While chatbots have grown common in applications like customer service, they have several shortcomings which disrupts user experience. Traditional chatbots rely on pattern matching and database lookups, which are ineffective when a user’s question deviates from what was expected. Responses may feel impersonal and fail to address the true intent when questions deviate slightly from pattern matching rules.

This is where large language models (LLMs) can provide value. LLMs are better equipped to handle out-of-scope questions due to their ability to understand context and previous exchanges. They can generate more personalized responses compared to typical rule-based chatbots. As such, chatbots represent a prime use case for generative AI in enterprises.