Agentic AI for Business Leaders: Identifying, Piloting & Governing AI Agents Training Course

Course Overview

Learning Objectives

• Explain what agentic AI is and how AI agents differ from AI assistants and conventional automation.
• Identify business processes where agents can add value and those where they should not be used.
• Screen and prioritize agent use cases by value, feasibility, data readiness, and risk.
• Set the appropriate level of autonomy and human oversight for each use case.
• Build a business case with realistic costs, benefits, and assumptions that a pilot can test.
• Design a time-bound pilot with a clear scope, success criteria, and stop conditions.
• Define accountability for agent actions and decisions across business, technology, and risk functions.
• Set requirements for access to data and systems, security, privacy, and audit trails.
• Evaluate vendors and platforms with leadership-level criteria rather than technical detail.
• Assess the impact of agents on roles, skills, and ways of working, and lead the change that follows.
• Establish the policies and controls that must be in place before agents act on behalf of the organization.
• Measure pilot results with indicators that inform the decision to scale, adjust, or stop.
• Prepare an adoption roadmap that aligns agent initiatives with strategy and governance.

Who Should Attend

Learning Outcomes

• By the end of this course, participants will be able to:
• Explain agentic AI and how AI agents differ from AI assistants and conventional automation.
• Identify processes in their organizations that suit agents and those that do not.
• Prioritize agent use cases using value, feasibility, data readiness, and risk criteria.
• Set autonomy levels and human oversight points that match the risk of each use case.
• Prepare a business case with costs, benefits, and assumptions that a pilot can test.
• Write a pilot charter with scope, owners, success criteria, and stop conditions.
• Define accountability for agent actions across business, technology, and risk functions.
• Specify access, security, privacy, and audit trail requirements for agents.
• Evaluate vendors and platforms using leadership-level criteria.
• Plan for workforce impact and change management as agents are introduced.
• Decide whether to scale, adjust, or stop an agent initiative based on pilot evidence.
• Develop an adoption roadmap that links agent initiatives to strategy and governance.

Course Outline