The solution combines AT&T’s IoT core network and Cisco’s mobility services platform, allowing localized data routing, predictable performance, and secure connectivity for enterprise and industrial environments
In sum – what to know:
Edge networks – AT&T and Cisco integrate AI inference into telecom infrastructure to process data closer to devices, reducing latency and cloud dependency.
Enterprise cases – Initial deployments focus on video analytics, industrial monitoring, and transportation systems requiring real-time insights and secure data handling.
Compute layer – GPUs and developer tools support AI model deployment across distributed IoT environments, expanding edge AI scalability.
AT&T and Cisco have announced a collaboration to integrate networking, edge computing, and AI infrastructure, with support from Nvidia, to enable real-time data processing closer to where it is generated.
The solution combines the U.S. telco’s IoT core network with Cisco’s mobility services platform, allowing localized data routing, predictable performance, and secure connectivity for enterprise and industrial environments. Cisco’s AI Grid, built with Nvidia infrastructure, is designed to support AI inference at the network edge, reducing reliance on centralized cloud processing.
The companies said the architecture is intended for use cases such as video surveillance, transportation systems, and industrial automation, where low latency and data control are important. The partners also noted that the system applies security policies across devices, network connections and applications.
Powered by AT&T’s global IoT connectivity, the collaboration also brings Cisco’s AI capabilities into the AT&T network to enable intelligent automation and actionable insights across millions of connected devices at scale, powered by Nvidia GPUs.
A demonstration was conducted at AT&T’s Discovery District in Dallas, focused on public safety applications using video analytics. The companies are also testing the solution in an industrial setting with TanMar Companies in Louisiana, where edge-based video systems are being used for site monitoring and operational visibility.
Shawn Hakl, senior vice president of product at AT&T Business, said: “Delivering scalable, highly secure AI services to meet enterprise and developer needs is pivotal to our IoT connectivity strategy.”
Chris Penrose, global vice president of business development in the telco unit at Nvidia, added: “Distributed computing is the next frontier for AI infrastructure, and telecommunications networks sit at the heart of that buildout. By integrating Nvidia AI infrastructure with AT&T’s highly secure IoT connectivity and Cisco’s networking, we’re giving app providers the tools to deliver real‑time intelligence at the edge—keeping data local, secure, and under customer control while enabling scalable AI across millions of connected devices.”
In a recent blog post, Nvidia said it was working with a number of partners to make software-defined AI-RAN as a foundation for future wireless networks. Nvidia highlighted that the approach integrates AI workloads directly into radio access networks, supporting the transition toward AI-native 5G and early 6G architectures.
In this field, Nvidia and Nokia expanded collaborations with operators in Europe, Asia and North America. Companies including T-Mobile US, SoftBank and Indosat Ooredoo Hutchison reported progress in deploying AI-RAN systems in live network environments, according to AI chipmaker.
T-Mobile demonstrated over-the-air performance using Nokia’s software and massive MIMO radios in the 3.7 GHz band, supporting commercial devices and applications such as video streaming and AI-based services.
SoftBank conducted a live trial using fully software-defined 5G, achieving a 16-layer massive MIMO configuration, while Indosat Ooredoo Hutchison has implemented software-defined 5G with Nokia’s vRAN software on Nvidia AI-RAN platforms, moving from proof of concept to pre-commercial field validation.
Nvidia also noted that its latest ´State of AI in Telecom´ report showed that the industry is stepping up AI-native RAN and 6G investments, with 77% of respondents anticipating a much faster time to deployment of this new AI-native wireless network architecture.
Earlier this week, Nvidia and T-Mobile US announced a collaboration with Nokia and a group of AI developers to deploy physical AI applications over distributed edge networks built on AI-RAN infrastructure. The initiative aims to support real-time AI workloads by integrating compute capabilities directly into telecom networks.
Under this initiative, T-Mobile is piloting Nvidia’s AI-RAN systems to enable edge-based processing at both cell sites and mobile switching offices. The setup allows AI applications to run alongside 5G connectivity, supporting use cases that require low latency and continuous data processing across wide-area networks.
Jensen Huang, founder and chief executive at Nvidia, recently told the firm’s annual AI ecosystem event GTC in San Jose, California: “Telecoms is about as large as the world’s IT industry – about $2 trillion. You see base stations everywhere; [they are] one of the world’s infrastructures; the infrastructure of the last generation of computing. That infrastructure will be completely reinvented. And the reason is very simple: that base station, [which has done] one thing [until now], is going to be an AI infrastructure platform [when] AI runs at the edge.”
Returning to AT&T, the U.S. telco had announced at MWC 2026 a “preview”, available from the second quarter of this year, of its last-mile enterprise AI connectivity offering with AWS, which brings its fiber and 5G systems “directly” into AWS environments. The service, called AWS Interconnect, offers a site-to-cloud channel for AI workloads via AT&T’s 5G-based fixed wireless access (FWA) solution in enterprise offices, and its fiber metro and long-haul systems.
AT&T said the solution will reduce network complexity and latency for real‑time analytics, machine learning, and agentic AI use cases. The firm is building an “AI‑ready network”, it said, to scale network network performance for spiralling enterprise workloads. It said it will expand its fiber capacity to 1.6Tbps across key metro and long‑haul routes.
The U.S. operator also recently said it is working with AWS to provide high-capacity interconnect fiber to AWS data centers.
