AI is too big for the European internet – Nokia
Most technology and business leaders in the US and Europe believe that current networks will require substantial evolution and investment to meet the demands of the AI supercycle. This is according to research commissioned by Nokia which surveyed about 2,000 technology and business decision-makers in the US and Europe. They included telecom and data centre infrastructure providers, businesses and organisations planning to adopt and integrate AI into their operations.
In the US, 88% of telecoms providers and enterprises said that infrastructure limitations could restrict AI’s scale, as did with 78% of respondents in Europe. The 10% discrepancy is interesting – could it be Europeans are slightly less moved by hype or fail to see the urgency of the situation?
The reasons why
Nokia claims the research explains that AI is redefining network requirements hence the infrastructure must evolve to meet its demands. For example, more workloads are shifting to uplink whereas previously downlink carried most of the traffic. Also, data flows are more distributed and expectations around latency, throughput, resilience, security and energy efficiency are rising.
Nokia argues that the changes it outlines carry implications for telcos, AI and cloud providers, and mission-critical enterprises, as well as for “national competitiveness and long-term digital leadership”.
Nokia says regarding AI applications, “autonomous vehicles and smart manufacturing lines to surveillance drones and remote health care diagnostics[…]generate large volumes of data at the edge that must be transmitted upstream for processing, making them uplink-intensive. This stresses today’s networks, which were originally engineered for downlink-focused consumer use, such as browsing websites and video streaming.”
The story so far?
“The first wave of the AI supercycle has already reshaped industries and accelerated innovation. This research shows a clear understanding across the ecosystem that future waves will demand more advanced, AI-native networks and substantial investment to strengthen network requirements.
“Connectivity, capacity, and low-latency performance are becoming ever more essential ingredients for transforming how devices interact, industries operate, and people live and experience technology as AI moves forward,” said Pallavi Mahajan, Chief Technology and AI Officer, Nokia.
The research commissioned by Nokia includes perspectives from operators, enterprises and partners about the capabilities they need from next-generation infrastructure to scale AI effectively. The research is broken down into separate geographic reports.
US in the lead
The US continues to lead global AI deployment and mass-market adoption, but 88% of respondents from there expressed concern that the expansion of network infrastructure may not keep pace with AI investment. They cited the need to optimise bi-directional data flow, expand fibre capacity, real-time training feedback, and low-latency edge infrastructure as essential priorities and building blocks for modernizing network architecture and powering the next phase of AI growth.
The report, Infrastructure First Is the New America First can be found here.
Europe
In Europe, 86% of enterprise respondents said current networks are not yet equipped to handle widespread AI adoption. Two-thirds of those surveyed said they already have AI in live use, and more than half have experienced challenges such as downtime, latency and throughput constraints associated with increasing data demands.
To address these challenges, respondents emphasised the need for consistent regulatory simplification and alignment across markets, timely spectrum availability, adjustments in competition policy to enable market consolidation, and industry-wide investment in energy-efficient, AI-ready networks.
These findings can be found in the AI is too big for the European Internet report here.
