Dr. Vijay Kumar Kannan is a senior technology leader, AI strategist, and public-sector innovation practitioner with over 25 years of experience in software engineering, enterprise architecture, data science, and digital transformation. As Joint Director and Head of Software Engineering at C-DAC Chennai, he leads strategic initiatives across Generative AI, Agentic AI, Big Data Analytics, Retrieval-Augmented Generation (RAG), and enterprise AI governance. His leadership spans national-scale AI and analytics programs, including healthcare intelligence, governance modernization, and digital public infrastructure. An ISO/IEC 42001:2023 AI Management Systems Lead Auditor, Dr. Kannan specializes in building responsible, scalable, and enterprise-ready AI ecosystems. He is also a published researcher in Scopus-indexed journals with contributions in Big Data, Semantic Analysis, Machine Learning, Generative AI, and AI-driven decision systems. At AI-DataX 2026, he brings a practical and forward-looking perspective on architecting intelligent, governed, and transformative AI enterprises.  

Beyond Prediction: Harnessing Generative AI and LLMs for the Intelligent Data Enterprise                                                                                                                                                                                     Abstract: As enterprises navigate an unprecedented surge of structured and unstructured data, the challenge is no longer limited to predicting outcomes—it is about transforming data into intelligent, context-aware action. This session explores how Generative AI and Large Language Models (LLMs) are reshaping the modern data enterprise by moving beyond traditional analytics toward systems that can interpret, reason, generate insights, and interact with data more naturally. “Beyond Prediction” presents a practical framework for integrating LLMs into enterprise data ecosystems, where AI becomes an active collaborator in the analytics lifecycle. From natural language querying and automated knowledge synthesis to AI-driven storytelling and decision augmentation, the talk examines how generative technologies are redefining how organizations extract value from data. Real-world perspectives will highlight how these capabilities can bridge technical complexity and strategic business outcomes. Equally, the session addresses the enterprise realities of scaling Generative AI responsibly—governance, explainability, trust, and operational accountability. It emphasizes that sustainable AI transformation requires more than innovation; it demands architecture that is secure, governed, and human-centered. Attendees will gain a grounded roadmap for architecting the Intelligent Data Enterprise—one where Generative AI and LLMs are not isolated tools, but foundational components of a smarter, more adaptive, and strategically empowered future.