Overview
Robotics projects rarely succeed on hardware alone. The practical deployment layer often lives in the workflows around the robot: routing, approvals, operator context and the software that keeps the whole system usable.
A robot can execute a motion or service pattern, but the surrounding business still needs decisions, context and escalation rules.
That is where AI workflow software becomes important: it connects robotics behaviour back to people, process and system state.
- Why hardware-only thinking creates deployment gaps
- Where AI agents and workflow logic sit around robotics programs
- What software layers are usually needed to make robotics usable in practice