TITLE: AI Growth Outpaces Network Infrastructure, Studies Find

Artificial intelligence expansion is surpassing the capabilities of current global network infrastructure, according to two studies conducted in the United States and Europe.

The research, which surveyed more than 2,000 senior technology decision-makers, indicates that AI workloads are placing unprecedented stress on systems originally designed for consumer-oriented downlink activities like web browsing and video streaming. As AI applications proliferate in sectors such as autonomous vehicles, smart manufacturing and remote healthcare, data generation at the network edge has surged, demanding greater uplink capacity, lower latency, enhanced resilience, improved security and better energy efficiency.

Background on the Studies

The surveys analyzed AI ambitions against real-world network limitations. Respondents from operators, enterprises and partners across both regions reported that distributed data flows and uplink-intensive operations are challenging existing infrastructure. For instance, surveillance drones and diagnostic tools in healthcare produce large data volumes that must be sent upstream for processing, shifting network demands away from traditional patterns.

This mismatch is seen as a barrier to the next wave of innovation. Without upgrades, the global AI supercycle—characterized by rapid scaling of intelligent systems—risks being constrained, potentially slowing economic and societal benefits.

Key Findings on Network Stress

The studies highlight how AI is transforming network requirements. Workloads are increasingly bidirectional and edge-based, requiring networks to handle complex, real-time interactions. Expectations for performance have risen sharply: decision-makers cited needs for higher throughput to support AI-driven operations and greater security to protect sensitive data flows.

In the US, enterprises emphasized the need for resilient networks to underpin productivity gains from AI adoption. European respondents echoed these concerns, pointing to distributed architectures that demand seamless connectivity across borders and industries.

Pallavi Mahajan, a technology and AI officer, noted that advanced, AI-optimized networks are essential. "Connectivity, capacity and low-latency performance are critical for how devices interact and industries evolve," she said in comments tied to the research.

AI's broader impact includes ecosystem-wide upgrades. Companies adopting AI report smoother operations, reliable services and compounded productivity. At a governmental level, efficient public services could emerge, positioning AI-ready economies to attract investment and drive growth.

Energy Constraints as a Growing Barrier

Energy availability emerged as a major concern in both regions, with AI's compute-intensive nature straining outdated electricity grids. These grids, built decades ago, were not designed for the dense, continuous workloads of modern AI systems, leading to power bottlenecks and escalating costs.

In the US, 54% of surveyed companies indicated that energy expenses would significantly affect their AI expansion plans. The figure was higher in Europe, where 61% of respondents are relocating or considering relocating computational resources abroad to access more reliable and affordable power.

Mahajan described AI as placing strain on both networks and supporting power infrastructure. "As workloads drive higher utilization and nonstop operations, grid availability and efficiency are key limits on scaling," she said.

Regional disparities could reshape economic landscapes: areas with abundant energy may foster thriving AI ecosystems, while shortages could cap development. This underscores the need for integrated strategies addressing power alongside connectivity.

Opportunities for Transatlantic Collaboration

The research reveals a consensus across the US and Europe on the necessity of next-generation networks to handle complex AI demands. Stakeholders from various sectors agree that capabilities like enhanced capacity and low-latency edge processing are vital for effective scaling.

This shared perspective opens avenues for joint industry and policy efforts to bolster digital foundations. Modernizing networks could ensure both regions capture AI's benefits, from job creation to societal advancements.

Calls for action include ecosystem-wide collaboration among operators, enterprises, policymakers and technology providers. Simplified regulatory frameworks would facilitate timely investments, enabling infrastructure upgrades without undue delays.

Mahajan emphasized coordinated steps: "The US and Europe can modernize networks together, accelerating innovation and delivering AI's impact at scale."

Strategic decisions on infrastructure today will influence the trajectory of intelligent technologies over the coming decade, determining competitive edges in an AI-driven world.