AI moves labor management beyond static standards and periodic performance reviews toward continuous, data-driven optimization. It can identify patterns across shifts, tasks and individuals, flagging inefficiencies before they compound.
AI also improves task allocation by matching the right associate to the right activity based on skill, availability and current workload. Over time, the system learns from operational data to refine labor standards and planning accuracy, improving throughput without adding headcount.
The Infios Archer, takes this further at the individual level. Rather than relying on supervisors to review data manually and deliver coaching when time allows, the agent analyzes labor and operational performance data, identifies coaching opportunities for every worker and generates personalized feedback and suggested guidance that team leads can deliver during or after the shift. The result is more consistent, timely coaching for every associate without managers having to run the analytics themselves.