• Assembled has updated its Schedule Generation tool to factor AI and other digital agents into call‑center rostering.
• The change aims to reduce the manual work and errors of planning mixed human and digital shifts.
• Managing capacity, handoffs and customer experience becomes more complex as digital labor is included.
• Contact centers should pilot the feature and measure digital agent throughput before full rollout.

What Assembled is doing

Assembled’s Schedule Generation now explicitly factors in AI and other forms of digital labor alongside human agents. The company says the change is designed to streamline the traditionally labor‑intensive process of creating call‑center schedules by recognizing that conversations and tasks can be handled by bots or virtual agents as well as people.

This update reflects a broader shift: workforce planning must account for a blended environment where human staff and digital workers share tasks, hand off interactions, and shape required coverage windows.

Why this matters

Call‑center scheduling has long been a balancing act—matching predicted demand with available staff while minimizing overtime and service gaps. Introducing digital labor complicates that picture: a chatbot can handle a high volume of routine transactions but may require human backup for escalations. By modeling digital agent capacity, Schedule Generation aims to reduce both overstaffing (wasting human time) and understaffing (hurting service).

For operations leaders, that promises two clear benefits:

  • Time savings: less manual rework and fewer ad‑hoc adjustments as digital agents absorb predictable traffic.
  • Better accuracy: rosters that reflect real blended capacity should reduce unexpected service shortfalls.

Potential challenges and risks

Neglecting the differences between human and digital labor is the biggest potential mistake. AI agents do not behave like people: they have different throughput, availability patterns, and failure modes. If planners treat a bot as a one‑to‑one substitute for a human without measuring its effective capacity, schedules can still fail.

Other risks to watch:

  • Misforecasting digital agent performance during peak or novel interactions.
  • Poorly designed handoffs that increase average handle time and customer frustration.
  • Compliance and break scheduling complexities when responsibilities shift between humans and systems.

How teams should approach adoption

Operations teams should pilot the new capability in a limited queue or use case, measure throughput and escalation rates for digital agents, and tune forecasting inputs before scaling. Integrations with workforce management and real‑time monitoring tools will be important to keep schedules accurate as automation changes behavior.

Bottom line

Assembled’s move to explicitly include AI and digital labor in Schedule Generation is a timely response to blended contact centers. It offers a path to faster, more accurate rostering—but only if organizations treat digital agents as a different class of resource and validate assumptions with real data before wide rollout.

Image Referance: https://www.nojitter.com/workflow-automation/assembled-s-schedule-generation-factors-in-ai-agents