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Aleksandr Koshkarov

Agentic AI: Levels, Opportunities, and Use Cases

Bio

Aleksandr Koshkarov is a PhD candidate in Computer Science at the University of Sherbrooke, under the supervision of Dr. Tahiri Nadia, with extensive experience in both AI and advanced data analysis across fields such as bioinformatics, ecology, agriculture, data-driven management, and sociology. He has led an AI department at a university, combining deep expertise in both fundamental and applied research. Aleksandr holds an MSc in Data Science from the University of Sheffield (UK) and has been actively engaged in data science since 2010.

Summary

This presentation explores Agentic Artificial Intelligence (AI), a rapidly emerging field beyond traditional generative models, characterized by autonomy, proactive decision-making, and goal-oriented behaviors. Participants will learn about the essential concepts that distinguish agentic AI from generative AI tools like ChatGPT, understand the five progressive levels of AI agents, and discover how these intelligent agents operate. Practical frameworks will be highlighted with concrete examples. The talk will also highlight several specific use cases, particularly in higher education and research. Join us to explore how agentic AI is reshaping opportunities across industries and opening new frontiers in education and innovation.