From the course: Designing Agentic AI Products (No Code Required)
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Enterprise customer experience applications
From the course: Designing Agentic AI Products (No Code Required)
Enterprise customer experience applications
- Agent AI can generate design ideas, test, and iterate towards optimization goals. This can be in a factory setting or a car showroom. Everything the agent AI does is to analyze, get results, reason, and present output, and iterate to arrive at the desired optimization. The fastest growing use case for GenAI is customer experience with intelligent chatbots, but this involves human interaction to make decisions when the chatbot makes mistakes or when customer gives feedback that can be applied to enhance their experience. How can an agent AI break down this task to enhance customer experience? The agent AI should first engage to get customer input. This could be a chat or a voice-based input. It should then use tools to understand the customer response and use reasoning to identify their complaint or feedback. Then it should iterate based on the right response to fix the customer's problem and arrive at the best response, which can be validated by a different agent that collects…
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