Autonomous networks are quickly becoming one of the top priorities in telecommunications. According to the latest NVIDIA State of AI in Telecommunications report, 65% of operators said AI is driving network automation, and 50% named autonomous networks as the top AI use case for ROI.
Yet many telcos still report gaps in AI and data science expertise. This makes it difficult to scale safe, closed-loop automation across complex, multidomain networks.
Most telecom network operations centers (NOCs) today operate using reactive, alarm-driven workflows. Engineers manually triage thousands of incidents across multiple tools, sift through a high volume of alarm and performance data, and stitch together fragmented dashboards and logs before applying a fix or dispatching a field team. NOCs are a natural starting point for autonomous networks, because they concentrate high-volume, repeatable tasks where AI can directly cut MTTR and OPEX.Tech Mahindra, a leading global provider of technology consulting and digital solutions to enterprises across industries, and NVIDIA are collaborating to close this AI skills gap. They’re doing so by making autonomous network building blocks—open models, tools, and implementation guides—into assets telecom developers can readily adopt and adapt in their own environments.
