Why Telecom Operators Are Building Their AI Strategy on Open Models
Telecom operators are increasingly building their AI strategies on open models — and the reasons go beyond mere cost. Open models give telcos the ability to trust, control and customize AI across their most critical workloads — from autonomous networks to customer care. NVIDIA’s latest State of AI in Telecommunications report reflects this shift, with 89% of respondents reporting that open source models and software are important to their company’s AI strategy. For operators, the strategic value of open models is fivefold: They expand access to frontier‑level intelligence at lower cost, allowing operators to reserve closed models for the workloads where they drive the most value. Independent benchmarks such as the Artificial Analysis Intelligence Index v4.3.2 show that leading open models are becoming more competitive across demanding reasoning, coding, scientific and agentic workloads.
They support telco‑specific customization, with open weights and training recipes that operators can fine‑tune for their own operations using network, customer and industry data. They enable trustworthy AI by giving telcos greater visibility into and control over model artifacts and behavior, so models can be evaluated, adapted and governed in alignment with regulations and business policies. They enable flexible, secure deployment: teams can size and optimize open models to run across public clouds, private infrastructure and edge environments. They unlock the opportunity for telcos to deliver locally adapted AI services to enterprise and government customers by hosting and fine-tuning open models. Open Foundations, Tuned for Telecom Operations The NVIDIA Nemotron family of open models provides frontier-level reasoning performance optimized for agentic workflows, as well as speech capabilities for voice applications, with open weights, training data and recipes. SoftBank Corp. illustrates how an operator can use open models as a basis for developing and continuously advancing its telecom-specific AI capabilities. “Open models allow SoftBank Corp. to build on the rapid progress of global foundation models while applying the network knowledge and operational expertise we have accumulated over many years,” said Rajeev Koodli, principal fellow of SoftBank Corp. and senior vice president of SB Telecom America. “We are using open foundations extensively, including NVIDIA Nemotron models and others, in developing our SoftBank Large Telecom Model, continuously advancing it for telecom-specific use cases such as network operations, design and overall management.” In addition, NVIDIA is collaborating with partners to help turn open models into practical building blocks for telecom AI. NVIDIA announced the 30-billion-parameter Nemotron 3 Large Telco Model (LTM), fine-tuned by AdaptKey on open source telecom datasets to deliver accuracy gains for telecom-specific tasks. This gives operators an open baseline that can understand telecom industry terminology and reason effectively through telecom operations workflows such as network configuration and customer incident triage. To help operators customize the Nemotron 3 LTM and other open models with their own operational data, NVIDIA released the full recipe that walks through the end-to-end fine-tuning pipeline for adapting open models to operator-specific networks, customers and procedures using NVIDIA NeMo open libraries. Scale Open Models Into Production Workflows Open models are a critical building block, but it takes more than models to bring autonomous telecom operations safely into production. For AT&T, the value of model choice lies in making that flexibility operational in alignment with its business priorities. “At AT&T, we believe the future of AI is not about choosing a single model; it’s about intelligently matching every workload to the right combination of performance, cost and control,” said Andy Markus, chief data and AI officer of AT&T.
