In this session, we explore the evolution of AI into the agentic model paradigm: fully autonomous agentic model capable of setting their own goals, planning multi-step strategies, executing actions, learning from feedback, and adapting over time with minimal human intervention. These agentic models transcend prompt based generation by initiating tasks, they perceive context, articulate intentions, invoke tools or APIs, and iteratively reflect on outcomes using reinforcement learning and internal memory architectures. As AI transitions from reactive assistants toward proactive collaborators, agentic models are increasingly deployed to manage end to end workflows, such as content creation, editing, personalization, or customer support, while retaining transparency, adaptability, and traceable decision-making even in dynamic environments.