Agentic AI refers to systems that autonomously perceive data, reason through specialized models, execute tasks via external tools, and continuously learn from feedback to improve performance. This four-step cycle of perceive-reason-act-learn enables agents to handle sophisticated business processes without constant human oversight. Understanding agentic AI requires looking beyond simple chatbots to systems that can independently execute complex, multi-step workflows. Unlike traditional AI assistants that respond to individual prompts, agentic systems maintain context across extended interactions and can adapt their approach based on real-time feedback.