KT announced on the 10th that it will minimize customer inconvenience through proactive quality innovation using AI for mobile communication customers. This innovation involves AI analyzing customer usage patterns and quality information to predict abnormal signs and take preemptive measures.
AI utilizes deep learning and machine learning algorithms such as convolutional neural networks (CNN) to analyze mobile communication quality data, including response speed and signal strength. Through this, AI predicts whether abnormal signs occur and communicates this to the customer service center to verify whether any inconvenience has arisen during actual service usage. If the customer is experiencing inconvenience, a specialized engineer will be dispatched to the site to check and replace relay devices.
This system allows AI to recognize subtle inconveniences that customers may not perceive or signal weakening due to weather anomalies, taking quality improvement measures in advance. From the customer's perspective, an improvement in perceived quality can be expected. Quality checks can occur before the customer directly raises any issues, which is expected to reduce complaint cases by about 60%.
KT analyzes communication data generated from 13 million mobile communication customers daily using AI models, conducting quality improvement work based on data excluding personal information. In the future, there are plans to continuously enhance AI models using Microsoft's AX infrastructure. Additionally, in the second half of the year, proactive quality innovation using AI will be expanded to wired customers such as internet and IPTV users.