What’s It About?
Artificial intelligence has become established in customer service, but the initial enthusiasm is giving way to a sober assessment. While digital assistants and chatbots continue to be regarded as important tools, it is becoming apparent that their success depends heavily on the quality of the data foundation and integration into existing business processes. The number of companies deploying AI solutions has fallen considerably, from an originally assumed 95 percent to a realistic 54 percent.
Background & Context
AI-based systems in customer service promise considerable advantages: they enable personalized customer engagement through analysis of previous interactions, work around the clock, and relieve human employees of recurring standard requests such as order tracking. Through intelligent assistants, service employees gain immediate access to relevant customer data and interaction histories, which noticeably improves processing speed.
The measurable effects are quite remarkable: response times can be shortened by an average of about 19 percent, while process costs can drop by around 11.7 percent. Over 80 percent of customers report being satisfied with AI-supported interactions. Nevertheless, considerable challenges emerge in practice: fragmented data sets, a lack of integration of various systems, and insufficient data quality frequently hinder a successful rollout. Scaling the solutions remains a central problem for many companies.
What Does This Mean?
- Technology alone does not guarantee success – structured processes and high-quality data foundations are decisive
- Companies should develop realistic expectations and understand AI as a complement to human service
- The focus is shifting from pure automation toward intelligent support for service employees
- Investments in data integration and quality are critical to the success of AI projects in customer service
- The initial euphoria is giving way to a pragmatic approach with a differentiated assessment of use cases
Sources
KI im Kundenservice: Auf den Hype folgt die Bewährungsprobe (Computerwoche)
AI in Customer Service and Support (SAP)
Chatbots im Kundenservice (sncom)
KI im Kundenservice (HubSpot)
KI im Kundenservice: Chancen, Herausforderungen, Best Practices (Novomind)
This article was created with AI assistance and is based on the listed sources as well as the language model’s training data.
Further Reading: From Text Generator to Digital Employee: How AI Is Changing the World in Four Stages