Role-Based Programme
RB1295

AI for Business Operations

Advanced Process Intelligence, Operational Automation & Performance 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, process management, planning, performance monitoring, reporting, and continuous improvement.
  • Use AI-assisted analysis to identify operational bottlenecks, inefficiencies, capacity constraints, process risks, cost drivers, and performance gaps.
  • Apply AI to workflow optimisation, resource planning, management reporting, root-cause analysis, operational reviews, and decision support.
  • Use AI-assisted analytics to improve productivity, turnaround time, service quality, resource utilisation, cost efficiency, and management visibility.
  • Build responsible AI-enabled Business Operations workflows with strong governance, validation, privacy, control, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchProcess MappingOperational AnalyticsKPI IntelligenceRoot Cause AnalysisForecasting ConceptsWorkflow OptimisationResource PlanningRisk AnalysisManagement ReportingDecision-Support ToolsWorkflow AutomationAI AgentsContinuous Improvement Tools

Who should attend

  • Business Operations Managers
  • Operations Managers
  • Business Operations Analysts
  • Operations Analysts
  • Business Process Managers
  • Operational Excellence Professionals
  • Process Improvement Managers
  • Business Support Managers
  • Shared Services Professionals
  • Business Planning Professionals
  • Operations Programme Managers
  • Performance Management Professionals
  • Business Transformation Professionals
  • Operations Excellence Leaders
  • Leaders Responsible for Business Operations & Operational Performance

Prerequisites & Participant Readiness

  • Experience in business operations, process management, operational excellence, business analysis, or performance management
  • Familiarity with workflows, KPIs, management reporting, resource planning, and operational reviews
  • Basic awareness of Generative AI and common business applications
  • Comfort working with operational, process, performance, and business information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across planning, processes, reporting, controls, and operational improvement
  • Distinguishing AI-assisted operational management from fully automated business decisions
  • Understanding hallucinations, data quality, operational risk, and human accountability
Practical activities
  • Mapping AI opportunities across the Business Operations lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Business Operations teams

Scenarios

Inefficient Business Process to AI-Enabled Operating Model

Current Process → Bottlenecks → Rework → KPI Analysis → Root Causes → Future-State Workflow → Automation Opportunities → Performance Measures

Participants use AI to analyse a high-effort business process, identify inefficiencies and root causes, redesign the workflow, and create a controlled AI-enabled operating model.

Rising Operational Costs to Performance Improvement Strategy

Operational Data → Cost Drivers → Capacity → Productivity → Risk → Improvement Opportunities → Business Case → Executive Dashboard → Action Plan

Participants use AI to diagnose rising operational costs, identify resource and process drivers, prioritise improvement initiatives, and build a measurable performance and cost-optimisation roadmap.

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