IIM Bangalore - Executive Education

Generative AI and Agentic AI with Business Applications (Batch-5)

IIM Bangalore - Executive Education

Data Analytics
Partner Institution

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About Programme

Mode of Delivery: In-person deliveryCase Studies – Real-life use cases; Demonstrations; ApplicationsHands-on with Tools/Platform/libraries

This programme blends theory, hands-on development, and real-world applications, focusing on:

Programme OverviewThis course goes beyond traditional Generative AI by integrating Agentic AI—AI systems that demonstrate autonomy, goal-directed behavior, and adaptability. Unlike conventional Generative AI applications that require explicit human prompts at every step, Agentic AI enables autonomous decision-making, planning, and execution, making AI systems more dynamic and responsive.

End-to-End AI Autonomy – Learn how to design AI agents that can act independently, make decisions, and iterate without constant human intervention.
Combining Generative & Agentic AI – Understand how LLMs power agent-based architectures and how to use tools like GitHub Copilot/Cursor, ChatGPT, Perplexity, Firecrawl, ManusAI etc. frameworks such as LangGraph/Autogen/CrewAI/ManusAI agents and models such as Deepseek, OpenAI (including reasoning models), Grok, Llama, Mistral AI etc.
Hands-on, Industry-Focused – Engage in real-world projects where AI agents perform complex tasks such as knowledge retrieval, task decomposition, and multi-agent collaboration.
Enterprise & Product Integration – Explore how businesses are adopting Agentic AI for automation, customer service, cybersecurity, and more.

Now is the time to bridge the gap between static generative AI models and dynamic agent-based AI systems. This course will prepare participants to:

Build, fine-tune, and deploy agentic AI models
Integrate AI agents with enterprise applications
Understand the ethical and governance challenges of autonomous AI
Develop Strategies for Generative and Agentic AI Adoption:Build a roadmap for integrating Generative and Agentic AI into the organization. Understand data governance and infrastructure requirements for AI-driven innovation. Align technology, platform, and talent strategies with AI objectives.
Understand the Fundamentals and Applications of Generative and Agentic AI:Explore the principles and applications of Generative AI, including content creation, simulation, and personalization. Gain insights into Agentic AI systems, focusing on autonomous decision-making, multi-agent systems (MAS), and adaptive problem-solving. Learn techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning for domain-specific AI solutions.
Identify and Prioritize Use Cases:Recognize high-impact applications of Generative and Agentic AI across industries. Develop frameworks for evaluating and prioritizing use cases for business success. Understand common pitfalls in AI projects and how to mitigate risks.
Build and Lead Effective AI Teams:Define roles and responsibilities for teams working on Generative and Agentic AI. Identify skill gaps and develop training programs for talent development. Foster collaboration between technical and business units for AI initiatives.
Focus on Responsible and Sustainable AI Practices:Understand ethical considerations, such as mitigating bias, ensuring fairness, and safeguarding data privacy. Explore sustainable AI practices to minimize environmental impact.

Programme Content

Programme ContentThis course blends cutting-edge theory, hands-on implementation, and real-world applications to equip participants with the skills to build and deploy AI agents.

Introduction to Generative and Agentic AI:Intuitive understanding of Generative and Agentic AI; Relationship between traditional AI, Generative AI, and Agentic AI; Converting a business problem into a Generative/Agentic AI problem; Framework for problem-solving using Generative and Agentic AI; Use cases of these technologies across industries such as media, marketing, finance, healthcare, and operations; Overview of business process transformation using Generative and Agentic AI.

Sales and Marketing: Content creation, campaign optimization, customer engagement, and personalization.
Retail and E-Commerce: Generative AI for personalized product recommendations and personalized design studios.
Healthcare: Image generation, patient data summarization, and automated analysis.
Banking and Finance: Fraud detection, report generation, and credit analysis using Generative AI.Case Studies:
Generative AI for automated content creation in a media company.
Agentic AI for Generative Business Intelligence (GenBI) – converting natural language to reports and dashboards.
This program provides practical insights and hands-on experience, equipping participants to drive innovation and transform their organizations with Generative and Agentic AI.

Programme Objective


This is designed to spearhead and implement Generative and Agentic AI initiatives within their organizations. The course provides a comprehensive understanding of how to integrate these transformative technologies into business strategies, focusing on organizational readiness, technology adoption, and ethical considerations.
Develop Strategies for Generative and Agentic AI Adoption:Build a roadmap for integrating Generative and Agentic AI into the organization. Understand data governance and infrastructure requirements for AI-driven innovation. Align technology, platform, and talent strategies with AI objectives.
Understand the Fundamentals and Applications of Generative and Agentic AI:Explore the principles and applications of Generative AI, including content creation, simulation, and personalization. Gain insights into Agentic AI systems, focusing on autonomous decision-making, multi-agent systems (MAS), and adaptive problem-solving. Learn techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning for domain-specific AI solutions.
Identify and Prioritize Use Cases:Recognize high-impact applications of Generative and Agentic AI across industries. Develop frameworks for evaluating and prioritizing use cases for business success. Understand common pitfalls in AI projects and how to mitigate risks.
Build and Lead Effective AI Teams:Define roles and responsibilities for teams working on Generative and Agentic AI. Identify skill gaps and develop training programs for talent development. Foster collaboration between technical and business units for AI initiatives.
Focus on Responsible and Sustainable AI Practices:Understand ethical considerations, such as mitigating bias, ensuring fairness, and safeguarding data privacy. Explore sustainable AI practices to minimize environmental impact.

Programme Audience

Mode of Delivery: In-person deliveryCase Studies – Real-life use cases; Demonstrations; ApplicationsHands-on with Tools/Platform/libraries

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+91 9403890085[email protected]Mon – Fri, 9am – 5pm IST

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Generative AI and Agentic AI with Business Applications | IIM Bangalore