This is basically right. The problem with space imagery is that almost everyone who wants it has a niche use case, and those few organizations without a niche use case (the US Weather Service, various militaries, etc) generally want imagery that's so specialized to their own problem that they have to spec, buy, and operate their own orbital assets.
Take Ukraine as an example. Leaving aside the moral question of whether a satellite imagery company should be profiting off the Ukrainian war, Ukraine appears to be using commercial orbital imagery providers to figure out Russian troop movements. That use case is not one any commercial provider anywhere is going to build an ML model for. But analysts working on behalf of Ukraine can absolutely either use raw pixels or develop their own ML algorithms that run on top of the raw pixels to find Russian tanks.
And almost every other potential user is similar. They're all looking for something different. Oil companies want to pre-screen drilling locations. NGOs want to look at deforestation in Brazil or methane leaks in Saudi Arabia. You could even go all the way down to individuals -- at the right price, individual farms might want to look at relative growth rates of corn in their fields, or soil moisture levels, etc. Or they might want to count heads of cattle or sheep, or... or... or.
The point being, outside of weather, which we already know how to get to end users without having them subscribe to an orbital imagery provider service, every customer is different, and what they want from the pixels is different. It's basically the long-tail problem. In order to be profitable you have to fill an enormous number of niche use cases.