Planes, Trains and AI Datacentres

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This article is featured in the Q3 2026 Future Strategist newsletter, you can read the rest of the newsletter here.

Planes, Trains and Automobiles is a 1987 American road trip comedy featuring two travelling executives struggling with a snowstorm to get back to Chicago by whatever transport means they can in time for Thanksgiving. Our take on this famous movie title features the ever-more creative financing for the AI capex juggernaut that is travelling inexorably towards $3 trillion of spend. Everyone loves comparing the AI boom with the railroad excess of the early 1900s but that bubble doesn’t reflect today’s risks that are far more akin to the financing bubble of the 1980s airline industry. Aircraft leasing became synonymous with the inventive use of finance and operating leases to create apparently less risky capital structures.

The 1980’s aircraft leasing analogy

In 1987, British Airways was privatised in the UK and this author remembers writing research to unmask the financing tricks at play. Operating leases that carried apparent protection covering the asset could be presented without balance sheet entry and with only an operating cost line in the P&L. This often masked the extent of real risk – when traffic weakened, fuel costs rose and credit tightened; rentals were a fixed cost alongside falling revenues. Leasing amplified the damage rather than single-handedly causing the bankruptcies. Continental, Pan Am and Midway entered bankruptcy, while aircraft lessor GPA narrowly avoided it after its planned flotation failed. The particularly uncomfortable discovery was that repossessing an unsalable aircraft wasn’t a great outcome.

Today’s AI data centres have potentially familiar baggage: expensive equipment, optimistic forecasts and financing that assumes tomorrow will co-operate. The technology may change the world, that doesn’t mean everyone financing it is destined for success.

The airline lesson was not leasing was inherently reckless, it was that accounting presentation could make fixed obligations look less threatening than they were. Under the old American rules, capital leases appeared as assets and liabilities, while operating leases generally stayed off the balance sheet, with future rentals disclosed in footnotes. 

Accounting standards are tighter but room still exists to be creative

Today’s accounting has closed much of that particular loophole. US companies generally recognise both operating and finance leases once they commence. But the analytical blind spot has shifted towards leases not yet commenced, construction commitments and contractual purchases of future capacity. These are not automatically current balance-sheet liabilities, yet they can commit tomorrow’s cash before tomorrow’s revenues arrive. 

Financing systems today can turn a temporary shortage into a long-term payment schedule. GPUs need not become useless for their economics to disappoint – lower rental prices, expensive power or delayed deployment can do the job. Meanwhile, a take-or-pay customer contract protects the supplier only insofar as the customer can pay and the supplier delivers. The equipment, the customer and the refinancing market may all depend on the same exuberant spending cycle.

The example of Coreweave as a financing structure poster-child

CoreWeave provides a useful example without making any explicit predictions of its own particular outcome. The company is a Neocloud, contracting to provide compute with very large contracts backed by various forms of debt and security. As at June 2026, it reported approximately $35.6 billion of debt; adding the recognised operating and finance leases, the figure becomes roughly $52.1 billion. The leases are discounted back using an imputed discount rate so that on a gross basis, a further $12.8 billion needs to be added to the liability calculation to get to gross lease commitments. On top of that, we add a further $35.5 billion of disclosed, undiscounted payments on signed leases that have not commenced.

CoreWeave: Debt and lease obligations waterfall

Obligations build from $35.6bn published debt to $100.4bn

Note: The waterfall adds published debt, recognised leases, imputerd interest liabilities and estimated payments on signed leases not yet commenced. Market cap shown separately at $50bn.

Source: Company filings, 30 September 2026.

Turning to the revenue of the Company to assess how these expenses and debts will be repaid.

CoreWeave: Revenue, EBIT and illustrative interest charges

Bloomberg consensus revenue and EBIT forecasts, interest scenarios based on $35.6bn disclosed debt

Note: Interest illustrations: 10% x 3.56bn; 15% x 35.6bn = 5.34bn. Forecast figures supplied in the accompanying text.

Source: Bloomberg, 30 September 2026.

The chart above shows the revenue and EBIT forecasts for CoreWeave using consensus analysts’ forecasts from Bloomberg. The interest charge illustrations are based on the existing disclosed debt number of $35.6 billion. As can be seen, at 15%, the EBIT for the 2026-28 period is all but consumed by the servicing charges. It is perhaps of no surprise then that as interest rates rise in the public markets, the CDS of CoreWeave reflect greater risk than the equity market assumes. As at the end of September 2026, CDS levels on CoreWeave had risen to 850 basis points; under any normal evaluation, this represents a highly distressed debt situation with a significant chance of default.

It isn’t necessarily a bad outcome, but risks are increasingly elevated

We should not forget that the company has substantial contracted demand. The question is whether cash arrives, after operating costs and investment, quickly enough to meet those debt and interest obligations without perpetually receptive capital markets. Like the movie we set out with, this is a battle against the clock. The question is will CoreWeave get to Chicago in time for Thanksgiving!

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