How Nokia’s AI Networking Lab Prepares Telcos for AI Demands

AI puts networks under pressure in places most users never see. Behind every chatbot prompt and automated business tool sits a data centre network that now needs to move huge amounts of information with speed and precision.

Nokia wants to position itself in the middle of that transformation. 

The vendor has launched a new AI Networking Innovation Lab in Sunnyvale, California, which is aimed at helping operators, hyperscalers and cloud companies test how AI infrastructure behaves under real-world conditions.

The facility focuses on one of the biggest questions facing the telco and cloud sectors: how networks cope with AI workloads that demand low latency, high throughput and constant availability across distributed environments.

This is becoming harder as AI services scale across cloud platforms, enterprise networks and edge infrastructure.

Nokia says the lab gives partners a place to validate technologies before they reach live deployment.

Rudy Hoebeke, Vice President of Software Product Management at Nokia, says: "The launch of Nokia’s AI Networking Innovation Lab marks a major milestone in our commitment to drive the next era of AI-native connectivity.

"As the industry continues to evolve with solutions like scale-across and AI-Grid, this lab is poised to accelerate AI networking technology that will not only support but optimise these emerging industry offerings.

"This centre gives our customers and partners early access to new technologies, deeper collaboration with the world’s leading AI ecosystem players and the confidence that their networks are validated under more realistic AI conditions.

"By accelerating innovation and reducing deployment risks, we’re enabling the industry to deliver faster, more reliable, and more sustainable AI experiences to people and businesses everywhere."

AI puts pressure on telco infrastructure

The launch reflects how AI infrastructure as much about networking as it is about compute.

With soaring demands, telco operators and cloud providers need data centre fabrics capable of handling AI training and inference traffic without bottlenecks or downtime.

Nokia says traditional networking approaches no longer meet the demands created by large-scale AI systems.

The company is instead building an environment where switching silicon, networking protocols and automation tools can be tested together under operational pressure.

The lab also acts as a proving ground for Nokia Validated Designs, which are reference architectures tested across multi-vendor environments.

These designs are intended to help operators reduce deployment risks and integration complexity when building AI-ready networks.

Arno van Huyssteen, Vice President of Global Telecommunications for Nscale, says: "Nokia is a strategic networking partner for Nscale as we build towards AI Grid, and the engineering rigour behind their Validated Designs reflects the kind of innovation needed to enable next-generation AI infrastructure.

"The depth of hardware, software and failure testing behind those blueprints is what will give operators the confidence to deploy complex AI environments faster, with fewer integration risks and less operational disruption.

"We're excited to collaborate in the AI Networking Innovation Lab to help push the boundaries of AI-native networking and validate the next generation of solutions before they reach production."

Partners target interoperability and AI scale

Nokia is building the facility around ecosystem collaboration with silicon vendors, GPU companies, cloud platforms and testing providers.

The aim is to improve compatibility between networking layers and avoid fragmented AI infrastructure deployments.

AMD is among the companies working with Nokia through the initiative. The chipmaker says open ecosystems are significant as customers look to avoid dependence on single-vendor AI stacks.

Travis Karr, Corporate Vice President, HPC and Sovereign AI at AMD, says: "AMD believes customer collaboration and an open ecosystem are fundamental to accelerating AI innovation.

"By co-developing solutions with partners, such as Nokia in their AI networking innovation lab, we ensure our AMD enterprise AI solutions are tested with Nokia data centre switches on real-world workloads and network demands.

"An open, standards-driven approach empowers customers to integrate seamlessly across heterogeneous environments, avoiding lock-in and fostering industry-wide advancement in AI."

The lab also supports testing across multiple AI transport technologies, including Ultra Ethernet Consortium protocols and RoCEv2, or Remote Direct Memory Access over Converged Ethernet version two, which is commonly used in high-performance AI networking.

For telco providers building AI services into enterprise and cloud offerings, those standards are becoming more important as networks scale.

Real-world testing is core to AI rollout

One of the biggest themes running through Nokia’s announcement is realism.

The company says the lab recreates operational AI workloads to test congestion, automation and failure scenarios rather than relying on theoretical performance metrics.

Keysight is using the facility to emulate AI training environments at scale and assess how networks perform under stress.

Ram Periakaruppan, Vice President and General Manager, Network Applications and Security business at Keysight, says: "Partnering with Nokia in the AI Networking Innovation Lab has enabled us to benchmark and optimise AI networks under real-world conditions.

"Keysight emulated AI training workloads at scale across a range of AI transports, from UEC and RoCEv2 to emerging lossless fabric architectures.

"Together, we are helping accelerate AI network adoption by giving operators and hyperscalers the validated insights needed for confident, large-scale deployment."

As telco operators push further into AI infrastructure, networking vendors are competing on validation, automation and ecosystem support.

Nokia is betting that operators investing in AI services and cloud connectivity will need tighter integration between data centre networking, cloud architecture and operational testing long before those services reach customers.