Agentic AI Strategies and Applications
Program Details
- Overview
- Academics
- What You'll Learn
Agentic AI Strategies and Applications is designed to equip you with practical skills to immediately improve productivity using AI. This program focuses on autonomous AI agents—systems that can take goals, break them into steps, use tools, and get work executed with minimal human intervention. As organizations increasingly seek “AI that gets things done,” you will gain hands-on experience building and deploying agentic AI solutions that deliver real business impact. The program begins with essential foundations in modern AI and foundation models (including large language models that power agentic workflows), presented in an accessible way for non-technical professionals. From there, you will learn to map workflows, select the right tools, and translate complex problems into structured agentic solutions.
Through real-world business cases, simulations, and hands-on low/no-code exercises, you will build the ability to identify opportunities, develop agentic workflows, and evaluate outcomes based on business impact.
Who Should Register
Who Should Register
Business professionals, managers, senior leaders in functional areas, team leaders, consultants and career-advancing professionals in corporate environments, including Kelley School alumni looking to add AI capabilities to their toolkit. This program is designed for professionals seeking to leverage autonomous AI agents for improving productivity, streamlining operations, and making better decisions. No programming or technical background required.
Why Choose Kelley School of Business
Kelley’s approach to AI is distinguished by comprehensive coverage of:
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A thorough understanding of how to scope and measure AI performance in complex application environments (e.g., business, healthcare, cybersecurity)
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Modern data practices, including data generating processes, exploration approaches, and services identification
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Fundamental foundation models that power agentic AI workflows
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Agentic AI strategy and implementation, with sample applications
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Business impact measurement, including ROI analysis, stakeholder identification, and KPI articulation
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Governance considerations, including use cases, security, and monitoring.
Curriculum
Course Overview
Module 1: Foundations: AI, Business Contexts, and the Agentic Mindset
Understanding AI as a reasoning partner; plus business application environments
Topics
- Background and history/evolution of AI
- Non‑technical introduction to LLMs and foundation models
- Chatbot vs. agent: what makes an agent different
- Identifying use cases in organizations and scoping/specifying business problems
Module 2: Autonomous Agents: Design, Deployment, and Hands-On Practice
Building and working with autonomous AI agents
- Building autonomous agents: from prompt to full autonomy
- Hands-on practice with agent platforms: delegating tasks, providing context, and evaluating agent output
- Agent reliability, guardrails, and knowing when to trust (or override) agent decisions
- How agents use tools and produce reliable output
- Reasoning and planning
- Connecting multiple AI steps into end-to-end workflows
- Memory management and human‑in‑the‑loop
Module 3: Building Agentic Systems: Tools, Planning, RAG, Memory and Orchestration
From single agents to multi-agent orchestration
Topics
- How agents use tools and produce reliable output
- Reasoning and planning
- Connecting multiple AI steps into end-to-end workflows
- Memory management and human‑in‑the‑loop
Module 4: Enterprise Reality: Evaluation, Deployment, Security, Governance, and Economics
Accountability, Risk Management, and Organizational Readiness
Topics
- Agentic AI Deployment and Monitoring
- Evaluation and Governance
- Security and Privacy
Applied Labs/Activities:
- Hands-on exercises applying agentic AI to real business scenarios
- Guided projects where participants build and deploy their own AI agents
What You'll Learn
Participants will learn how to:
- Understand what Agentic AI is and why it matters for corporate productivity
Understand how autonomous AI agents differ from chatbots, RPA, and traditional automation, and know when to use each. - Identify where Agentic AI can create real business value
Recognize high impact productivity use cases across functions and industries. - Translate workflows into Agentic AI opportunities
Break down real business workflows into well-defined, buildable agentic AI use cases. - Design and govern Agentic AI workflows responsibly
Define appropriate levels of autonomy, human oversight, and accountability. - Evaluate Agentic AI solutions and platform options
Assess solution approaches at a business level without needing technical expertise. - Define success metrics and business impact
Define KPIs, measure business impact, and calculate ROI for Agentic AI initiatives.