Business Transformation with AI Agents Program: Increase Productivity & Revenue Through Innovation and Automation Part 1 – Basics

This two-day course introduces participants to AI Agents, their foundations in modern generative AI, and how to deploy them responsibly to drive productivity, automation, and new revenue opportunities. 

Day 1 : Focuses on core concepts, market perspectives, governance, and a guided demonstration of key agent building blocks (tools, memory, retrieval-augmented generation, actions). 

Day 2 : Is a hands-on Use Case Activation Lab where teams map business processes, identify and prioritize AI Agent opportunities, define success metrics and constraints, and produce a practical blueprint and pitch for next steps. The program is tailored for business professionals, innovation leaders, digital transformation teams, and students.

Day 1 : AI Agent Fundamentals & Business Context 

• AI landscape overview: GenAI and AI Agents; crash course on LLMs for non-technical audiences
• Foundations of AI Agents: architectures, decision-making, and capabilities 
• Types of AI Agents and market perspectives 
• Traditional automation vs AI Agents: strategic comparison and selection logic 
• Real-world applications and industry case studies 
• Introduction to governance, ethics, and security for AI Agents 
• Basic technological architecture and frameworks overview 
• Guided demonstration: agent building blocks in practice (tools, memory, RAG, actions) 
• Mini-exercise: evaluate an agent concept for value, feasibility, and risk 
• End-to-end example: Customer Support Triage Agent (framing, business case, risks, success metrics) 
• Readiness checklist for the Day 2 workshop 

Day 2 : Use Case Activation Lab & Pitch 

• Business mapping techniques for AI Agent use case identification 
• Map AI Agent capabilities to business needs  
• Afternoon workshop 
• Prioritize opportunities : quick wins vs strategic initiatives (ROI logic) 
• Define success metrics, data needs, and constraints 
• Complete a blueprint canvas (scope, stakeholders, governance) 
• Prepare a short presentation/pitch 
• Group presentations with facilitator feedback and discussion 
• Final action planning, wrap-up, and Q&

• Understand how AI Agents fit into the modern AI landscape (GenAI and LLMs) and how they create business value 
• Explain the foundations and types of AI Agents, including key building blocks (tools, memory, RAG, actions) 
• Compare traditional automation and AI Agents to choose the right approach for a given business problem
• Recognize governance, ethical, security, and risk considerations for AI Agent deployment 
• Identify and map AI Agent opportunities in business processes and operating models 
• Prioritize use cases based on impact, feasibility, and ROI (quick wins vs strategic initiatives) 
• Define success metrics, data requirements, and constraints for an AI Agent initiative 
• Produce a practical AI Agent blueprint canvas and present a short pitch with next steps

Blended: lecture-style presentations, guided demonstrations, group discussions, case studies, and an interactive Use Case Activation Lab with templates and group presentations.