid rising concerns over excessive AI spending, which has begun to outpace projected revenues. Amazon’s announcement of a $200 billion investment in 2026 led to a 9% stock decline, with other tech giants like Meta, Alphabet, Microsoft, and Oracle also experiencing significant drops. Analysts worry that despite substantial capital outlays, companies have yet to show meaningful returns from AI, leaving revenue timelines vague.
- https://www.axios.com/2026/02/18/ai-meta-amazon-microsoft – Investor sentiment toward AI investments is shifting, with increasing skepticism about the high levels of spending by major tech companies. A Bank of America global fund manager survey reveals that 35% of investors believe companies are overspending on AI—a record share. Amazon’s plan to boost capital expenditures by 60% in 2026, reaching $200 billion, largely directed toward AI infrastructure, has raised concerns about reduced funds for stock buybacks and potential impacts on shareholder returns.
- https://www.axios.com/2026/02/17/alphabet-google-amazon-bonds – As of early 2026, major tech companies—Alphabet, Amazon, Meta, Microsoft, and Oracle—have collectively issued $45 billion in U.S. bonds to finance significant investments in AI infrastructure, particularly energy-intensive data centers. Despite concerns about aggressive AI spending, bond investors remain confident, treating their debt as high-grade and nearly sovereign in safety, especially in the case of Alphabet. International investors are also showing strong demand for this tech debt.
- https://fortune.com/2025/12/19/ai-hyperscalers-debt-issuance-bond-binge-cash-flow-capital-expenditures/ – The tech giants fueling the AI boom generate so much cash relative to their debt that they have more than enough room to issue more, according to Bank of America. In a note this week, analysts looked at the top five publicly traded AI hyperscalers: Meta, Alphabet, Microsoft, Amazon and Oracle. BofA pointed out that while the companies can fund their near-term capital expenditures with cash, they are tapping debt markets for balance-sheet flexibility and better cost of capital.
- https://www.trustnet.com/News/13468690/debt–not-equity–is-now-funding-the-ai-boom-bond-managers-warn/ – Tech companies are no longer funding their investments in artificial intelligence (AI) primarily through equity or internal cash flows, but are increasingly turning to debt, prompting fixed income managers to reassess how much credit risk is building beneath the sector’s rapid expansion. For much of the past decade, large technology companies sat comfortably in investment-grade portfolios. Strong balance sheets, conservative funding models and large net cash positions meant exposure to the sector was widely seen as low risk. That assumption is now being tested as capital expenditure accelerates and financing choices change.
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The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The article references a Financial Times report from July 11, 2026, indicating recent developments. However, the Financial Times article itself is not directly accessible, making it challenging to verify the exact publication date and content. The eDaily article was published on July 12, 2026, suggesting timely reporting. The Financial Times is a reputable source, and the article appears to be original, with no evidence of recycling or republishing.
Quotes check
Score:
7
Notes:
The article includes direct quotes from Marija Entina of DoubleLine and Pramod Atluri of Capital Group. While these quotes are attributed, they cannot be independently verified due to the lack of direct access to the original Financial Times article. The eDaily article does not provide direct links to the original sources, making it difficult to confirm the authenticity of these quotes.
Source reliability
Score:
8
Notes:
The eDaily article cites the Financial Times, a reputable major news organisation. However, the eDaily article itself is from a niche publication, which may affect the overall reliability. The lack of direct access to the Financial Times article limits the ability to assess the accuracy of the reporting.
Plausibility check
Score:
7
Notes:
The claims about rising yields on long-term AI-related bonds and investor skepticism align with recent market trends. For instance, SpaceX’s 30-year bond yield rose from 6.7% to 7.3% in less than two weeks. However, without direct access to the original Financial Times article, it’s challenging to fully verify the context and accuracy of these claims.
Overall assessment
Verdict (FAIL, OPEN, PASS): OPEN
Confidence (LOW, MEDIUM, HIGH): MEDIUM
Summary:
The article reports on recent developments in long-term AI-related bonds, citing the Financial Times as the primary source. However, the lack of direct access to the original Financial Times article and the reliance on a niche publication for reporting raise concerns about the accuracy and reliability of the information. The inability to independently verify quotes and claims further diminishes confidence in the content’s credibility.