Agentic AI is changing how businesses approach customer interactions and operations. Unlike Robotic Process Automation (RPA), which follows strict rules to perform tasks, Agentic AI can understand goals and formulate plans independently. For instance, while an RPA bot can upload a resume to a database, an Agentic AI can analyze a resume, recognize key qualifications, and draft a personalized outreach email. This shift represents a significant move from reactive systems that merely provide information to proactive systems that take initiative on behalf of the user. The article outlines four levels of autonomy for Agentic AI. The first level, Observe-and-Suggest, involves the agent monitoring data and alerting users without taking action. The second level, Plan-and-Propose, sees the agent devise a strategy for the user to approve. The third level, Act-with-Confirmation, has the agent prepare actions that the user can confirm before execution. Finally, Act-Autonomously allows the agent to operate independently within set boundaries, notifying users only after the task is completed. Each level has specific implications for design and user oversight. For instance, agents that simply suggest actions need to provide clear, non-intrusive notifications. In contrast, autonomous agents require robust monitoring and well-defined boundaries to maintain user trust. As companies integrate these systems, understanding these distinctions and their design requirements will be essential for optimizing user experience and operational efficiency.