Topics

This session introduces Artificial Intelligence, covering its background, historical context, and the fundamentals of AI development. It also provides an overview of prompt engineering techniques for generating text and images, setting the foundation for understanding AI’s capabilities and applications.

This session covers AI systems that combine Generative AI with other functions. It covers concepts and tools to build Agentic AI Systems.

This session explores strategic uses of generative AI in business, focusing on high-impact opportunities across industries in areas like marketing, customer service, and product development. It includes case studies of successful AI-driven transformations in sectors such as healthcare, finance, and retail, highlighting real-world applications and value. The session also presents frameworks to help businesses decide whether to build or buy generative AI solutions, giving participants criteria to evaluate the best approach for their needs.

This session focuses on integrating generative AI into current enterprise systems and workflows, emphasizing practical steps for embedding AI smoothly within existing structures. It examines the choice between customizing generative AI models for specific business needs and using readily available tools. The session also covers the role of data feedback loops in continuously improving AI performance, highlighting how ongoing data integration refines model accuracy and effectiveness over time.

This session addresses the critical aspects of risk management and ethics in generative AI, focusing on data privacy, security, and intellectual property concerns. It covers ethical issues, including managing bias, preventing misinformation (AI “hallucinations”), and ensuring accountability in AI applications. The session also discusses relevant legal frameworks and regulatory considerations for businesses deploying generative AI, highlighting the importance of responsible and compliant AI integration.

This session covers leadership strategies for promoting generative AI adoption within organizations, focusing on effective approaches to drive AI initiatives across teams and departments. It emphasizes the importance of building cross-functional teams to support AI projects and details change management techniques to secure organizational buy-in, ensuring a smooth transition and widespread support for generative AI transformation efforts.