AI’s $600 Billion Question: Can the Industry Monetize Fast Enough?

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# AI’s $600B Question

The AI bubble is reaching a tipping point. Navigating what comes next will be essential.

By [David Cahn](https://sequoiacap.com/people/david-cahn/)

Published June 20, 2024

In September 2023, I published [AI’s $200B Question](https://sequoiacap.com/article/follow-the-gpus-perspective/). The goal of the piece was to ask the question: “Where is all the revenue?”

At that time, I noticed a big gap between the revenue expectations implied by the AI infrastructure build-out, and actual revenue growth in the AI ecosystem, which is also a proxy for end-user value. I described this as a “$125B hole that needs to be filled _for each year of CapEx at today’s levels_.”

This week, Nvidia completed its ascent to become the most valuable company in the world. In the weeks leading up to this, I’ve received numerous requests for the updated math behind my analysis. Has AI’s $200B question been solved, or exacerbated?

If you run this analysis again today, here are the results you get: AI’s $200B question is now AI’s $600B question.

![](https://sequoiacap.com/wp-content/uploads/sites/6/2024/06/600B-table-1.png)

Note: It’s easy to calculate this metric directly. All you have to do is to take Nvidia’s run-rate revenue forecast and multiply it by 2x to reflect the total cost of AI data centers (GPUs are half of the total cost of ownership—the other half includes energy, buildings, backup generators, etc)1. Then you multiply by 2x again, to reflect a 50% gross margin for the end-user of the GPU, (e.g., the startup or business buying AI compute from Azure or AWS or GCP, who needs to make money as well).

What has changed since September 2023?

1. **The supply shortage has subsided:** Late 2023 was the peak of the GPU supply shortage. Startups were calling VCs, calling anyone that would talk to them, asking for help getting access to GPUs. Today, that concern has been almost entirely eliminated. For most people I speak with, it’s relatively easy to get GPUs now with reasonable lead times.
2. **GPU stockpiles are growing:** Nvidia reported in Q4 that about half of its data center revenue came from the large cloud providers. Microsoft alone likely represented approximately [22% of Nvidia’s Q4 revenue](https://platformonomics.com/2024/02/follow-the-capex-triangulating-nvidia/comment-page-1/). Hyperscale CapEx is reaching historic levels. These investments were a major theme of Big Tech Q1 ‘24 earnings, with CEOs effectively telling the market: “We’re going to invest in GPUs whether you like it or not.” Stockpiling hardware is not a new phenomenon, and the catalyst for a reset will be once the stockpiles are large enough that demand decreases.
3. **OpenAI still has the lion’s share of AI revenue:** The Information recently reported that OpenAI’s revenue is now [$3.4B](https://www.theinformation.com/articles/openais-annualized-revenue-doubles-to-3-4-billion-since-late

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