- writing and refactoring code. probably 50 times a day now - improving documentation across the company - summarizing meetings automatically with follow ups - drafting most legal work before a lawyer edits (saved 70% on legal bills) - entity extraction and data cleanup for my users
Probably an unpopular opinion, but I think the most efficient companies of the future will tackle the ironies of automation effectively: Carefully designing semi automation that keeps humans in the loop in a way that maximises their value - as opposed to just being bored rubber stamping the automation without really paying attention).
It's a clutch that will help you cope with the problem. But the real value is on fixing the actual issue.
If your meeting is aimed at producing "general understanding", it's already a dangerous one, and the understanding should go to the correct documentation (what is best done during the meeting). Otherwise, it should produce "focused understanding" between a few people and with immediate application.
If all you take from it is notes, well, I'm really sure that your team won't go digging through meetings notes every time they need to learn about some new context. Meeting notes are useful for CYA only, and if people feel safe they'll be filled directly at /dev/null.
None of that is marketed as "AI." It's just a thing the computer does. The single most valuable application of deep learning so far (content recommenders) is a cultural phenomenon, but it’s not referred to as “AI” but rather “the algorithm.”