This article breaks down the massive debt and revenue milestones that AI leaders (NVIDIA, OpenAI, Anthropic) must hit to justify the $9–15 trillion in planned data-center build-out. It shows how banks, hyperscalers, and chipmakers need AI services to generate over $2 trillion annually by 2030 or risk a market collapse.

• Building the planned 190 GW of AI data-center capacity could cost $9.5–15 trillion (far above Bloomberg's $3 trillion estimate), requiring banks to roughly double annual debt issuance to $500B–$1T just to sustain it
• NVIDIA's projected $1 trillion 2027 revenue depends heavily on three clients (likely ODMs for Microsoft, Google, Meta), tying its fate to those firms' ability to keep raising debt
• OpenAI and Anthropic will drive 70–90% of AI compute demand but are on track for under $360 billion combined revenue by 2029—less than half the ~$875 billion needed even under a scenario where only half the planned capacity gets built
• Outside the major AI labs there are essentially no other large-scale compute buyers, meaning enterprise IT spending on AI would need to grow by orders of magnitude to justify current valuations and debt levels

Secondary-market trades on Forge Global pushed Anthropic’s valuation to about $1 trillion, surpassing OpenAI’s roughly $880 billion price. The surge reflects scarce share supply, rapid revenue growth (from a $9 billion to $39 billion annual run rate), and partnerships with Amazon and Palantir.

• Anthropic's secondary-market valuation hit ~$1 trillion on Forge Global, surpassing OpenAI's ~$880 billion, up from just $380 billion three months earlier
• Anthropic's annualized revenue run rate jumped from $9 billion (late 2025) to $39 billion (March 2026), fueling investor demand
• Share scarcity is driving frenzied bidding, with offers ranging from $960 billion to $1.05 trillion and some even involving property trades
• Growth is tied to Claude Code's popularity and major partnerships with Amazon and Palantir

OpenAI and Anthropic are approaching record IPOs but face enormous costs for AI model training. OpenAI expects a staggering $121 billion in computing expenses by 2028, leading to significant projected losses, while Anthropic anticipates similar challenges but on a smaller scale. Both companies are rapidly releasing new AI models, intensifying the competition and cost pressures.

• OpenAI projects $121 billion in cumulative computing expenses by 2028, driving major projected losses despite revenue growth.
• OpenAI's revenue is set to hit $1 billion in 2024 (up from $540 million in 2023), with a potential valuation around $100 billion.
• Anthropic trails with projected 2024 revenue of $300 million (up from $100 million in 2023), growing more slowly but leaning on its safety-focused reputation to attract investors.
• Both companies are racing to release new models, intensifying competitive and cost pressures ahead of their IPOs.