According to Ericsson, telecommunications operators are preparing intelligent networks for the AI era, transforming simple connectivity into strategic, high-value infrastructure.
Network management is shifting from static pipelines to automated, AI-driven platforms. Upgrading to 5G Standalone and evolving toward 5G Advanced creates the baseline required to run AI workloads across operations and deliver consistent, low-latency services.
Operators need embedded intelligence to support data-intensive use cases such as generative models, agent-based applications, and robotics. Integrating specialized silicon into radio units improves energy efficiency and uplink performance, enabling networks to handle heavy processing needs closer to the edge.
Preparing intelligent networks for AI operations
Collaboration across the industry is accelerating research toward commercially viable deployments. Building autonomous systems requires interoperable technologies that span radio access computing, transport, core network functions, and management platforms.
To meet the processing demands of future connectivity, operators must align compute, cloud, and radio architectures. Joint engineering efforts—such as partnerships between Ericsson and Intel—aim to accelerate AI-native 6G across connectivity and cloud domains. These collaborations target AI-driven radio access networks and packet core use cases while addressing platform security.
Open, interoperable software is another critical layer for avoiding vendor lock-in and scaling intelligent platforms. Initiatives like the Linux Foundation’s OCUDU project foster portable, open-source CU/DU software stacks. As a founding premier member, Ericsson contributes architectural guidance intended to speed wireless innovation.
Embedding intelligence across both edge and core is essential to secure autonomous physical deployments. Partnerships involving NVIDIA and other platform providers are advancing open frameworks that integrate AI capabilities directly into network architecture to build operational trust for physical AI systems.
For long-term capital planning, operators now have clearer commercial milestones. An industry coalition including Ericsson and Qualcomm outlined a roadmap at Mobile World Congress that charts the path toward commercial 6G systems beginning around 2029.
Erik Ekudden, Group CTO at Ericsson, says: “We are already on the journey toward an intelligent fabric, and it is happening right now. With clear proof points across the entire network, we are proving that a fully AI-powered network is not a distant capability five years out.
“By bringing intelligence into every domain today, we are giving the industry the foundation it needs to scale the next generation of AI.”
Maximising architecture value in the AI era
Hardware interoperability is a primary challenge for service providers aiming to deliver commercial 6G services by 2030.
Early validation of new standards helps device manufacturers ensure their products work reliably at launch. Lab tests with Qualcomm have already validated physical-layer capabilities, exploring cmWave frequencies in the 6–8 GHz range to improve uplink performance.
Prototype user equipment from MediaTek has demonstrated features designed to reduce latency—an essential requirement for scaling extended reality and other AI-augmented applications.
Spectrum management remains an operational concern. Live demonstrations with Apple have showcased Multi-RAT Spectrum Sharing between 5G and simulated 6G environments, illustrating ways to migrate networks while preserving valuable spectrum resources.
With initial 3GPP specifications expected around 2029, connectivity leaders must assess their infrastructure readiness now. Establishing interoperability proof points enables communication service providers to plan future rollouts with greater confidence.
In the near term, telcos should prioritise maximising the value of existing 5G Standalone architectures and network APIs as AI use cases expand. Active participation in standards and ecosystem partnerships will help align internal network strategies with the broader direction of the telecom industry.
See also: Why AI and automated operations need horizontal telco clouds
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