Of course software can affect the physical world: Google Maps changes traffic patterns; DoorDash teleports takeoff food right to my doorstep; the weather app alters how people dress. This list is un-ending. But these effects are always second-order. Humans are always there in the background bridging the gap between bits and atoms (underpaid delivery drivers in the case of doordash).
The more interesting question is whether AI can __directly__ impact the physical world with robotics. Gemini can wax poetic about optimizing fertilizers usage, grid spacing for best cross-pollination, the optimum temperature, timing, watering frequency of growing corn, but can it actually go to Home Depot, purchase corn seeds, ... (long sequence of tasks) ..., nurture it for months until there's corn in my backyard? Each task within the (long sequence of tasks) is "making PB&J sandwich" [1] level of difficulty. Can AI generalize?
As is, LLMs are better positioned to replace decision-makers than the workers actually getting stuff done.
[1] http://static.zerorobotics.mit.edu/docs/team-activities/Prog...