How the AI Labs Make Profit (Maybe, Eventually)

I wrote this essay as a submission to Dwarkesh Patel’s blog prize, though I have been meaning to write this up for a while.Usually, for a company to become profitable, they need to increase revenue, decrease costs, or some mixture of the two. For AI companies in their current form, I think there is a third way they can become profitable that looks like increasing revenue but is distinct from what they are currently doing. Namely, internal deployment where they spin up internal companies.First, the AI companies currently aren’t facing a lot of pressure to become profitable. That’s partially the reason that OpenAI and Anthropic are the first companies to reach ~$900B valuation and be cash flow negative. They’ve had the luxury of not being profitable and focusing on growth because the market has been willing to fund their growth. This allows for ideologies within the companies to remain that eventually might not continue to fly, like “we are going post-economic, money won’t matter” or “we will build the machine god and ask it to make money”. But eventually, companies will be forced to become profitable. There is only about ~another round of capital left where the companies can remain unprofitable. Perhaps OpenAI/Anthropic could raise $250-500B at a $1.5-2.5T valuation, but it seems very unlikely that they could raise $1T+ at a $4T+ valuation.It’s fairly hard to imagine AI labs doing much to cut costs to become profitable. They could prioritize developing and releasing smaller models, but it seems difficult to stay in the race without pushing the frontier. They could try to cut their research costs, but these are likely to increase as demand for larger and more intelligent models continues. With company ambitions and investor desires, it doesn’t seem like cutting will be the chosen method.It is more plausible that the labs could increase their revenues by charging more. Many individual users are paying $2000/year/company, and some enterprises are likely paying $100M+/ye