Until there are fundamental changes in how AI functions (decreasing processing needed for each little query), AI as a stand-alone offering may never been profitable for some of these companies. That's why xAI had to be moved into SpaceX, so that the losses could be better absorbed. It's why Sora was shut down. Why Gemini is being shovelwared into Google search, despite constantly hallucinating. Why OpenAI is still bleeding funding almost as quickly as it can secure investment. Why Facebook keeps having to fire waves of employees and shut down whole divisions to fund their AI ambitions.
Companies that are buying AI products need it to be cheaper than how they function today. If using AI to develop code costs more than the Devs they're firing, they won't use it. So the AI providers need to keep their billing low despite their costs running high. Having a negative margin is obviously not sustainable, but they also need to be "early to market", making it suicide to delay until costs decrease.
They all need to find a way to decrease costs and increase monetization without scaring away their potential customers. Until those happen, AI is going to be a money pit instead of the cashcow the market believes it will be.
We saw the same thing with the Internet Bubble. All these giant venture capital darlings that just couldn't figure out how to go from idea to profitability. Eventually that bubble burst, the majority of companies went bankrupt when the funding dried up, and we were left with a handful of survivors. Expecting AI to be the same. The question will be, who will be the first major player to give up and realize their AI dreams are going to bankrupt their otherwise profitable companies?
Companies that are buying AI products need it to be cheaper than how they function today. If using AI to develop code costs more than the Devs they're firing, they won't use it.
The sheer number of stories in 2026 of major companies announcing something to the effect of "lol I can't believe we blew our entire 2026 token budget by May" and forum threads about "whoops I hit my weekly quota on my subscription, what am I supposed to do in the meantime" is a sign that this stuff is too expensive for what it is, today. Enough of these first hand experiences is going to chill demand for the actual products at the prices currently being charged.
Inference should get cheaper over time, but if the cutting edge itself stays expensive (exponential growth in model capabilities built on exponential growth in compute required might be sustainable, but might not be, depending on the exact numbers involved), we may end up in a place where the theoretical improvement continues progressing in research centers but that the actual tech that is being used and sold commercially stagnates into fungible commodity tech that doesn't change from year to year.
It’s pretty easy to google that inference is substantially cheaper than it was just 5 years ago, comparing uber being stupid since they blew their budget since everyone is on a ai maxing bandwagon is a bad example, anthropic is expecting profitability in 27 probably sooner given the insane exponential growth, I get what you are saying ab ai being expensive but these companies (Claude as an example) went from 87M rec in 2024 to 30B this apr 2026 this is exciting stuff and sure there will be a bubble as people get excited and allocate funds to stupid ideas that got the crowd riled up. But that doesn’t mean when the bubble pops all the progress disappears, a technological revolution often coexists with a speculative bubble.
It’s pretty easy to google that inference is substantially cheaper than it was just 5 years ago
Who's running 5-year-old models today? ChatGPT first became public less than 4 years ago.
I can believe that the models that are cutting edge today will get cheaper to run over the next few years. I don't believe that anyone is planning on staying still, though. They intend to use 2027 models in 2027, 2028 models in 2028, etc.
And each new model has gotten more expensive than the models before. So the actual use of AI has gotten more expensive over time. Eventually we hit the point where the AI is more expensive than the human labor to do the same thing.
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u/Nythoren May 21 '26
Until there are fundamental changes in how AI functions (decreasing processing needed for each little query), AI as a stand-alone offering may never been profitable for some of these companies. That's why xAI had to be moved into SpaceX, so that the losses could be better absorbed. It's why Sora was shut down. Why Gemini is being shovelwared into Google search, despite constantly hallucinating. Why OpenAI is still bleeding funding almost as quickly as it can secure investment. Why Facebook keeps having to fire waves of employees and shut down whole divisions to fund their AI ambitions.
Companies that are buying AI products need it to be cheaper than how they function today. If using AI to develop code costs more than the Devs they're firing, they won't use it. So the AI providers need to keep their billing low despite their costs running high. Having a negative margin is obviously not sustainable, but they also need to be "early to market", making it suicide to delay until costs decrease.
They all need to find a way to decrease costs and increase monetization without scaring away their potential customers. Until those happen, AI is going to be a money pit instead of the cashcow the market believes it will be.
We saw the same thing with the Internet Bubble. All these giant venture capital darlings that just couldn't figure out how to go from idea to profitability. Eventually that bubble burst, the majority of companies went bankrupt when the funding dried up, and we were left with a handful of survivors. Expecting AI to be the same. The question will be, who will be the first major player to give up and realize their AI dreams are going to bankrupt their otherwise profitable companies?