Agentic AI for Business and Management

Course Category : Governance

An advanced programme for understanding Agentic AI and leveraging its capabilities to support decisions, automate workflows, and strengthen efficiency and governance across business and management environments.
Duration: 5 Days
Level: Advanced

Introduction

The shift from AI systems that primarily respond to instructions toward systems capable of planning and executing sequences of actions is reshaping the management of organisational processes. Agentic AI introduces a model in which intelligent agents can pursue defined objectives, use tools, coordinate multi-step tasks, and operate within established boundaries.
This course examines the managerial and operational foundations of Agentic AI, including agent architecture, multi-agent workflows, business use-case selection, human oversight, risk management, and governance. It enables participants to evaluate opportunities for deploying AI agents across management, decision-making, and organisational processes while maintaining appropriate accountability, transparency, and responsible AI controls..

Targeted Audience

Executives and Department Managers
Digital Transformation and AI Managers
Business Development and Strategy Managers
Operations and Organisational Excellence Managers
Project and Programme Managers
Business Analysts and Management Consultants
Innovation and Transformation Professionals
AI Governance and Risk Professionals

Targeted Skills

Understanding Agentic AI architectures and capabilities
Analysing suitable enterprise use cases for AI agents
Designing agent-based workflows
Distinguishing automation, Generative AI, and Agentic AI
Evaluating single-agent and multi-agent models
Defining autonomy and human oversight levels
Managing AI agent governance and risks
Developing an enterprise Agentic AI adoption roadmap

Expected Outcomes

Explain the fundamental principles of Agentic AI and its role in business environments.
Identify processes and decisions suitable for intelligent-agent deployment.
Analyse agent architecture components, including goals, planning, memory, and tools.
Design conceptual enterprise workflows based on single or multiple agents.
Evaluate appropriate autonomy and human-oversight levels for different use cases.
Identify operational, managerial, and ethical risks associated with AI agents.
Establish an initial governance framework for enterprise Agentic AI.
Develop a phased roadmap for Agentic AI adoption.

Training Topics Index

Agentic AI concepts and evolution within the AI landscape
Differences between automation, Generative AI, and intelligent agents
Autonomy, goals, decisions, and actions
Core components of an intelligent agent
Enterprise value and managerial use cases

Agent cycle perception, planning, execution, and evaluation
Goals, instructions, context, and memory
Tool use and enterprise information sources
Designing multi-step agent workflows
Single-agent and multi-agent patterns

Executive and managerial decision-support agents
Administrative task and workflow coordination
Agents for information analysis and reporting
Agent applications across customer service, resources, and operations
Selecting use cases based on value, complexity, and risk

Defining autonomy and authority levels
Human-in-the-Loop and human approval points
Risks of errors and unintended agent actions
Accountability, transparency, documentation, and decision logs
Privacy, security, and responsible-use controls

Assessing organisational and operational readiness
Prioritising an Agentic AI use-case portfolio
Operating models, roles, and responsibilities
Performance, value, and risk indicators
Developing a phased adoption, scaling, and governance roadmap

Course Features

Updated and Interactive Content
Hypothetical Examples and Case Studies
Pre- and Post-assessments to Measure Impact
Verified Certificate with a QR Verification Code

Agentic AI for Business and Management