There is an expectation that Modern AI technologies will become entrenched in every part of our lives due to the pandemic. Fittingly, startups and investors are working overtime to create and fund new technology companies to develop or deploy new AI technologies. Big rounds often make headlines, and startups are building their businesses at breakneck speed to stay ahead of both technological advances and the biggest tech companies with their own AI strategies.
But despite all this enthusiasm, there are some minor details worth noting. That said, the economics for AI startups are often worse than for most software startups.
The fact that Anthropic, a leading AI startup that has raised billions of dollars, reportedly had a gross profit margin of 50% to 55% last December, shows that the cost of building and running modern AI models is This suggests that AI-focused startups are valued differently. The profile is different because all the computing power is spent in huge amounts.
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Earnings quality is determined in part by gross profit margin (revenue minus cost of goods sold). All else being equal, the higher these margins, the better the return. Startups have long relied on the quality of their earnings to explain large losses during periods of expansion. Sure, startups burn a lot of cash, but the returns they generate are pure in quality and therefore very valuable.
This is among the most important reasons why software companies are often valued on multiples of revenue rather than profits. If you have a high gross profit margin, you can make a huge amount of gross profit if your revenue is strong. Investors love it. However, this is not a valuation model that can be applied to a company that sells food products, for example.
The AI gross margin debate is not new. Back in 2020, venture firm a16z claimed that AI startups would have lower gross margins due to “heavy use of cloud infrastructure and ongoing human support.”