AT&T

com → Jul 24, 2026 Here’s a development of vital importance to network operators with AI-native telco aspirations. Earlier this year, the GSMA launched Open Telco AI , an initiative that aims to address the fact that generic AI frontier models aren’t tuned for the specific needs of telecom network operators by fostering the development of telco-grade AI models. Louis Powell, director of AI initiatives at the GSMA, explained to TelecomTV during MWC26 that AT&T and AMD were laying the foundations for the initiative: That collaboration resulted in the development by AT&T of a family of open telco models called OTel that were trained on a specialised telco-specific dataset curated by GSMA and its collaborators, including telecom operators, network equipment providers and academia.

0 , which has been trained, with help from the likes of Red Hat, Dell Technologies and Microsoft Azure, using more than 400 billion tokens on AMD GPUs. “We’re training these models to provide the telco industry with more flexibility and better optimisation,” noted Andy Markus, AT&T’s chief data and AI officer, in this blog . OTel models “drive down token costs by providing model options that are suited to our tasks, and can run on right-sized hardware, either on premises or in the cloud,” he noted. ” He added: “Domain-adapted models are highly accurate and can be significantly smaller in size.

Just as healthcare, financial services and manufacturing are developing domain-specific AI approaches, the telecoms industry needs models trained on its unique standards, protocols and operating environments. This is not just about accuracy it is about enterprise requirements; reducing costs and maintaining control by deploying models across clouds and on-premise as needed. ” There’s a lot more insight in both blogs, which are recommended reading, and it’s worth remembering that the GSMA is one of the founding partners of TelecomTV’s AI-native Telco Accelerator (ANTA) initiative , so these developments will also bring critical insights to the ANTA community.

” To align tasks with the most suitable model, AT&T developed an AI gateway “that goes beyond simple model selection: It uses cache-aware routing to intelligently match each task to the most cost-effective model – without compromising on quality. It can even change models partway during multi-turn sessions. At each turn, the gateway weighs speed and cost with the expected quality of the output, then routes the prompt to the best model.