I think it is important to remember that "decades" here means <20 years. Remember that in 2004 it was considered sufficiently impossible that basically no one had a car that could be reliably controlled by a computer, let alone driven by computer alone:

https://en.wikipedia.org/wiki/DARPA_Grand_Challenge_(2004)

I also think that most job domains are not actually more nuanced or complex than driving, at least from a raw information perspective. Indeed, I would argue that driving is something like a worst-case scenario when it comes to tasks:

* It requires many different inputs, at high sampling rates, continuously (at the very least, video, sound, and car state)

* It requires loose adherence to laws in the sense that there are many scenarios where the safest and most "human" thing to do is technically illegal.

* It requires understanding of driving culture to avoid making decisions that confuse/disorient/anger other drivers, and anticipating other drivers' intents (although this can be somewhat faked with sufficiently fast reaction times)

* It must function in a wide range of environments: there is no "standard" environment

If we compare driving to other widespread-but-low-wage jobs (e.g. food prep, receptionists, cleaners) there are generally far more relaxed requirements:

* Rules may be unbreakable as opposed to situational, e.g. the cook time for burgers is always the same.

* Input requirements may be far lower. e.g. an AI receptionist could likely function with audio and a barcode scanner.

* Cultural cues/expectations drive fewer behaviors. e.g. an AI janitor just needs to achieve a defined level of cleanliness, not gauge people's intent in real-time.

* Operating environments are more standardized. All these jobs operate indoors with decent lighting.