Artificial Intelligence (AI) in customer support has advanced from basic automation to sophisticated agents capable of handling complex interactions. Traditional chatbots, which initially used rule-based systems and later incorporated natural language processing (NLP), are effective for simple, repetitive tasks but struggle with maintaining context and handling dynamic conversations. Large language model (LLM)-based chatbots, such as ChatGPT, enhance interaction quality by generating human-like responses and retaining conversational context, yet they lack the ability to execute tasks autonomously. Advanced AI agents surpass these limitations by integrating deep learning and real-time adaptive systems, allowing them to automate workflows, personalize interactions, and proactively engage with users. These agents offer advantages in handling intricate customer interactions and optimizing business processes, leading to increased customer satisfaction and reduced operational costs. For businesses, selecting between traditional chatbots and AI agents depends on the complexity of interactions and the need for automation, with AI agents offering a scalable solution for dynamic, context-aware customer support.