With the deployment of generative AI, the role of knowledge databases is fundamentally changing. Organizations are on the threshold of industrializing their knowledge processes. In the future, knowledge databases will be operated by machines and humans for both machines and humans. The expansion of machine knowledge requires a different approach to text creation, using specific formatting, tags, or keywords, detailing functionalities, and elaborating on dependencies or causal chains. With the integration of ChatGPT into its leading knowledge database, USU now offers a customer service solution that significantly relieves service teams by enabling automated, high-quality services.
In practice, creating and structuring relevant content for various use-cases is very labor-intensive and thus one of the biggest hurdles to implementing a corresponding knowledge database. Generative AI will support this in the future by analyzing, classifying, and organizing important information from tickets, manuals, etc., into clear structures. Creating FAQs from extensive documents will also be accomplished in just a few interaction steps. Furthermore, the rephrasing of answers according to the target audience or in the "tone of voice" of the company is possible.
"The use of generative AI leads to a fundamentally different way of working in customer service. While machines now have highly developed language knowledge, they do not have subject matter knowledge. Both come together in our knowledge database. In the future, knowledge modules will be written and formatted in such a way that they can be interpreted and processed by machines," says Harald Huber, CTO and Managing Director of USU.