Customer service is being reinvented by conversational AI, sentiment analysis, and intelligent routing. This course is designed for team leads, operations managers, and support agents who want to harness AI to reduce response times and increase satisfaction. You will start by understanding the difference between rule-based chatbots and generative AI agents (like those powered by LLMs). The curriculum covers how to design effective conversational flows, handle fallback scenarios, and ensure seamless handoff to human agents. You will learn to use AI for real-time sentiment detection during live chats, automatically escalating frustrated customers to senior staff. Another module focuses on AI-assisted knowledge management—automatically suggesting articles to agents or surfacing answers directly to customers. You will also explore post-interaction analytics: topic clustering to identify common pain points, and predictive NPS (Net Promoter Score) based on conversation patterns. Ethical considerations include transparency (customers knowing they talk to a bot) and data privacy. Hands-on exercises include configuring a no-code chatbot for a sample helpdesk and using a sentiment analysis dashboard to prioritize tickets. By the end, you will be able to lead a customer service AI adoption roadmap, train your team to work alongside AI, and measure concrete improvements in cost-per-ticket and resolution time.
