The expectation that Modern ai technology will find a home in every aspect of our lives is a pandemic. Fittingly, startups and investors are working overtime to build and fund technology startups to create or deploy new ai technology. Big rounds often make headlines, and startups are being built at breakneck speeds to stay ahead of both the technology curve and larger tech companies that have their own ai strategies.
But for all the excitement, there's one annoying detail that deserves our attention: ai startups often do worse financially than most software startups.
The fact that Anthropic, a leading ai startup that has raised billions of dollars, reportedly had gross margins of ai-profit-questions”>50% to 55% last December, highlights the costs of building and running modern ai models, and hints that ai-focused startups have a different valuation profile due to the sheer expense of all that computing power.
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Revenue quality is based in part on gross margins (revenue minus costs of goods sold) and the better those margins, the better the revenue, all else being equal. Startups have long relied on earnings quality as an explanation for their staggering losses during their growth years; Yes, startups consume a lot of cash, but the revenue they generate is impeccable in terms of quality and therefore worth quite a bit.
This is, among other reasons, why software companies are often valued by a multiple of their revenues rather than their profits. When gross margins are high, strong revenues generate tons of gross profits. Investors like that. But that is not a valuation model that can be applied to a company that, for example, selling groceries.
The conversation about ai gross margins is not new. In 2020, the venture firm a16z ai-and-how-its-different-from-traditional-software/”>argument that ai startups would have lower gross margins due to “intensive use of cloud infrastructure and ongoing human support.”
