Role-Based Programme
RB1321

AI for Workforce Management

Smarter Scheduling, Capacity, Productivity & Service-Level Performance

IMAGE REQUIRED
Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Workforce Management across demand planning, staffing, scheduling, adherence, productivity, and operational reporting.
  • Apply AI to analyse workload volumes, staffing availability, attendance, schedule adherence, service levels, and capacity gaps.
  • Use AI to improve shift planning, intraday workforce decisions, exception analysis, workforce summaries, and management reporting.
  • Develop practical skills for workload balancing, schedule review, productivity analysis, scenario planning, and workforce-performance improvement.
  • Understand responsible AI use, employee-data privacy, fairness, bias, transparency, and human oversight in workforce decisions.

Tools covered

Generative AI AssistantsWorkload AnalysisStaffing Requirement AnalysisShift & Schedule Planning SupportAttendance & Adherence AnalysisCapacity MonitoringProductivity AnalysisIntraday Management SupportWorkforce Performance ReportingScenario Planning

Who should attend

  • Workforce Management Managers
  • Workforce Management Analysts
  • Workforce Planning Professionals
  • Scheduling Analysts
  • Real-Time Management Professionals
  • Operations Managers
  • Service Operations Managers
  • Contact Centre Operations Professionals
  • Capacity Planning Professionals
  • Resource Managers
  • Operations Analysts
  • Team Leaders
  • Performance Management Professionals
  • Operations Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of workforce management, scheduling, or operations
  • Familiarity with staffing, shifts, workload, attendance, service levels, or productivity metrics is helpful
  • Basic spreadsheet, analytical, and digital-tool skills
  • No programming or technical AI knowledge required
  • Prior AI-tool experience is helpful but not mandatory

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Workforce Management
  • Exploring AI support across workload analysis, staffing, scheduling, adherence, and reporting
  • Distinguishing Generative AI from WFM, scheduling, HR, ERP, and workforce analytics systems
  • Understanding AI limitations, hallucinations, bias, and workforce-decision risks
Practical activities
  • Identifying recurring Workforce Management activities suitable for AI assistance
  • Comparing traditional and AI-assisted workforce-management workflows
  • Mapping AI opportunities across the workforce-management lifecycle

Scenarios

Unexpected Demand Surge to Intraday Workforce Response

Live Workload → Staffing Availability → Schedule Adherence → Capacity Gap → Coverage Options → Workforce Actions → Service-Level Impact → Management Update

Participants use AI to analyse a sample intraday demand surge, identify capacity gaps, compare coverage options, and prepare a structured workforce response plan for operational review.

Workforce Performance Gap to Schedule & Productivity Improvement Plan

Workforce Data → Attendance & Adherence → Productivity Analysis → Coverage Gaps → Possible Causes → Schedule Adjustments → Improvement Actions → Leadership Summary

Participants use AI to analyse sample workforce data, identify operational performance gaps, and develop an evidence-based schedule and productivity improvement plan while preserving human oversight for employee-impacting decisions.

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