Artificial Intelligence is evolving beyond simple chatbots into systems capable of reasoning, planning, and independently completing complex tasks. These systems, often referred to as Agentic AI or AI Agents, represent the next stage of AI adoption where intelligent agents can take actions, use tools, coordinate workflows, and assist with real-world problem solving.

This webinar introduces the fundamentals of Agentic AI, explaining how autonomous AI agents differ from traditional chatbots and how they combine reasoning, memory, planning, and tool usage to perform multi-step tasks. Participants will explore practical applications of AI agents in research, coding, business operations, productivity, and automation.

The session also addresses critical safety and governance considerations including human oversight, guardrails, reliability, accountability, and responsible AI deployment.

This webinar is designed for students, professionals, educators, managers, and anyone seeking a practical introduction to the rapidly emerging world of AI agents and autonomous systems.

Areas Covered in the Webinar

Introduction to Agentic AI

• What Agentic AI means
• Difference between chatbots and AI agents
• Evolution from reactive AI to autonomous systems
• Why AI agents are gaining attention

How AI Agents Work

• Reasoning and decision-making
• Multi-step task execution
• Planning and goal-oriented behavior
• Memory and contextual awareness
• Tool use and external integrations

Components of an AI Agent

• Large Language Models (LLMs)
• Planning frameworks
• Retrieval systems
• APIs and external tools
• Feedback loops and monitoring

Agentic AI vs Traditional Chatbots

• Conversational responses vs task execution
• Static prompts vs autonomous workflows
• Single interaction vs ongoing processes
• Examples of modern AI agents

Real-World Applications

• Research assistants
• Coding and software development agents
• Business process automation
• Personal productivity assistants
• Customer support workflows
• Data analysis and reporting

Risks and Safety Considerations

• Hallucinations and unreliable outputs
• Over-automation risks
• Data privacy concerns
• Security vulnerabilities
• Human oversight requirements
• Responsible deployment practices

Guardrails and Governance

• Safety mechanisms for AI agents
• Permission and approval systems
• Human-in-the-loop design
• Ethical boundaries and accountability
• Monitoring and auditing agent behavior

Future of Autonomous AI

• Emerging trends in AI agents
• Workplace transformation
• Opportunities and limitations
• Human-AI collaboration models