Agentic AI for Business Leaders

Agentic AI empowers business leaders to harness intelligent autonomous systems for strategic decision-making and innovation in a competitive market.

Artificial IntelligenceDuration: 6 Hours Certificate on Completion
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$ 249
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About This Course

This course is designed for business leaders, executives, and decision-makers who want to understand how Agentic AI can transform organizations. Unlike traditional automation or generative AI chatbots, agentic systems can reason, plan, use tools, and collaborate—making them powerful enablers of productivity and innovation.

Through real-world frameworks, business case examples, and a hands-on capstone project, learners will gain the knowledge to spot opportunities, evaluate feasibility, manage risks, and build roadmaps for AI adoption in their organizations—without requiring coding skills.

Course Objectives

Define and explain Agentic AI and how it differs from chatbots, automation, and standard generative AI.

Assess organizational readiness by evaluating data maturity, culture, and grassroots AI usage.

Identify business problems suitable for agentic systems and avoid over-engineering for trivial or high-risk tasks.

Understand key technical concepts (hallucinations, tokens, RAG, guardrails, memory, etc.) in a business-friendly way.

Evaluate AI solutions and vendors, avoiding “agent washing” and measuring ROI, cost, and reliability.

Build an AI governance and risk framework, ensuring accountability, ethical use, and safety in adoption.

Design a practical roadmap for pilot projects and scaling agentic AI initiatives.

Apply learning in a capstone project by analyzing and enhancing an AI-powered expense reporting system.

Course Prerequisites

No coding or technical background required – the course is designed for business decision-makers. Basic familiarity with AI/automation concepts (chatbots, data-driven tools) is helpful but not mandatory. Comfort with strategic thinking and business analysis, since the focus is on applying AI to organizational contexts. An open mindset toward innovation, experimentation, and organizational change.

Target Audience

Business leaders & executives looking to align AI strategies with business goals.

Department heads & managers in IT, Operations, Finance, HR, Customer Support, etc. who want to leverage AI in workflows.

Innovation & strategy professionals responsible for driving digital transformation.

Consultants & advisors working with organizations on AI adoption.

Non-technical leaders who want to “speak the AI language” and engage effectively with technical teams and vendors.

Curriculum

0 Lessons | 6 Hours
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Agentic AI for Business Leaders

Course Overview & Introduction

  1. Introduction to the course and objectives
  2. Framing the gap between AI jargon and business decisions
  3. What “Agentic AI” is vs. traditional chatbots and automation
  4. Why organizations need agentic systems now

Understanding Agentic AI (TQ: Agentic AI)

  1. Definition and scope of agentic AI
  2. Key differences between agentic systems and generative AI / rule-based automation
  3. Core properties of agents:
    "Autonomy;\nDecision making;\nTool use;\nPlanning;\nMemory;\nCollaboration."

Is Your Organization Ready?

  1. Assessing internal maturity (data, culture, experimentation readiness)
  2. Identifying “hidden AI champions” and grassroots AI usage in teams
  3. Approaches to budgeting, funding, and piloting small AI experiments

Technical Essentials for Leaders (No Coding Required)

  1. Core technical concepts: hallucinations, tokens, guardrails, memory, context windows
  2. Basics of prompt design and retrieval-augmented generation (RAG)
  3. Context management and multi-step reasoning in agents
  4. Recognizing failure modes: where and why agents go wrong

Spotting the Right Problems for Agentic AI

  1. Business problem types suited for agentic AI:
    "Adaptive workflows;\nComplex decision making;\nOrchestration tasks."
  2. When agentic AI is not the right fit:
    "High-stakes or regulated environments. \nTrivial repetitive tasks better handled with simpler automation."
  3. Balancing scope, safety, and risk when selecting pilots

Evaluating Solutions & Talking Tech

  1. How to decode vendor claims and avoid “agent washing”
  2. Build vs. buy vs. partner decisions for AI adoption
  3. Business-relevant metrics to track:
    "Performance and reliability;\nInference cost and efficiency;\nLatency and response times."

Ethics, Governance & Risk

  1. Handling failures at scale: graceful degradation and human fallback
  2. Building accountability frameworks and oversight mechanisms
  3. Addressing risks:
    "Bias and fairness;\nSafety and adversarial inputs;\nAbuse prevention and audit trails."

Your Agentic AI Roadmap

  1. Moving from pilots to scaled adoption
  2. Planning 90-day wins vs. long monolithic AI roadmaps
  3. Selecting an initial “boring but impactful” problem
  4. Structuring governance, stakeholder buy-in, and cross-functional teams
  5. Resourcing considerations for long-term sustainability

Capstone Project – Agentic Expense Reporting System

  1. Analyze an existing AI-powered expense reporting system with agentic elements
  2. Identify enhancements:
    "New agent insertion points;\nImproved integration strategies;\nStronger safeguards."
  3. Define metrics for success
  4. Plan fallback strategies, risk mitigation, and rollout roadmap

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