There is potential for integrating ML with time series data in industrial applications (things like smelters, reactors etc.), where you have continuous stream of time series measurements from things like gauges and thermocouples. If you can detect (and respond) to changing circumstances faster then a humans in control room reacting to trends or alarms then potential big efficiency gains...

Operator guidance is often based on heuristics - when metric A exceeds X value for Y seconds take action Z. Or rates of change if the signal is changing at a rate of more than x etc.

So in these areas there exists potential for ML solution, especially if it's capable of learning (i.e. last response overshot by X so trim next response appropriately).