I interviewed for a company which used time series modelling to predict engine failure on ships. Though they didn't call it that, they called it just "AI" and weren't familiar with the time series literature at all. (Neither was I, but I did at least know that the time series literature was a thing.) They just used a bunch of sensors attached to the engine.

That seems like a scenario where there wouldn't be external sources of information capable of improving your predictions. It also seemed to me like a scenario where good old fashioned statistical methods would outperform LSTMs, which was what they used.

(I didn't get the job - I was offered it, but they rescinded their offer at the last moment, supposedly because their investors had insisted they should hire a web developer instead.)