Research and safety have to take a backseat for cost reduction. I mean there are many avenues to profitability for them, one I can think of is they could cut their cost significantly by creating smaller and smaller models that match or nearly match Gpt4, while paid subscribers wouldn't be able to really tell the difference. No one is really challenging them on their benchmark claims.
I think their main challenge is that in 5-10 years from now, if their current definition of AGI is still elusive, models of Gpt4 capabilities or similar (Llama 3 can fool most people I think) will be running locally and freely on pretty much any OS of choice without having to make a single outside API call. Every app will have access to local inference that neither costs developers nor the users anything to use. Especially after the novelty has worn off a bit, it's hard to see consumers or developers paying up to use something that's technically better but not significantly enough to justify a $20+/mo subscription or per token cost. Right now though, local inference has a huge barrier of entry, especially when you think across platforms.
Honestly, I think Google and Apple can afford to spend the cash to develop these models in perpetuity, while OpenAi needs to worry about massive revenue growth for the next few years, and they probably don't really have the personnel to grow revenue aggressively either. It's a research lab. The downside of revenue seeking too, is that sometimes the pursuit kills the product.