Agentic AI Systems: Why They Matter and How They Will Reshape Enterprise Automation

We are on the cusp of a new AI revolution—one that moves beyond static prompts and siloed models into dynamic, autonomous systems. Agentic AI represents a significant leap where AI entities (agents) are capable of reasoning, taking initiative, collaborating with other agents, and improving over time.

In this session, we will explore how Agentic AI Systems are designed, orchestrated, and deployed to solve real-world business problems. Through hands-on examples and enterprise case studies, participants will learn how agent-based architectures can replace legacy systems like static ticket analytics, enhance IT service workflows, and even transform expert monetization platforms.

The speaker will also share a behind-the-scenes look at how Agentic AI is powering her own startup, bridging cutting-edge research with high-impact automation.

Key Takeaways:

• What is Agentic AI?
  Understanding the evolution from foundational models to autonomous multi-agent systems.
• How Agentic Systems Work:
  Architectural overview of planning, memory, tool use, and inter-agent collaboration.
• Enterprise Use Cases:
  • Replacing STA/ITSM workflows with LLM agents
  • Automating Root Cause Analysis (RCA)
  • Enabling dynamic report generation and insights
  • Real-time orchestration in expert platforms and customer service
• Demo Walkthrough:
  A guided walkthrough of a real Agentic AI pipeline using OpenAI tools, LangChain, or ReAct agents.
• Building Your First AI Agent:
  Starter template + tools you need to begin your agentic journey (LangChain, AutoGen, CrewAI, etc.)
• Future of Work with AI Agents:
  Why Agentic AI will redefine workflows, collaboration, and expertise delivery across industries.

Lekha Priya is an AI Architect with deep expertise in designing enterprise-scale GenAI solutions — from retrieval-augmented generation (RAG) systems to agentic workflows for IT Ops and automation. With a background in building modular AI pipelines, I specialize in aligning LLM-based systems with business value, scale, and reliability. I currently lead architecture efforts at Kyndryl, shaping next-gen AI systems that bridge unstructured intelligence and action automation.