Role-Based Programme
RB1339

AI for Operations

Advanced Process Intelligence, Automation & Operational Excellence

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across business operations, service delivery, production, supply chain, workforce, quality, reporting, and continuous improvement.
  • Use AI-assisted analysis to identify operational bottlenecks, capacity constraints, quality issues, resource gaps, risks, cost drivers, and improvement opportunities.
  • Apply AI to process optimisation, workforce planning, inventory decisions, performance reporting, root-cause analysis, operational risk, and workflow automation.
  • Use AI-assisted analytics to improve productivity, service quality, turnaround time, resource utilisation, cost efficiency, resilience, and management visibility.
  • Build responsible AI-enabled Operations workflows with strong governance, validation, control, security, fairness, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchProcess MappingOperational AnalyticsDemand & Capacity AnalysisWorkforce IntelligenceInventory AnalyticsQuality IntelligenceRoot Cause AnalysisRisk AnalysisKPI DashboardsDecision-Support ToolsWorkflow AutomationAI AgentsContinuous Improvement Tools

Who should attend

  • Operations Managers
  • Senior Operations Managers
  • Business Operations Managers
  • Service Operations Managers
  • Production & Manufacturing Managers
  • Supply Chain Operations Professionals
  • Logistics & Warehouse Managers
  • Workforce Management Professionals
  • Operational Excellence Professionals
  • Process Improvement Managers
  • Operations Analysts
  • Quality & Compliance Professionals
  • MIS & Operations Reporting Professionals
  • Operations Transformation Professionals
  • Leaders Responsible for Operational Performance

Prerequisites & Participant Readiness

  • Experience in operations, service delivery, production, supply chain, workforce management, process improvement, or operational reporting
  • Familiarity with workflows, KPIs, capacity, quality, service levels, risk, and performance reviews
  • Basic awareness of Generative AI and common business applications
  • Comfort working with operational, process, workforce, and performance information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, automation, and AI agents
  • Exploring AI applications across planning, execution, quality, reporting, and continuous improvement
  • Distinguishing AI-assisted operational decisions from autonomous operational control
  • Understanding hallucinations, data-quality risks, operational impact, and human accountability
Practical activities
  • Mapping AI opportunities across end-to-end Operations
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Operations teams

Scenarios

High Operating Cost & Low Productivity to AI-Enabled Operations Model

Operational Data → Process Bottlenecks → Workforce Utilisation → Quality Gaps → Cost Drivers → Root Causes → Workflow Redesign → Automation → KPI Tracking

Participants use AI to diagnose declining operational efficiency, identify the major process, workforce, quality, and cost drivers, redesign the operating model, and create measurable improvement actions.

Rapid Growth & Operational Complexity to Scalable Operations Strategy

Demand Growth → Capacity → Workforce → Inventory / Supply → Service Levels → Risks → Automation Opportunities → Governance → Executive Dashboard

Participants use AI to assess an operation facing rapid growth, identify capacity and control gaps, compare scaling scenarios, introduce responsible automation, and create a scalable operational transformation roadmap.

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