Scalable AI and ML-Powered Customer Support for Telecom Enterprises: Optimizing Engagement for 200 Million+ Customers - Santhosh Pininti (International Journal of Intelligent Systems and Applications in Engineering, 2024)
The telecom industry faces unprecedented challenges in managing large-scale customer support operations for user bases exceeding hundreds of millions. Traditional human-led models are increasingly inefficient, leading to long wait times, poor customer satisfaction, and high churn rates. This paper proposes a highly scalable AI and Machine Learning (ML) framework tailored for telecom enterprises with extensive customer bases. The solution leverages intent recognition, sentiment-aware routing, predictive analytics, and AI-driven omnichannel self-service to deliver responsive, personalized, and cost-effective support. With insights from large-scale telecom implementations, the proposed system demonstrates tangible improvements in First Contact Resolution (FCR), Net Promoter Score (NPS), and operational efficiency.