Nvidia and its telecom partners, which include SoftBank Corp and NTT Data, plan to demonstrate a stack of data, models, simulation tools and secure runtimes at DTW Ignite 2026.
This move is aimed at helping operators move from task-based automation to fully autonomous network operations.
The company argues while generative AI has delivered strong returns in network management, customer care and back-office automation, most of the impact has been limited to speeding up predetermined steps while humans still correlate insights and direct next actions.
Nvidia claims automation is now “the launchpad to autonomy” rather than the end goal, with AI agents expected to proactively monitor for problems and coordinate changes across network, IT and business systems while keeping humans in control of policy.
Nvidia cites figures showing 54% of telecom operators view data-related issues as their biggest obstacle to building telecom-specific AI models, largely because the most valuable network and customer data is too sensitive to use directly for training.
SoftBank Corp is tackling the problem by using Nvidia’s NeMo Safe Synthesizer and NeMo Anonymizer tools to generate privacy-preserving synthetic datasets which mirror the structure of real network performance and configuration datasets.
Those datasets are being used to fine-tune its Large Telecom Model (LTM) and build specialised network agents.
On the runtime side, Nvidia stated its NemoClaw blueprints and OpenShell secure runtime are designed to give long-running agents policy-based guardrails and sandboxed access to telecom systems, allowing operators to expand agent responsibilities while keeping behaviour auditable and governed.
NTT Data is applying Nvidia’s open Nemotron models alongside NemoClaw to build agents which track long-term network performance trends and escalate anomalies to specialised research agents for deeper telemetry analysis.
Other partners building on the same framework include: AdaptKey, which is piloting self-healing 5G agents with operators; ServiceNow, which is bringing its Project Arc incident-response tooling to telecom network operations centres; and Tata Consultancy Services, which is developing a multi-fidelity AI sensor architecture for faster anomaly detection.
Simulation is the third pillar of the effort, intended to let agents test recommendations in near-real-time digital environments before acting on live systems.
Software company Forsk stated its GPU-accelerated radio propagation model now achieves ray-tracing-level accuracy up to 200 times faster than CPU-only systems, while Viavi Solutions reports order-of-magnitude gains in RAN simulation throughput after shifting workloads to Nvidia’s RTX Pro 6000 Blackwell GPUs.
KDDI and KDDI Research, working with Nvidia, Keysight and Samsung Research America, are building a high-fidelity RAN digital twin aimed at the 6G era, allowing multiple autonomous agents to simulate scenarios for future radio conditions and traffic shifts.
The TM Forum’s DTW Ignite conference runs 23–25 June 2026 in Copenhagen.
Source: Mobile World Live
Image Credit: NVIDIA
Source: Tahawul Tech