Role-Based Programme
RB1103

AI for Business Operations

Advanced Operational Intelligence, Process Optimisation & Business Performance

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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 analysis, coordination, and decision-making.
  • Use AI-assisted analysis to identify operational bottlenecks, recurring issues, capacity constraints, productivity gaps, risks, and improvement opportunities.
  • Apply AI to process optimisation, operational reporting, cross-functional coordination, resource planning, and business reviews.
  • Evaluate AI opportunities based on business value, feasibility, data readiness, operational risk, governance, and measurable outcomes.
  • Build an actionable AI-enabled Business Operations framework that improves execution, productivity, visibility, and continuous improvement.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument IntelligenceOperational Data AnalysisProcess AnalysisPerformance DashboardsRoot Cause AnalysisScenario PlanningWorkflow AutomationKnowledge AssistantsAI AgentsDecision-Support Tools

Who should attend

  • Business Operations Professionals
  • Business Operations Managers
  • Senior Business Operations Managers
  • Operations Strategy Professionals
  • Business Excellence Professionals
  • Operational Excellence Professionals
  • Business Process Professionals
  • Operations Analysts
  • Business Performance Professionals
  • Program Operations Professionals
  • Shared Services Professionals
  • Business Unit Operations Teams
  • Transformation Professionals
  • Process Improvement Leaders
  • Senior Managers Responsible for Business Operations

Prerequisites & Participant Readiness

  • Experience in business operations, process management, business excellence, planning, or performance management
  • Familiarity with operational KPIs, workflows, management reports, and cross-functional coordination
  • Basic awareness of Generative AI and business analytics
  • Comfort working with operational documents, spreadsheets, and business data
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, automation, and AI agents
  • Exploring AI applications across business operations, planning, reporting, coordination, and improvement
  • Distinguishing AI assistance, analytics, automation, and autonomous execution
  • Understanding hallucinations, data limitations, context gaps, and human accountability
Practical activities
  • Mapping AI opportunities across the Business Operations lifecycle
  • Identifying operational activities suitable for augmentation or automation
  • Creating an AI opportunity map for Business Operations

Scenarios

Operational Performance Gap to Process Improvement

Performance Gap → KPI Analysis → Process Mapping → Root Cause Analysis → Improvement Options → Resource & Risk Assessment → Future-State Workflow → Management Action Plan

Participants use AI to diagnose an operational-performance problem, analyse the underlying process, identify root causes, redesign the workflow, and create a measurable improvement plan.

AI-Enabled Business Operations Transformation

Business Priorities → Operational Challenges → AI Use Cases → Value & Feasibility → Business Case → Governance → Workflow Redesign → Prioritisation → 12–24 Month Roadmap

Participants build an AI-enabled Business Operations roadmap covering productivity, process optimisation, service quality, cross-functional execution, workflow automation, governance, and measurable business outcomes.

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