Abstract
By leveraging AIOps, machine learning, and predictive analytics, telecom operators today can achieve self-diagnosing, self-healing, and self-optimizing networks. The result: up to 40% OPEX savings, improved efficiency, reduced risk, and enhanced customer experience. This white paper explores the transformation of telecom operations through “Dark Operations,” a fully autonomous model where AI-driven systems silently manage networks with minimal human intervention. Real-world case studies demonstrate significant cost reductions and operational resilience, positioning dark operations as a critical step for telecoms aiming to stay competitive in a rapidly evolving landscape.
Key Insights
Telecom networks can self-diagnose, self-heal, and optimize performance without human intervention, reducing downtime and improving customer experience.
AI-driven systems enable instant fault detection and resolution, ensuring seamless service delivery and minimizing operational delays across critical processes.
Dark operations powered by AI cut costs by 25–40% through automation of NOC tasks, predictive maintenance, and customer support, driving efficiency at scale.