Description:

Generative AI and Agentic AI are reshaping how organizations approach planning, analysis, decision support, and strategic execution. Generative AI can help teams synthesize information, generate ideas, evaluate options, and accelerate research and communication. Agentic AI extends these capabilities by enabling systems to carry out multi-step tasks, use tools, retrieve information, and support more dynamic workflows.

This session introduces foundational to intermediate concepts in Generative AI and Agentic AI, with a focus on strategic applications relevant to planning and business strategy. Participants will explore how these technologies can support activities such as scenario analysis, strategic planning, decision support, knowledge synthesis, and workflow coordination.

The session emphasizes practical business relevance and is designed to balance conceptual understanding with applied examples that help participants identify meaningful opportunities for AI adoption in their own contexts. Participants will leave with a stronger understanding of Gen AI and Agentic AI, a practical view of business use cases, and a clearer framework for evaluating where these tools can create value responsibly and effectively.

Duration:

4 hours

Course Code: BDT 619

Learning Objectives:

After completing this course, participants will be able to:

1. Understand foundational to intermediate concepts in Generative AI and Agentic AI
2. Explain how Agentic AI differs from traditional chatbots and prompt-based AI interactions
3. Identify the core components of agentic systems, including instructions, planning, memory, tools, and feedback loops
4. Recognize strategic applications of Gen AI and Agentic AI in planning and business strategy
5. Use AI to support research, synthesis, scenario thinking, and decision support
6. Evaluate practical use cases where AI can improve planning efficiency and strategic insight
7. Understand the strengths and limitations of these technologies in real-world business settings
8. Identify risks such as hallucinations, poor reasoning, insecure data handling, and over-reliance on AI-generated outputs
9. Apply a framework for assessing where AI use cases are feasible, valuable, and appropriate for their teams

General familiarity with AI concepts is recommended. No technical background in AI development is required. Suitable for professionals involved in planning, strategy, innovation, operations, transformation, and related business or technical functions.

Course Outline:

Introduction to Generative AI and Agentic AI

1. Overview of Generative AI and Agentic AI
2. How Generative AI supports content generation, synthesis, and reasoning assistance
3. How Agentic AI extends AI capabilities through multi-step workflows and tool use
4. Differences between chat-based AI, assistants, workflows, and agents
5. Capabilities and limitations of current AI systems
6. How these technologies are changing planning and strategic work

Foundational Concepts in Generative AI

1. How large language models work at a practical level
2. Prompts, context, and output generation
3. Strengths of Gen AI for summarization, ideation, drafting, and analysis
4. Common limitations, including hallucinations and inconsistent outputs
5. The importance of prompt design and context quality
6. When Generative AI is useful and when traditional methods may still be preferable

Foundational Concepts in Agentic AI

1. What makes a system “agentic”
2. Instructions, goals, and task decomposition
3. Memory and context management
4. Tool use, retrieval, and interaction with external systems
5. Decision-making, iteration, and feedback loops
6. Human-in-the-loop design and oversight
7. When an agentic approach is appropriate versus when a simpler AI workflow is sufficient

Effective Prompting Techniques

1. Writing effective prompts for business and planning tasks
2. Structuring requests for clearer outputs and more useful analysis
3. Using follow-up prompts to refine ideas and challenge assumptions
4. Prompting for summaries, comparisons, recommendations, and structured outputs
5. Improving output quality through context, constraints, and iteration

Strategic Applications for Planning and Business Strategy

1. Supporting trend analysis and strategic research
2. Synthesizing internal and external information for planning
3. Generating options, alternatives, and strategic hypotheses
4. Scenario exploration and what-if analysis
5. Assisting with strategic communications, summaries, and executive-ready outputs
6. Using AI to improve planning workflows, coordination, and knowledge access

Practical Demonstrations

1. Demonstration: Using Generative AI to synthesize strategic inputs and generate planning insights
2. Demonstration: Comparing a basic prompt workflow with a more agentic multi-step workflow
3. Interactive exercise: Evaluating sample use cases for feasibility, value, and risk in a business context

Risks and Responsible Use

1. Identifying inaccurate, incomplete, or misleading outputs
2. Managing confidentiality and sensitive information
3. Understanding the risks of over-reliance on AI-generated content
4. Knowing when human judgment must remain central
5. Recognizing the limits of current AI in strategic and planning contexts

Training material provided: Yes (Digital format)