Driven by advancements in large language models (LLMs) such as OpenAI’s ChatGPT and Google’s Bard, the customer service and support landscape is undergoing a significant transformation.

This talk proposal focuses on harnessing the power of LLMs to augment human agents and revolutionize support interactions. It digs into the advantages of LLMs, such as their quick deployment and scalability, and shows how they improve customer service speed, efficiency, and consistency.

Additionally, the talk emphasizes the criticality of enterprise-specific content for generating credible responses, presenting a three-part approach that combines system instructions, user questions, and relevant documentation. The proposal also addresses the challenge of centralizing and managing unstructured data assets, providing insights into leveraging LLMs for support-driven decision-making.

Attendees will gain valuable insights into the potential of LLMs in customer service and support, understand the importance of contextualization, and learn effective strategies for content management to ensure accurate and personalized responses.