Dr. Shefali Singhal is an accomplished academician and researcher in the field of Artificial Intelligence and Machine Learning, currently serving as an Associate Professor at Manav Rachna International Institute of Research & Studies. With over 17 years of experience in teaching, research, and academic leadership, she has consistently contributed to advancing intelligent systems and technology-driven education. Her research spans AI/ML, cloud computing, and data-driven applications, with numerous publications in reputed Scopus and SCIE-indexed journals and international conferences. She is a patent holder in AI-driven optimization for green computing and has authored books and book chapters in the domain of algorithms and intelligent technologies. Dr. Singhal has also been actively involved in interdisciplinary innovation projects and has served as a reviewer and session coordinator in international conferences. Recognized for her academic excellence, she has received the Best Paper Award and has been associated with multiple faculty development initiatives including programs by leading institutions and industry bodies. She has also visited University of Wollongong, Dubai to present her research work in February 2026. Her keynote engagements focus on emerging AI paradigms, intelligent automation, and real-world applications of machine learning, aiming to bridge the gap between research, innovation, and industry needs.

From Assistants to Autonomous Agents: The Rise of Agentic AI in Intelligent Systems Artificial Intelligence has evolved significantly from traditional rule-based approaches to advanced machine learning systems capable of generating insights and content. A new and transformative phase in this journey is Agentic AI, where systems are designed to act independently by setting goals, making decisions, and executing tasks with limited human involvement. This keynote focuses on the transition from passive AI tools to intelligent agents that can proactively operate in complex and changing environments. The session will explore the foundational concepts behind Agentic AI, including autonomous decision-making, integration of reinforcement learning, multi-agent interaction, and the use of external tools and memory for enhanced reasoning. It will also discuss how modern AI models can coordinate multiple steps to complete tasks efficiently. Real-world applications in areas such as healthcare, education, cybersecurity, and business automation will be presented to highlight the practical significance of these systems. Furthermore, the talk will examine key concerns related to the deployment of autonomous AI, including trust, transparency, ethical implications, and system safety. The keynote will conclude with insights into future research opportunities and the growing role of Agentic AI in shaping intelligent, adaptive, and scalable digital ecosystems.