Can AI handle real support tickets without human approval

Been messing with some ai agent stuff for our support queue. the idea is it suggests fixes for common tickets and a human approves before it runs anything. sounds smart on paper but in practice im not fully convinced yet. right now its in simulation mode where it reviews tickets, pulls context, and proposes full resolutions.

most of the time it’s fine for simple stuff like password resets, access issues, and basic troubleshooting. but once things get a bit unclear or the ticket is poorly written, it starts making assumptions that don’t always hold up. we’ve seen a pretty consistent split where the majority of suggestions are usable, but there’s still a small chunk where it either overreaches or picks the wrong path from similar past cases. nothing catastrophic in testing, but enough to make you pause before letting it execute anything for real.

had one case where a user just said “can’t access system” and it jumped straight to suggesting a full account reset and permission rebuild, which would’ve been way too aggressive for the actual issue. on paper the system looks good because the success rate is high in controlled tests, but real tickets are messy and unpredictable, and that’s where the gaps show up.

how do you decide when something like this is safe enough to move from simulation to real execution without humans approving every step?