AI Competence in Customer Support

AI Explorer

Initial situation

In light of the ongoing shortage of skilled workers, it is becoming increasingly difficult for SMEs - especially in rural regions - to find suitable specialists. Currently, Lauffer does not use any AI applications; data processing in systems such as ERP, PDM and service management is largely manual.
The project therefore aims to identify suitable AI use cases to improve customer service through intelligent self-service and by linking and analyzing service, ticket and machine data. Such AI solutions can help customer service to respond more quickly to inquiries, solve problems automatically and work more efficiently overall. This can both increase service quality and mitigate the effects of the skills shortage.

Solution idea

In order to identify the potential of AI in customer service, a structured series of workshops was held as part of the AI Explorer. Based on the current tasks and challenges, possible use cases were developed, which were then jointly evaluated and prioritized. A detailed analysis of the cost-benefit ratio and the technical and organizational requirements for implementation was carried out for the three most promising use cases. The aim of the project was to develop a sound basis for decision-making and a project plan for the implementation of the top 3 use cases.

Implementation of the AI application

The following final recommendation was made: For the successful use of AI, it is recommended to rely on established out-of-the-box solutions, as individual developments involve a great deal of effort and are hardly worthwhile for smaller companies. Sufficient data quality is a prerequisite, which is why the systematic collection, cleansing and checking of relevant data should be started at an early stage, e.g. with a quick check for predictive maintenance. Processes also need to be streamlined and further digitalized in order to create a reliable basis for AI applications.