Tomasz Tunguz - Lopsided AI Revenues
Tomasz TunguzVenture Capitalist If you were forwarded this newsletter, and you'd like to receive it in the future, subscribe here. Lopsided AI Revenues
Which is the best business in AI at the moment? I analyzed Q4 revenue data from publicly traded companies across multiple sectors—software companies, consulting firms, and hardware manufacturers to determine which segment dominates the AI market. NVIDIA’s data center business dominated the field, generating $31b in Q4 revenue with impressive margins exceeding 70%. In second place, Microsoft’s AI business, including Azure, is at a $3.25b Q4 revenue. IBM reported $2b, which was a big surprise to me. Clearly, IBM’s role as the third largest generator of AI revenue is a combination of consulting and software revenue. In their most recent quarterly earnings, the company clarified the breakdown in their book of business : 20% software & 80% consulting. For OpenAI and Anthropic, I estimated Q4 revenues by taking 40% of their reported 2024 annual projections. Data for Accenture and Salesforce came directly from their published earnings transcripts. Just how large is the GPU business relative to others? Well, let’s stack them all up.
The GPU business is approximately four times larger than all of the software, infrastructure, and consulting sectors combined, based on public disclosures & pressreports. While these figures are illuminating, they don’t capture the complete AI market landscape. This analysis doesn’t capture several significant segments: hyperscalers like Amazon & Google who haven’t broken out their AI segments’ revenue, AI-focused data companies like Snowflake and Databricks, inference-as-a-service startups, other hardware manufacturers like Broadcom, and security companies such as Palo Alto Networks and CrowdStrike—all of which have burgeoning AI businesses. Maybe this group doubles the revenue. While precise total market figures remain elusive, the trend is clear: hardware investments still outpace software and services revenue in today’s AI landscape. With hyperscalers investing at least $250b in datacenters this year, software revenue has a long way to go and years of exceptional growth to catch up to equal it. |
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