In 2024, telecom companies’ capital expenditures (CapEx) are estimated to approach $295 billion, while operational expenditures (OpEx) exceed $1 trillion — including spending on manual network planning and maintenance processes. In telecom networks, configuration and optimization involve managing a large number of interdependent parameters, which directly affect network performance, user experience, and spectrum efficiency for millions of customers and end-users. Telecom network engineers need to continuously adjust these settings based on time of day, user behavior, mobility, interference, and service types.
Generative AI supports Large Telecom Models (LTM) and AI agents, enabling next-generation AI in network operations. It helps telecom companies optimize OpEx, efficiently utilize CapEx, and unlock new revenue opportunities. NVIDIA has developed an agent-based AI solution that introduces autonomy to this dynamic environment by monitoring real-time network KPIs, making data-driven decisions, and automatically adjusting parameters.
Unlike traditional rule-based systems, AI agents can sense conditions, reason through complex trade-offs, learn from feedback loops, and incorporate human-in-the-loop feedback as needed to adapt to new scenarios. They can also orchestrate changes across multiple layers and vendors to enable coordinated actions such as load balancing, inter-unit interference coordination, or energy conservation in low-load areas. This level of autonomous control not only improves efficiency and quality of service (QoS) but also reduces operational complexity and shortens problem-solving time in dense, high-demand environments.
By leveraging NVIDIA AI, telecom companies can reduce network downtime, improve the productivity of field technicians, and deliver better service quality to customers. Connect with our team of experts or explore additional resources.