Networks for AI: Building AI-Driven Networks for an AI-First World
The era of AI requires more than just connectivity; it demands a new generation of AI driven networks that are intelligent, responsive, and optimised for real-time, data-intensive workloads. The GSMA’s ‘Networks for AI’ workstream unites the mobile ecosystem to evolve our networks, transforming them from passive data carriers into active enablers of AI innovation.
The strategic imperative for AI-ready networks
A new demand on a global scale
As artificial intelligence becomes embedded in every industry, the demands on our digital infrastructure are fundamentally changing. Legacy network architectures, designed for different traffic patterns, are no longer sufficient to handle the vast, distributed, and low-latency workloads of modern AI. Processing data efficiently, securely, and in real-time requires a strategic shift in network design from the core to the edge.
A proactive, collaborative approach
The GSMA provides a forum for the mobile ecosystem to address this challenge proactively. Our ‘Networks for AI’ initiative is not about passively reacting to change; it is about actively building the future-ready infrastructure needed to support the next wave of AI services and applications, and to enable truly AI-driven networks at a global scale.
The architectural pillars of an AI-ready network
Our work focuses on several crucial technologies that are transforming mobile networks. We are facilitating the discussions, standards, and best practices required for their successful, interoperable deployment.
5G-Advanced
The opportunity
Positioned as the next major milestone, 5G-Advanced (or 5.5G) moves beyond connectivity to deliver significant integrated enhancements in speed, latency, mobility, and efficiency. These capabilities are being developed specifically to support highly immersive and interactive AI applications that require deterministic performance and reliability.
The GSMA’s role
The GSMA is actively involved in global discussions, shaping the requirements and standards to ensure these advancements unlock new potential for the enterprise market and create a robust platform for AI innovation.
Related reading
Edge computing
The opportunity
Processing AI workloads at the network edge—closer to where data is generated—is a critical strategy. It reduces latency for real-time applications, saves significant backhaul bandwidth, enhances data security and privacy, and lowers operational costs compared to relying solely on centralised cloud infrastructure.
The GSMA’s role
Through initiatives like the Operator Platform project, the GSMA is working to make these powerful edge capabilities easily and widely available on an interoperable, global basis, creating a unified platform for developers and enterprises.
Related reading
Network slicing
The opportunity
This core 5G capability allows operators to create multiple, isolated virtual networks on top of a single physical infrastructure. For AI, this is a game-changer. Critical AI applications, such as autonomous vehicle control or factory robotics, can be provisioned with a dedicated network “slice” that guarantees specific Quality of Service (QoS) metrics like high bandwidth and ultra-low latency.
The GSMA’s role
Our work focuses on developing the frameworks and best practices for the commercialisation and orchestration of network slicing, ensuring operators can deliver these tailored connectivity solutions for demanding AI use cases.
Related reading
A hub of collaborative action
Our focused work on Networks for AI is helping the industry move towards scalable, secure AI-driven networks, supported by a rich ecosystem of GSMA programmes. These initiatives provide the practical tools, shared intelligence, and ethical frameworks necessary for success.
Join the ‘Networks for AI’ workstream
Your expertise in network architecture, 5G-Advanced, edge computing, and service orchestration is needed to shape the future of AI-driven, AI-ready networks across the mobile industry. By joining the Mobile AI Community, you can contribute directly to the technical frameworks and best practices that will define the next generation of AI-ready networks.