NVIDIA Brings Trusted, 24/7 AI Agents to Telecom Operations

At DTW Ignite 2026, NVIDIA and its partners are showcasing the data, models, simulation and secure runtime stack enabling telcos to build more secure agentic workflows across autonomous networks and operations. Telecom operators have seen remarkable returns from using generative AI to automate network management, customer care and back-office operations. Most of that impact has been task‑based: automation that speeds up predetermined steps while people manually correlate insights and direct next steps.

Automation is no longer the finish line - it's the launchpad to autonomy. The industry is now pushing toward truly autonomous networks and operations, where AI agents proactively watch for problems and coordinate changes across network, IT and business systems. Together, synthetic data, telecom-domain models, secure agent runtimes and simulations form critical pieces of a secure, telecom autonomy platform , where agents understand operator intent, act safely across business and network domains and keep humans in control of policy.

NVIDIA and its partners are demonstrating these building blocks at TM Forum's DTW Ignite 2026 - running this week in Copenhagen - giving operators a practical path to running more autonomous, resilient networks and powering richer AI‑driven services for consumers and businesses. Unlock Privacy‑Safe Telecom Data for AI Models Reasoning models that understand the telecom domain are the foundation of autonomous networks. These specialized models require fine‑tuning on high‑quality datasets, yet 54% of operators cite data‑related issues as their biggest barrier, with the most valuable network and customer data too sensitive to use directly.

Synthetic data is enabling operators to safely increase the volume and diversity of training data, protect sensitive information and democratize access to production‑like telecom datasets across internal teams and external developers, without exposing raw customer records. is using technologies such as NVIDIA NeMo Safe Synthesizer and NVIDIA NeMo Anonymizer to generate privacy‑preserving synthetic datasets that reflect the structure and distribution of real network performance and configuration datasets. These datasets are being used to fine-tune its large telecom model and build specialized network agents.

Securely Deploy Autonomous Telecom Agents As telecom operators look to achieve autonomy across end-to-end workflows, they need AI agents that can stick with a complex job from start to finish, not just execute a pointed task. Long‑running autonomous agents that operate under strict service-level agreements, change‑management policies and regulatory constraints are key to this shift. NVIDIA NemoClaw blueprints and the NVIDIA OpenShell secure runtime give these agents policy‑based guardrails and sandboxed access to telecom systems, so operators can more safely expand the role of agents in operations while keeping behavior predictable, auditable and governed.

AdaptKey is collaborating with operators to pilot security‑hardened, long-running agents for self‑healing 5G network operations. NemoClaw and OpenShell power agents that detect security and connectivity issues and submit scoped remediation requests into AdaptKey 's KeySmith platform for execution, which orchestrates diagnosis and runs agents that apply auditable fixes across core, radio access network (RAN) and billing systems. Amdocs is showcasing the potential of NemoClaw and OpenShell for proactive customer-care agents, including roaming assistance scenarios where autonomous agents can identify customers whose roaming package is nearing depletion, engage them with approved options and execute actions within defined business policies and operational controls.