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US Leads Global AI Borrowing With $708 Billion in Debt as New Study Reveals Which Countries Are Financing the AI Boom
30 Oct 2026
New research by British Business Funding reveals that the United States, Japan and Malaysia have the highest AI-linked borrowing relative to GDP among 20 major AI economies. The study highlights the growing financial commitments behind artificial intelligence infrastructure, data centres and semiconductor development.
30 October 2026 – The United States has accumulated more than $708 billion in AI-linked borrowing since January 2024, equivalent to 2.3% of its gross domestic product (GDP), according to new research published by British Business Funding.
The October 2026 study examines borrowing across 20 leading artificial intelligence economies, analysing the government loans, corporate bonds, private credit arrangements and project financing used to support AI development.
The findings place Japan second, with $89.8 billion in AI-linked borrowing equivalent to 2.02% of GDP, followed by Malaysia, where $8.25 billion represents 1.75% of the national economy.
The research highlights how the global AI expansion is increasingly dependent on debt financing, particularly as technology companies invest in data centres, computing infrastructure, semiconductor manufacturing and related facilities.
While the United States dominates in absolute borrowing, smaller economies such as Malaysia and Taiwan have also taken on substantial financial commitments relative to their economic size.
Which Countries Are Borrowing the Most to Fund Artificial Intelligence?
British Business Funding analysed publicly reported AI-linked debt transactions completed between January 2024 and October 2026.
The research includes government and public-sector AI credit, corporate bonds and convertible debt, project finance, private credit and asset-backed securities.
Each country's total borrowing was compared with its 2025 GDP to assess the scale of financing relative to its economy.
The study ranks countries according to AI-linked borrowing as a percentage of GDP, rather than total debt alone.
Top 10 Countries by AI-Linked Borrowing as a Share of GDP
| Rank | Country | Government & public AI credit ($bn) | Corporate bonds & convertibles ($bn) | Loans, project finance & private credit ($bn) | Total AI-linked borrowing ($bn) | % of GDP |
|---|---|---|---|---|---|---|
| 1 | United States | 6.00 | 409.88 | 292.25 | 708.13 | 2.30% |
| 2 | Japan | 0.00 | 39.73 | 50.05 | 89.78 | 2.02% |
| 3 | Malaysia | 0.05 | 0.00 | 8.20 | 8.25 | 1.75% |
| 4 | Taiwan | 0.00 | 9.46 | 5.37 | 14.82 | 1.61% |
| 5 | Netherlands | 0.00 | 14.25 | 1.86 | 16.11 | 1.21% |
| 6 | Australia | 0.14 | 5.62 | 13.88 | 19.64 | 1.07% |
| 7 | Singapore | 0.00 | 0.00 | 4.64 | 5.45 | 0.90% |
| 8 | United Arab Emirates | 0.00 | 0.00 | 0.00 | 3.17 | 0.55% |
| 9 | Ireland | 0.00 | 0.00 | 3.05 | 3.05 | 0.42% |
| 10 | South Korea | 2.23 | 0.49 | 2.15 | 4.87 | 0.26% |
Credit: British Business Funding, October 2026. Figures are reproduced as supplied in the research release. Some category totals do not reconcile with reported country totals; clarification is pending.
United States: $708 Billion in AI-Linked Borrowing
The United States leads the ranking with $708.13 billion in AI-linked debt, equivalent to 2.3% of GDP.
Corporate bonds and convertible securities account for approximately $409.88 billion, while loans, project finance, private credit and asset-backed securities contribute another $292.25 billion.
Government and public-sector AI credit represents $6 billion of the total.
According to British Business Funding, $412 billion of the identified US borrowing occurred during 2026 alone, suggesting that the pace of financing has accelerated as investment in artificial intelligence infrastructure expands.
The scale of borrowing reflects the financial resources required to construct and operate AI data centres, expand computing capacity and support the development of new technology infrastructure.
However, the research measures borrowing associated with AI investments rather than the profitability or economic returns generated by those projects.
Japan: SoftBank Accounts for Nearly 98% of AI Borrowing
Japan ranks second, with approximately $89.78 billion in AI-linked debt, equivalent to 2.02% of GDP.
Unlike the United States, where financing is distributed across multiple organisations and debt instruments, Japan's borrowing is heavily concentrated in one company.
British Business Funding reports that SoftBank accounts for approximately $88.1 billion of the country's identified AI-linked borrowing.
The company's financing includes a $15 billion bridge loan arranged through a group of banks.
This concentration highlights the importance of individual corporate borrowers in shaping national AI investment figures.
It also illustrates how large technology groups can influence the development of artificial intelligence infrastructure through their financing decisions.
Malaysia: Data Centre Investment Drives AI Borrowing
Malaysia ranks third despite having substantially lower absolute borrowing than the United States or Japan.
The country has accumulated approximately $8.25 billion in AI-linked debt, representing 1.75% of GDP.
According to the research, most of this financing supports data centre developments in Johor, a region attracting investment in digital infrastructure.
The identified projects include DayOne's $3.6 billion green financing arrangement and AirTrunk's $2.3 billion project loan.
These investments demonstrate how AI development is creating demand for physical infrastructure, including data centres and the facilities required to support large-scale computing operations.
For Malaysia, the results highlight the role of infrastructure financing in its participation in the international AI economy.
Taiwan and the Netherlands Complete the Top Five
Taiwan ranks fourth with $14.82 billion in AI-linked borrowing, equivalent to 1.61% of GDP.
The country's financing is closely associated with semiconductor production, chip packaging and server supply chains.
British Business Funding identifies two syndicated loans, each worth approximately $1.6 billion, arranged for semiconductor packaging companies ASE and SPIL.
Corporate bonds and convertible securities account for approximately $9.46 billion of Taiwan's total AI-linked borrowing.
The Netherlands ranks fifth, with $16.11 billion in identified debt, equivalent to 1.21% of GDP.
Much of this financing is associated with Nebius, which the report says accounts for approximately $15 billion across five transactions.
The largest identified transaction was a $5.75 billion convertible note offering in August 2026.
Like Japan, the Netherlands demonstrates how a small number of large technology companies can account for a substantial proportion of national AI-linked financing.
What AI Borrowing Means for Cities and Digital Infrastructure
The growth of AI-linked borrowing has implications for cities and regions hosting major technology developments.
Artificial intelligence infrastructure depends on physical assets, including data centres, electricity networks, semiconductor production facilities and supporting industrial services.
As companies invest in these assets, local economies may experience new construction activity, demand for technical expertise and opportunities for infrastructure development.
Malaysia's concentration of borrowing in Johor illustrates how particular regions can become important locations for AI-related investment.
Similarly, Taiwan's financing demonstrates the central role of semiconductor supply chains in supporting the technology industry's expansion.
However, such developments can also create challenges for cities and regional authorities.
Large data centres require substantial electricity, cooling capacity, land and supporting infrastructure. Their economic benefits therefore need to be considered alongside their effects on local resources and long-term development priorities.
The financial sustainability of these projects is also relevant to regional planning, particularly when developments depend on large debt commitments and future demand for computing services.
The Financial Risks Behind the Global AI Expansion
Although borrowing can accelerate innovation and infrastructure development, it also creates repayment obligations that must be met regardless of how quickly a project generates revenue.
British Business Funding cautions that businesses should carefully assess the financial assumptions behind AI investments.
A financial expert from the company explained:
Borrowing to fund new technology can open doors, but the repayments arrive on a fixed schedule even when the returns do not.
The firm recommends that organisations evaluate whether expected project revenues can cover borrowing costs under different economic conditions.
Businesses should consider the consequences of slower growth, higher interest rates and delays in generating revenue.
The research also recommends diversifying borrowing across lenders and financing instruments where appropriate.
For smaller companies, staged financing and asset-backed arrangements may help align borrowing with completed development milestones.
These considerations are particularly important for capital-intensive projects, including data centres and advanced technology facilities, where initial investment costs can be substantial.
Can AI Infrastructure Investment Deliver Sustainable Economic Growth?
The study demonstrates that the global AI expansion is not financed solely through venture capital, equity investment or government funding.
Debt has become an important source of capital for organisations developing the infrastructure required to support artificial intelligence.
The United States leads in both total identified borrowing and borrowing relative to GDP, while Japan, Malaysia, Taiwan and the Netherlands show different patterns of financing concentration and industrial investment.
For governments and cities, the findings highlight the increasing connection between technological development, financial markets and physical infrastructure.
However, higher AI-linked borrowing does not necessarily indicate stronger innovation, greater productivity or better economic outcomes.
The eventual returns will depend on infrastructure utilisation, commercial demand, operating costs and the ability of borrowers to meet their financial commitments.
As artificial intelligence investment continues expanding, the financial structures supporting these developments will become an increasingly important consideration for businesses, investors and policymakers.
The research indicates that understanding the debt behind AI infrastructure may be as important as tracking the technology itself.
