{"id":24307,"date":"2026-03-05T18:42:01","date_gmt":"2026-03-05T17:42:01","guid":{"rendered":"https:\/\/telecomkh.info\/?p=24307"},"modified":"2026-03-05T18:42:01","modified_gmt":"2026-03-05T17:42:01","slug":"gsma-launches-open-telco-ai-to-accelerate-development-of-telco-grade-ai","status":"publish","type":"post","link":"https:\/\/telecomkh.info\/?p=24307","title":{"rendered":"GSMA launches Open Telco AI to accelerate development of telco grade AI"},"content":{"rendered":"

New initiative is supported by open-telco models, including a new family of models from AT&T, compute from AMD and TensorWave, datasets from researchers and a new portal for industry contribution and collaboration via GSMA.com\/open-telco-ai<\/strong><\/p>\n

GSMA launched Open Telco AI, a global industry initiative designed to accelerate telco-grade AI through open collaboration across operators, vendors, AI developers and academic institutions. The launch introduces a new portal for telco open models, data, compute and tools to accelerate the development and evaluation of telco-focused AI models, accessed via GSMA.com\/open-telco-ai.
\nWhile frontier AI models have advanced rapidly, they continue to underperform on telecom specific tasks. Many general-purpose models struggle to interpret network data, understand standards documentation, or automate network operations with sufficient accuracy. This performance gap limits progress: only 16% of telecoms GenAI deployments1 have been applied to network operations.
\nOpen Telco AI meets this challenge by uniting industry and academic partners to build the foundations of telco grade AI models, data, compute, benchmarks and community. Progress is tracked through the Telco Capability Index, which measures model performance across an expanding set of telecom specific tasks.
\nAs founding supporters of Open Telco AI, AT&T and AMD are making significant contributions. AT&T is releasing a family of open telco-models developed and trained on open, publicly available data to be hardware and cloud agnostic, demonstrating that AI can deliver value across projects of any size and with varying levels of compute resources. AMD is providing compute capacity for model training, fine tuning, inference and evaluation through its GPU platforms, cloud partner TensorWave and open toolchains.
\nThe initiative is also supported by community programmes that bring together developers, researchers and operators to solve real-world telecom AI problems. This includes competitions such as the AI Telco Troubleshooting Challenge which attracted over 1,000 registrations and will announce its winners at MWC26 Barcelona.
\nLouis Powell, Director of AI Initiatives, GSMA, said: \u201cToday\u2019s AI models still fall short of the complexity, precision and reliability the telecom industry demands. Put simply, AI does not yet speak telco and operators are often deploying technology that cannot meet the required levels of accuracy, safety or efficiency. Establishing clear benchmarks and collaborating across the industry on datasets, models and agentic systems is essential. Open Telco AI provides a shared foundation designed to close this gap, an approach that other regulated sectors such as finance and healthcare can follow.\u201d
\n\u201cTelco networks are among the most demanding and regulated environments for AI and moving from promising demos to telco-grade performance requires an open foundation for data, workloads and compute,\u201d said Philip Guido, executive vice president and chief commercial officer, AMD. \u201cThrough Open Telco AI, with GSMA and AT&T, AMD delivers the enterprise and AI compute needed to train, fine-tune and run open, telco-grade models efficiently from core to edge.\u201d
\nAndy Markus, Chief Data and AI Officer at AT&T, said: \u201cThe telecom industry needs AI that understands the realities of networks \u2013 not only generic models repurposed for telco tasks. Through Open Telco AI, AT&T is helping build the datasets, models and evaluation frameworks that make telco grade AI possible at scale. By contributing our expertise and shaping realistic test environments, we\u2019re demonstrating how generative and agentic AI can improve customer experience, reduce operational friction and ultimately create new value. This collaboration with GSMA is accelerating the industry\u2019s path toward intelligent, automated networks.\u201d<\/p>\n

Building the Open Foundations of Telco-Grade AI<\/strong>
\nThe new portal will support the co creation of the essential building blocks for telco grade AI, including:<\/p>\n

\u2022 Telco Models:<\/strong> High performance open weight models designed for telecom tasks, from network troubleshooting to standards interpretation, including modelsof multiple sizes and architectures from AT&T, a radio-frequency language model from Khalifa University called RFGPT and a Large Telco Model (LTM) from AdaptKey AI built on NVIDIA Nemotron.<\/p>\n

\u2022 Open Data:<\/strong> A library of knowledge graphs, embeddings, and fine-tuning datasets of text, logs, and curated standards material from GSMA, Huawei Technologies France, Khalifa University, Mantis NLP, NetoAI, Pleias, Purdue University, The University of Texas at Dallas, University of Leeds and Yale University, and pipelines for generating synthetic data from NVIDIA.<\/p>\n

\u2022 Compute:<\/strong> Access to compute and open toolchain for projects training and inferencing open models via AMD and TensorWave.<\/p>\n

\u2022 Benchmarks:<\/strong> A leaderboard assessing model performance on seven telecom specific benchmarks, along with tools for evaluating and submitting models from local environments.<\/p>\n

\u2022 Community:<\/strong> Resources, challenges and engagement activities to encourage collaboration, including the AI Telco Troubleshooting Challenge and Agentic Challenge.<\/p>\n

The Open Telco AI initiative is supported by a host of valued contributing partners that have submitted data, models, and use cases including AMD, AT&T, Datumo, Huawei Technologies France, King Abdullah University of Science and Technology, KDDI, Khalifa University, KPN, LGU+, Mantis NLP, NetoAI, North Carolina State University, NVIDIA Orange, Ooredoo, Pleias, Purdue University, RelationalAI, SK Telecom, Softbank, Swisscom, TensorWave, Turkcell, University of Leeds, University of Texas at Dallas, and Yale University. Open Telco AI also has the support of valued participants partners including Adaptive ML, BMC, China Telecom, China Unicom, China Mobile, Deutsche Telekom, DU, e& UAE, Google Cloud, IBM, Liberty Global, Queens University, Telef\u00f3nica and Vodafone.<\/p>\n

[1] Source: GSMA Intelligence, Telco AI: State of the Market, Q4 2025, (published January 2026)<\/span><\/p>\n

Above, Philip Guido, executive vice president and chief commercial officer, AMD \/ image credited to AMD\u00a0<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

New initiative is supported by open-telco models, including a new family of models from AT&T, compute from AMD and TensorWave, datasets from researchers and a new portal for industry contribution and collaboration via GSMA.com\/open-telco-ai GSMA launched Open Telco AI, a global industry initiative designed to accelerate telco-grade AI through open collaboration across operators, vendors, AI … <\/p>\n

Continue reading \u00abGSMA launches Open Telco AI to accelerate development of telco grade AI\u00bb<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":24308,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[9,60],"tags":[],"_links":{"self":[{"href":"https:\/\/telecomkh.info\/index.php?rest_route=\/wp\/v2\/posts\/24307"}],"collection":[{"href":"https:\/\/telecomkh.info\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/telecomkh.info\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/telecomkh.info\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/telecomkh.info\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=24307"}],"version-history":[{"count":1,"href":"https:\/\/telecomkh.info\/index.php?rest_route=\/wp\/v2\/posts\/24307\/revisions"}],"predecessor-version":[{"id":24309,"href":"https:\/\/telecomkh.info\/index.php?rest_route=\/wp\/v2\/posts\/24307\/revisions\/24309"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/telecomkh.info\/index.php?rest_route=\/wp\/v2\/media\/24308"}],"wp:attachment":[{"href":"https:\/\/telecomkh.info\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=24307"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/telecomkh.info\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=24307"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/telecomkh.info\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=24307"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}