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If history is any guide, every major wave of public infrastructure spending outpaces equity markets and spills into bond markets. India has seen this before. Earlier this year, Meta, Nvidia, and Oracle each launched individual bond offerings of $25 billion [1] to each fund their own AI buildouts, with Amazon’s bond offering of $37 billion and Alphabet’s issuance of a rare 100-year bond to fund Alphabet’s larger debt offering in the UK.
Morgan Stanley is estimating $350-400 billion [1] in AI-related investment-grade bond offerings in the U.S. in 2026. For Indian retail investors who have experienced the AI boom through Nifty-listed tech proxies or U.S. equity ETFs, this shift in the credit System.provides a new and riskier way to think about the theme. Here’s the complete picture, India-first.
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Why Bonds and Why Now: A Recognisable Example from India’s Past
India doesn’t have to look outside for a relevant analogy, as it experienced a similar situation first-hand. Between the 1850s and 1900s, the British funded the construction of Indian Railways from London’s bond markets under the Guaranteed Railway System [2].
Funds to build the railways were guaranteed by the colonial government, and London bondholders received guaranteed 5% returns, irrespective of the actual profitability of railway lines. This guarantee made the debt look safe to London, even as many lines ran at a loss for years, supported by the guarantee instead of earnings.
The financing of AI infrastructure today is eerily similar to this previous example, with the absence of a government guarantee. Computing power, chips, and data centers have substantial requirements of capital, far beyond the cash flow even the most profitable technology behemoths can fund.
The debt is being financed at a record rapid pace, and investors are viewing the debt as safe, mostly because of the reputation of the companies involved rather than sound project economics. Between January and May 2026, the five major cloud players—Alphabet, Amazon, Meta, Microsoft, and Oracle—reported an unprecedented $159 billion [3] in combined corporate bond issuance. This remarkable rush to build out infrastructure is about a rapid expansion in the debt capacity of the tech sector, with these firms borrowing more in a few months than their combined total of $150 billion in corporate bond issuance over the five years from 2020 to 2024.
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Why Credit Quality Varies Across AI Infrastructure Bonds
This is the information about the phenomenon that Indian investors shouldn’t miss. Four out of the five hyperscalers, Alphabet, Amazon, Meta, and Microsoft, have been creating enormous amounts of profit with ease for years, leading to high credit ratings for these companies. Debt instruments issued by Microsoft are, by some standards, even safer than US Treasury Securities.
Oracle is the exception compared to the four named companies, with average ratings. The overall borrowing boom, much like the guaranteed Indian railway bonds that were issued 150 years ago, doesn’t lead to widening corporate bond spreads. In fact, they are at the lowest level in the past 25 years, as the biggest corporate issuers are believed to have strong balance sheets and low sensitivity to the returns of individual projects.
A clearer divergence is apparent in the ranking of risks. Debt issued by hyperscalers is seen as ‘safe’ compared to other debt that funds ‘risky’ projects involving Artificial Intelligence. An example of this is the $4.6 billion bond issuance by Blackstone-owned QTS Data Centers [1] for the construction of a Georgia data center to be used by Microsoft. Initially, the yield for this bond was 1.1% above bonds issued by Microsoft, and this gap has widened by 1.6%, indicating that project risk is being assessed much more conservatively than hyperscaler risk.
High-Yield AI Bonds: The Riskier Side of the AI Debt Boom
There are fewer rules and more flexibility below investment grade. CoreWeave, a company that leases high-capacity chips, completed a $2 billion bond sale last May [4], initiating a wave of high-yield bond issuance that continues today. Morgan Stanley predicts that high-yield bonds associated with AI will reach $50 billion this year.
CoreWeave, Nebius, and Iren, as well as other Neocloud companies, have issued billions of convertible bonds. The Bank for International Settlements is rightly concerned that several AI-driven companies are at risk of not fulfilling their loans, which is the same risk that eventually affected the numerous unsuccessful guaranteed railway companies when their guarantees ran out.
India’s Own AI Infrastructure Boom: Reliance, Adani, and Beyond
- India shows a similar trend in this regard, with Reliance Industries investing about $110 billion [5] into AI and digital infrastructure.
- The Adani Group is investing $100 billion [6] into AI-embedded renewable data centers, pledging this amount through 2035.
- This brings the total of India-focused AI infrastructure investments to $210 billion.
None of this really counts as “AI infrastructure debt” in the true, global hyperscaler sense, but it’s as close as it gets to a retail investment in India.
3 Ways Indian Investors Can Access Global AI Bonds
| Route | How it works | Typical entry point | Key friction |
| GIFT City (IFSC) | Invest via LRS into IFSCA-regulated global bond/ETF products through GIFT City brokers | ~$5,000+ depending on product | 20% TCS above ₹10 lakh remittance/year; limited product depth |
| Direct LRS/foreign broker | Open a foreign brokerage account and buy US-listed IG or high-yield bond ETFs with hyperscaler/data center exposure | No fixed minimum, broker-dependent | Full $250,000/year LRS cap; forex conversion costs of 0.5-1% |
| Domestic proxy exposure | Indian NCDs/bonds of companies building AI infra (Adani, Reliance-linked entities) | ₹1,000-10,000 (NCDs) | Not pure-play AI infra debt; standard corporate credit risk |
What Could Go Wrong: AI Bond Investment Risks for Indian Investors
- Duration risk on a multi-decade bet: Some of this debt has a 30-year maturity; Alphabet’s has a 100-year maturity. This effectively means bondholders are betting on which AI companies will survive for several decades.
- False sense of security: Like guaranteed returns that used to mask the poor economics of some railway lines, narrow spreads might also mask the poor economics of some projects within the AI buildout.
- Project-level vs. company-level risk: The widening gap between hyperscaler bonds and project-specific bonds (like the QTS-Microsoft case) shows risk differentiation is starting to emerge, even though the headlines suggest calm.
- Revenue-repayment mismatch: The BIS’s main concern is that some AI projects may never generate sufficient revenue to pay the debt.
- Currency and tax friction: Dollar risk holds rupee risk both ways, along with TCS and Schedule FA for LRS routes.
Is AI Infrastructure Bond Investing Right for Your Portfolio?
For a seasoned investor familiar with global diversification, a small investment-grade hyperscaler debt allocation via GIFT City funds is a reasonable way to gain access to the market—the four strongest issuers still resemble fortress balance sheet companies. But consider project-specific and junk-rated AI debt as a distinctly different, higher-risk category, and allocate accordingly.
The lesson from the Indian Railways, as well as the American AI bonds, is similar, and that is, long before the viability of the project is known, the debt has the appearance of safety because of a guarantee or a strong balance sheet. History’s lesson, whether from Indian railways or American AI bonds, is the same: a guarantee or a strong balance sheet can make debt look safe long before you know if the underlying project actually works.
Frequently Asked Questions
Imagine lending money to a really big tech company (let’s say Amazon, Meta, or Nvidia) for the purpose of constructing the physical components associated with AI.
AI exists outside the virtual world. A large volume of computing requires large and very expensive physical data centres, rapid microchips, and large cooling systems. These companies are opting to borrow hundreds of billions of dollars from the public by way of bonds instead of stock dilution. In return, they pay you back your principal and interest.
These companies are using bonds to fund the physical construction needed to support the scalable AI infrastructure, like data centers, cables, and the thousands of microchips needed. Even the biggest companies in the world simply do not possess the liquidity to fund the construction all at once.
Instead of selling off their equity (which would be bad for shareholders), they are using the AI Infrastructure Bonds. They are essentially borrowing money from the public and institutional investors, saying they will pay back the money with interest while they build it out.
Yes. Investing only in India is not your only option. These are the two primary ways Indian residents can invest in global AI bonds:
The Direct Route (LRS): There are no legal restrictions under RBI’s Liberalized Remittance Scheme (LRS) on sending your money abroad or buying foreign bonds through a global brokerage firm.
The Mutual Fund Route (GIFT City): You can invest in global mutual funds or international “Funds of Funds” established in India’s GIFT City (Gujarat). Retail investors pool funds, and the funds buy tech bonds.
They are certainly not the same, and the market is already splitting them into two very different groups:
“Fortress” Bonds: These are the bonds of AI-related companies that are very large and successful. Microsoft, for example, has a very successful core business that makes it very profitable. And, as a result, Microsoft bonds are safer than government bonds.
“Project” or “Junk” Bonds: Bonds for data centres or small “Neocloud” companies, like CoreWeave, which are leasing AI chips. Because these companies are very niche, and there is not very much demand for AI-related services outside the AI boom, these bonds are much more risky.
Taxation can be confusing. Here is the simplified version for 2026:
When money goes out (TCS): Under existing regulations, you can send up to ₹10 Lakhs overseas per financial year with no Tax Collected at Source. If you send more than ₹10 Lakhs, a TCS of 20% is levied. The good news is that you can apply for this to be refunded when you file your regular ITR.
When you earn money (Capital Gains): The only way you are taxed on the profit you earn from selling these investments is after you have held the investments for a set amount of time. This is very similar to most standard international mutual fund transactions.
Sources
- https://www.economist.com/finance-and-economics/2026/07/07/ai-has-taken-over-the-stock-market-the-bond-market-is-next
- https://irfca.org/docs/history/ir-uklaw-intro.html
- https://247wallst.com/investing/2026/06/12/in-5-months-big-tech-has-borrowed-more-than-in-the-last-5-years/
- https://investors.coreweave.com/news/news-details/2025/CoreWeave-Announces-Upsize-and-Pricing-of-2000-million-of-Senior-Notes/default.aspx
- https://economictimes.indiatimes.com/news/company/corporate-trends/reliances-110-bn-ai-investments-seen-back-loaded-over-seven-yrs/articleshow/128710454.cms?from=mdr#:~:text=Reliance%20chairman%20and%20managing%20director,and%20internet%20data%20affordable%20and
- https://www.thehindu.com/business/adani-to-invest-100-billion-in-ai-data-centres-by-2035/article70642031.ece#:~:text=This%20roadmap%20builds%20on%20Adani,Adani%20said.
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