That’s what they did for years. I suspect there are some “nice” macroeconomic trends helping them avoid this. Like regulatory capture and the general regulatory fragmentation of the global tech sector. And that new AI tech is prohibitively expensive.
Trying to do more with less would be one strategy - coming up with more efficient inference that takes less compute and energy. This seems to be what's driving companies in China like Deepseek. Whether one could be profitable with this strategy is another story, probably the best to hope for would be getting bought by one of the FAANGs (if you were able to show good results).
It's also possible that the first movers are doing all of the expensive and risky research and utterly failing to build a moat for themselves. It doesn't look like there's any particularly lock-in for any category of AI model, and open source is following closely behind.
Compute will get cheaper and open models will proliferate.
Doing that was a lot easier before though, with funding being more available, and big-tech has been happy to let others take the risk/dump VC funding into subsidizing their business models/... and then gobble up or copy the successful ones.
Also some of the big tech companies have been quite ruthless with firing people even when they could afford not to, which doesn't match that theory.