$600 Bn Revenue Needed To Justify AI Hardware Spend: Report

As big tech and AI companies continue to pour money into infrastructure to support and build artificial intelligence (AI) and generative artificial intelligence (GenAI) products and tools, some experts are questioning if the investments will pay off or not.

The question includes what the revenue generated by such companies should be to justify its AI hardware expenditure – a question that has been answered by Sequoia Capital’s partner and analyst David Cahn, who came up with a report outlining the AI revenue required for payback.

So, what did David Cahn’s report say? Let’s explore!
 

What Did Sequoia Capital’s David Cahn Report?

 

• “The AI bubble is reaching a tipping point. Navigating what comes next will be essential,” is how David Cahn, a partner and analyst at Sequoia Capital, began his analysis report titled “AI’s $600B Question”, which was published on Sequoia Capital’s website.

• The report follows up on his previous article titled “AI’s $200B Question”, which was also published on the company’s website in September 2023.

• The crux of both articles was to determine what the return on investment (ROI) and revenue generated should be for all the money being poured into building the necessary infrastructure for the AI and GenAI ecosystem.

• The first article came about as Cahn noticed a gap between the revenue expectations and the actual revenue growth in the AI ecosystem.

• This included summing up the reported revenues from bigwigs like OpenAI, Microsoft and others, along with generous “dummy assumption” estimates from like-minded businesses, leading to Cahn noting a “$125B+ hole that needs to be filled for each year of CapEx at today’s levels.”

• At the time, the estimated annual AI Revenue Required for Payback was set at $200 billion by Q4 2023.

• In the follow-up article, Cahn reports that the actual revenue generated reached $294 billion.

• However, the AI Revenue Required for Payback by Q4 2024 jumped to $600 billion annually.

 

How Did David Cahn Calculate The AI Revenue Required For Payback?

 

• As per the initial estimates, Cahn considered that for every $1 spent on a GPU, roughly $1 needs to be spent on energy costs to run the GPU in a data center, following which the end-user margins, estimated around double the expenditure, would need to be added.

• As per the report, “GPUs are half of the total cost of ownership – the other half includes energy, buildings, backup generators, etc.”

• Based on analyst forecasts predicting NVIDIA to earn a revenue of $50 billion in run-rate GPUs sold by Q4 2023, the cost to run a data center would equal $100 billion, while end-user revenue generation would need to be $200 billion.

• Following the same calculations and current forecast trends, NVIDIA’s GPU sales are expected to hit $150 billion by Q4 2023, making the cost of data centers $300 billion and end-user revenue generation $600 billion.

 

What Changes Did David Cahn Observe Since The First Report?

 

• As per David Cahn, late 2023 witnessed the peak of the GPU supply shortage, which has now subsided.

• Seeing the vast capabilities of AI and GenAI, companies have begun stockpiling GPUs, in a bid to make stronger and more powerful supercomputers.

• While Microsoft alone represented 22% of NVIDIA’s Q4 revenue, AMD found itself set to build a supercomputer consisting of approximately 1.2 million GPUs.

• Adding to Cahn’s generous assumption that Google, Microsoft, Apple and Meta will generate revenues around $10 billion annually and adding $5 billion for Oracle, ByteDance, Alibaba, Tencent, X and Tesla, along with other companies, the $125 billion hole is now a $500 billion hole.

• Moving ahead, NVIDIA is set to launch its B100 chip later in the year, which is believed to offer 2.5x better performance at a 25% surge in cost.

 

What Did David Cahn Say About The Road Ahead?

 

• Concluding his report, David Cahn said, “A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely. We are living through what has the potential to be a generation-defining technology wave.”

• “Companies like Nvidia deserve enormous credit for the role they’ve played in enabling this transition, and are likely to play a critical role in the ecosystem for a long time to come.”

• “Speculative frenzies are part of technology, and so they are not something to be afraid of. Those who remain level-headed through this moment have the chance to build extremely important companies.”

• “But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick, because AGI is coming tomorrow, and we all need to stockpile the only valuable resource, which is GPUs.”

• “In reality, the road ahead is going to be a long one. It will have ups and downs. But almost certainly it will be worthwhile.”

Do you think David Cahn’s analysis is on point?

Do you think AI companies need to start moving towards bigger revenues to justify their expenditures or do you think they have more time to reach that stage?

Let us know in the comments below!