AI workforce scheduling for continuous operations watches rosters, absences, demand, and rules as live signals, projects coverage gaps before they open, and drafts the corrective move — a float, a relief, a shift market post — with its evidence and compliance basis attached, for a coordinator to approve. MAIA runs this loop on the systems an operation already uses, with collective-agreement and fatigue rules encoded as checkable policy.
The half-life of a staffing decision
In hospitals, terminals, and depots, staffing decisions expire in minutes: the float that solves the 14:00 gap is gone by 14:20. Batch scheduling tools optimise last week; a decision loop that senses continuously acts inside the window while options still exist.
The compliance layer is what makes speed safe: agreement rules, qualification requirements, and rest constraints are encoded so that every drafted move arrives pre-checked, with the clause that permits it cited.
Operators stay in command
Coordinators approve, edit, or reject every consequential move — and each override is recorded with its reason, which makes the system's next draft smarter and the grievance file shorter. The measure of success is not fewer humans; it is fewer 03:00 surprises.