{"slug": "why-telecom-operators-are-building-their-ai-strategy-on-open-models", "title": "Why Telecom Operators Are Building Their AI Strategy on Open Models", "summary": "NVIDIA's State of AI in Telecommunications report found that 89% of respondents say open source models and software are important to their company's AI strategy, as telecom operators build AI on open models for trust, control and customization. NVIDIA announced the 30-billion-parameter Nemotron 3 Large Telco Model, fine-tuned by AdaptKey on open source telecom datasets for telecom-specific tasks such as network configuration and customer care. SoftBank Corp. principal fellow and SB Telecom America senior vice president Rajeev Koodli said open models let SoftBank \"build on the rapid progress of global foundation models while applying the network knowledge and operational expertise we have accumulated over many years\" in developing its SoftBank Large Telecom Model.", "body_md": "Telecom operators are increasingly building their AI strategies on [open models](https://www.nvidia.com/en-us/glossary/open-models/) — and the reasons go beyond mere cost. \n\nOpen models give telcos the ability to trust, control and customize AI across their most critical workloads — from [autonomous networks](https://www.nvidia.com/en-us/glossary/autonomous-networks/) to customer care. \n\n[NVIDIA’s latest State of AI in Telecommunications report](https://resources.nvidia.com/en-us-ai-in-telco/telco-report-state-o) reflects this shift, with 89% of respondents reporting that open source models and software are important to their company’s AI strategy. \n\nFor operators, the strategic value of open models is fivefold:\n\n1. They expand access to [frontier‑level intelligence](https://nvidianews.nvidia.com/news/nvidia-launches-nemotron-coalition-of-leading-global-ai-labs-to-advance-open-frontier-models) 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](https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index) show that leading open models are becoming more competitive across demanding reasoning, coding, scientific and agentic workloads.\n2. 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.\n3. They enable [trustworthy AI](https://blogs.nvidia.com/blog/what-is-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.\n4. They enable flexible, secure deployment: teams can size and optimize open models to run across public clouds, private infrastructure and edge environments.\n5. They unlock the opportunity for telcos to deliver locally adapted AI services to enterprise and government customers by hosting and fine-tuning open models.\n\n## **Open Foundations, Tuned for Telecom Operations**\n\nThe [NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) family of open models provides [frontier](https://www.nvidia.com/en-us/glossary/frontier-models/)-level reasoning performance optimized for agentic workflows, as well as speech capabilities for voice applications, with open weights, training data and recipes. \n\nSoftBank Corp. illustrates how an operator can use open models as a basis for developing and continuously advancing its telecom-specific AI capabilities.\n\n“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.”\n\nIn addition, NVIDIA is collaborating with partners to help turn open models into practical building blocks for telecom AI.\n\nNVIDIA [announced](https://blogs.nvidia.com/blog/nvidia-agentic-ai-blueprints-telco-reasoning-models/) the 30-billion-parameter [Nemotron 3 Large Telco Model](https://blogs.nvidia.com/blog/nvidia-agentic-ai-blueprints-telco-reasoning-models/) (LTM), [fine-tuned](https://adaptkey.ai/blog/building-domain-expert-llms) by [AdaptKey](https://huggingface.co/AdaptKey/AdaptKey-Nemotron-30b) 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.\n\nTo help operators customize the Nemotron 3 LTM and other open models with their own operational data, NVIDIA released the [full recipe](https://nvidia-nemo.github.io/Skills/tutorials/2026/02/27/teaching-a-model-to-reason-over-telecom-network-incidents/) that walks through the end-to-end fine-tuning pipeline for adapting open models to operator-specific networks, customers and procedures using [NVIDIA NeMo](https://github.com/nvidia-nemo) open libraries. \n\n## **Scale Open Models Into Production Workflows**\n\nOpen models are a critical building block, but it takes more than models to bring autonomous telecom operations safely into production.\n\nFor AT&T, the value of model choice lies in making that flexibility operational in alignment with its business priorities.\n\n“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. “Open models are essential to that approach, and with NVIDIA, we can bring that model-choice strategy into production with the scale, reliability and governance our business requires.”\n\nOperators need pipelines that prepare and protect their data for model fine‑tuning by anonymizing sensitive records and generating privacy‑preserving synthetic datasets. They also need a platform that can turn open models into governed, autonomous agentic workflows.\n\nNVIDIA provides that [end-to-end platform](https://developer.nvidia.com/blog/how-telcos-build-autonomous-networks-with-agentic-ai), powered by [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/) software and [NVIDIA Agent Toolkit](https://blogs.nvidia.com/blog/nvidia-agent-toolkit-open-models-tools-skills-secure-runtime-ai-agents/?ncid=so-nvsh-718272-vt26), and spanning data pipelines, open models, agent orchestration, secure runtimes and simulation.  \n\nTogether with a strong [partner ecosystem](https://blogs.nvidia.com/blog/telecom-ai-agents-dtw-ignite-2026/) building at every layer of this platform, telecom operators have a clear path to translate the benefits of open models into production-ready AI workflows.\n\n## **Create a Platform for Local AI Innovation**\n\nAs telecom operators [build AI infrastructure](https://resources.nvidia.com/en-us-telco-ai-factories/ebook-sovereign-ai-factories) aligned with [national AI strategies](https://blogs.nvidia.com/blog/nations-deploy-ai-strategic-priorities/), open models are giving them a foundation to deliver AI services tailored to local languages, industries, regulations and data governance requirements. \n\nOperators across countries can fine-tune open models for local-language and industry-specific needs, as well as host open models on their trusted platforms that customers can consume directly or build on with their own data and applications.\n\nFor Indosat Ooredoo Hutchison, one of Indonesia’s largest telecom operators, that means building AI that reflects the country’s own language and culture through its Sahabat-AI family of open source models.\n\n“For countries like Indonesia, the value of open models goes beyond access to powerful AI. It is about adapting that intelligence to our own language, culture, data and real-world needs,” said Chirag Sukhadia, chief data and AI officer of Indosat Ooredoo Hutchison. “Sahabat-AI puts this into practice, using open models as a foundation to build AI that understands Indonesia and can be developed for local applications. This allows us not only to adopt AI, but to build capabilities around it and enable more Indonesians to create with AI on their own terms.”\n\n*Learn more about* *NVIDIA technologies for telecommunications**.*", "url": "https://wpnews.pro/news/why-telecom-operators-are-building-their-ai-strategy-on-open-models", "canonical_source": "https://blogs.nvidia.com/blog/telecom-operators-open-models/", "published_at": "2026-10-06 13:00:19+00:00", "updated_at": "2026-10-06 13:18:12.611019+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-products", "ai-infrastructure"], "entities": ["NVIDIA", "SoftBank Corp.", "SB Telecom America", "Rajeev Koodli", "NVIDIA Nemotron", "Nemotron 3 Large Telco Model", "AdaptKey", "Artificial Analysis Intelligence Index v4.3.2"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/why-telecom-operators-are-building-their-ai-strategy-on-open-models", "markdown": "https://wpnews.pro/news/why-telecom-operators-are-building-their-ai-strategy-on-open-models.md", "text": "https://wpnews.pro/news/why-telecom-operators-are-building-their-ai-strategy-on-open-models.txt", "jsonld": "https://wpnews.pro/news/why-telecom-operators-are-building-their-ai-strategy-on-open-models.jsonld"}}