Ceteris paribus, those figures imply a $45bn loss this year, $90bn loss next year and $110bn loss in 2028 before breakeven in 2029.
That's $250bn of losses to be financed from 2026 onwards. (They raised ~$120bn, $25bn up front and the rest based on milestones. So Another ~$125bn uncovered.) That only works if OpenAI stays a fundraising darling. So not a doomsday sceanario. But perilous, and dependent on short-term trends extending into long-term curves.
> Revenue went from $3.7B to $13.07B — roughly 3.5x.
> Operating loss went from ~$8.8B to ~$20.9B — roughly 2.4x.
> Doesn't seem like a domesday scenario.
Those two lines are moving up and to the right, but are not parallel.
It all depends on where those two lines meet (the break-even point): too far in the future and the company will be dead anyway. Almost all companies will eventually be profitable; the problem is that the majority of them will need constant cash injections to keep the lights on.
Like the old aviation saying: even a brick will fly if it has enough thrust. doesn't make the brick a plane, though.
Compounding revenue & operating loss at those same rates (3.5x and 2.4x respectfully) puts those two lines meeting at around 2031. That'd be about 9-10 years to profitability, that seems pretty normal. Amazon took 9 years, Uber took 14 years before its first profitable year.
>Amazon took 9 years, Uber took 14 years before its first profitable year
Both had a path to profitability in an environment of falling interest rates. OpenAI is going public in an environment of higher for longer interest rates. The discounting math is nowhere near as attractive for investors.
Neither Amazon nor Uber have monopolies nor much of a network effect. Amazon retail is or was famously low or near zero margin with their profits driven by AWS. Uber's margins are not much better than any average business.
I think it depends on a lot of things, not the least of wish is, this could be the worst their financials get, or depending how competitive this whole thing is, it could be the best:
The AI companies also have a lot of space to grow their income (more ads, price hikes, ...). It seems realistic for them to turn profitable. But the market expected much more from these companies.
> The AI companies also have a lot of space to grow their income (more ads, price hikes, ...).
Ads, maybe, but not only are they already walking back recent price hikes, the paying customers were hitting the brakes even on the original price.
Note that this data you see (their increased revenue) came from a period where they were onboarding customers who were competing to see who used the most tokens.
IOW, this is the best-case scenario for them - customers with no cap on token spend.
But... the caps from customers came in before they hiked prices. Then they hiked prices. That resulted in a short-term boost to revenue to compensate for the caps. Now they are talking about walking back those hikes. That means they are going to find an equilibrium lower than their best-case scenario.
I like this read. Eventually, management did collectively realize that tokens spent leaderboards were a bad idea. That is going to massively reduce the waste that was needlessly being generated to hit work quotas.
just for completeness, I think the closer analogue is probably total expenses: $12.48 billion to $34 billion -- roughly 2.7x. But this is still pretty close to what you said, so I don't particularly disagree with the numbers.
I do wonder if this comparison is really meaningful. It looks like if they can grow infinitely, then at some point they should be profitable. However, that's already a somewhat sad story ("in the limit as x->inf, we'll actually _make_ money!"). And there are of course limitations. Anthropic, Google, open models etc are all real competitors, and it seems to me that there will only be one winner. If openAI is losing money faster than the others, then it may not survive long enough to reach that eventual profitability. And finally, the human population is limited. There isn't a true infinity that the pattern can extend to. If we've only reached 10% of the TAM that's fine, but if we're at like 70% (which personally I suspect is about right), then this looks bad.
Operating loss went from ~$8.8B to ~$20.9B — roughly 2.4x.
Doesn't seem like a domesday scenario.