Role-Based Programme
RB1322

AI for Workforce Management

Forecasting, Scheduling, Real-Time Performance & Capacity Optimisation

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for workforce forecasting, staffing, scheduling, intraday management, and operational control.
  • Apply AI to analyse workload demand, staffing requirements, schedule adherence, shrinkage, occupancy, utilisation, and service performance.
  • Use AI to improve roster planning, real-time workforce decisions, exception handling, staffing-gap analysis, and reporting.
  • Strengthen workforce-management decisions through scenario modelling, trend analysis, capacity optimisation, and performance intelligence.
  • Apply responsible AI practices related to employee data, privacy, fairness, workforce decisions, accuracy, and human oversight.

Tools covered

Generative AI AssistantsWorkforce Forecast AnalysisStaffing Requirement AnalysisScheduling IntelligenceIntraday ManagementAdherence AnalysisShrinkage AnalysisCapacity & Occupancy AnalysisWorkforce Performance AnalyticsScenario PlanningOperational ReportingExecutive Summarisation

Who should attend

  • Workforce Management Managers
  • Workforce Management Analysts
  • Workforce Planning Professionals
  • Scheduling & Rostering Specialists
  • Real-Time Management Analysts
  • Capacity Planning Professionals
  • Operations Managers
  • Service Operations Managers
  • Contact Centre Operations Professionals
  • Workforce Analysts
  • Operations Analysts
  • Resource Management Professionals
  • Team Leaders & Supervisors
  • Shared Services Operations Professionals
  • Workforce Operations Leaders

Prerequisites & Participant Readiness

  • Experience in workforce management, scheduling, forecasting, operations, service delivery, or capacity planning
  • Familiarity with staffing, workload, shifts, adherence, service levels, and workforce KPIs
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret workforce and operational data
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across forecasting, staffing, scheduling, intraday control, and reporting
  • Understanding how AI differs from WFM, HRMS, scheduling, and operational analytics platforms
  • Recognising hallucinations, biased recommendations, and limitations in workforce decisions
Practical activities
  • Mapping the workforce-management cycle to practical AI applications
  • Identifying high-value versus high-risk WFM use cases
  • Comparing traditional and AI-assisted workforce-management workflows

Scenarios

Demand Surge to Intraday Workforce Recovery

Actual Demand → Forecast Variance → Staffing Gap → Adherence Review → Capacity Options → Intraday Actions → Service Recovery → Performance Review

Participants use AI to analyse a simulated unexpected increase in workload, identify staffing and adherence gaps, evaluate real-time interventions, and develop a structured service-recovery plan.

Recurring Staffing Mismatch to WFM Optimisation Strategy

Historical Workload → Forecast Accuracy → Staffing Requirement → Schedule Analysis → Shrinkage → Adherence → Scenario Modelling → Workforce Optimisation Plan

Participants use AI to analyse persistent overstaffing and understaffing patterns, identify weaknesses across forecasting, scheduling, and shrinkage assumptions, and develop a structured workforce-management optimisation plan.

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