The Biggest Test for Anthropic’s IPO: AI Can Write Code and Chat, but Can It Actually Make Money for Companies?

How smart AI is is no longer the only hot question.
After news emerged that Anthropic may pursue a U.S. IPO, a more down-to-earth question deserves attention: How much are businesses willing to pay for AI? Can that revenue be sustained over the long term? When the novelty wears off, will customers keep paying?
That is the real test for AI commercialization.
Imagine a company buying AI services, initially perhaps just to try out the new technology. Over time, the boss realizes it can help write code, organize materials, analyze information, and even boost employee productivity. If these capabilities continue to create value, the company may be willing to renew its subscription or even expand its purchases.
But there’s a catch: a good experience doesn’t necessarily mean a strong willingness to pay, and lots of users don’t necessarily mean high profits.
Many products have gone through a similar story: downloads skyrocket, but paid conversions are like a late bus—you wait and wait, and it never shows up.
So if Anthropic enters the public markets, investors will need to look beyond model capabilities and user numbers to enterprise revenue, customer retention, paid conversion, product pricing, and whether service costs can be controlled as the business scales.
A particularly important question is whether AI is merely a tool that helps employees become more productive, or whether it can become deeply embedded in business workflows and turn into infrastructure customers can’t do without.
The former may be an optional expense; the latter has a much better chance of generating stable, long-term demand.
That said, commercialization doesn’t mean every AI product has to become profitable right away. Expanding the enterprise customer base takes time, and product development requires investment. What really matters is whether revenue growth can gradually validate the product’s value.
My view is that model capabilities determine why customers come, product experience determines whether they stay, and return on investment determines whether they keep paying.
The best business model for AI isn’t making customers marvel, “This technology is amazing,” but making them look at the numbers and say, “This is money well spent.”
$ACE

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