ZH reported, citing a May 22 report from China Daily.
A new phase of China’s artificial intelligence expansion is reshaping the country’s geographic and economic landscape, as energy-rich regions in the northwest rapidly transform into large-scale computing hubs powering the digital economy.
In places such as Hami in Xinjiang Uygur autonomous region and Qingyang in Gansu province, rows of data centers and server racks are replacing what were once industrial or resource-based facilities. Instead of oil pipelines and heavy machinery, the dominant sound is now the continuous hum of servers processing AI workloads around the clock.
From Energy Base to Computing Power Center
At the Tianshan Smart Valley Advanced Computing Cluster in Hami, telecom operators, cloud service providers and technology firms have arrived in large numbers over the past year. Demand for computing capacity has surged to the point where multiple clients are competing for the same server resources.
The driving force behind this shift is artificial intelligence’s rapidly growing demand for computing power. As large AI models expand in scale and complexity, the need for cost-efficient, high-capacity infrastructure has intensified.
Northwest China offers a unique combination of advantages: abundant renewable energy, lower electricity prices, cooler climate conditions and relatively inexpensive land. Together, these factors have made the region increasingly attractive for energy-intensive computing operations.
In some locations, industrial electricity costs are significantly lower than in eastern China, while overall operating expenses for computing firms can be more than 40 percent lower than in coastal regions.
Turning Green Power Into Computing Power
A defining feature of this emerging ecosystem is the integration of energy production and AI computing. The region’s vast wind and solar resources are being directly converted into digital output through data centers that run AI training and inference workloads.
Industry insiders describe this model as converting “green power into computing power,” where electricity is no longer just a utility input but a core driver of digital economic output.
In this system, AI models generate value through “tokens,” the smallest unit of computation used in large language models and other AI systems. Users and businesses pay for token consumption, and the resulting revenue flows back into covering electricity, infrastructure and operational costs.
This creates a tightly linked cycle in which energy supply, computing infrastructure and AI services reinforce each other, forming a new type of digital-energy economy.
Expanding AI Economy in Western China
The impact of this shift is already visible at the regional level. In Qingyang, Gansu, more than 500 AI-related companies had been established by 2025, generating significant revenue and creating new employment opportunities in the local digital sector.
These developments are supported by national-level policy support. China’s Government Work Report in 2026 introduced the concept of “computing power and electricity synergy,” reflecting the strategic importance of aligning energy infrastructure with digital development.
At the same time, government agencies have released action plans aimed at strengthening clean energy supply for AI computing facilities and accelerating the integration of renewable energy into digital infrastructure.
A National Computing Network Taking Shape
China’s AI computing architecture is increasingly divided into two interconnected zones.
Eastern regions such as Beijing, Shanghai and Shenzhen remain focused on low-latency applications, including real-time services like autonomous driving, e-commerce and telemedicine.
In contrast, northwestern regions are becoming large-scale hubs for AI training, inference and batch processing tasks that are less sensitive to latency but highly dependent on energy efficiency and scale.
However, network latency constraints still limit certain applications. For example, communication between Hami and Chongqing can reach around 50 milliseconds, exceeding thresholds required for ultra-real-time services. This reinforces the functional specialization between eastern and western computing zones.
The Rise of AI Infrastructure Economics
The development of northwest computing hubs also reflects broader changes in how AI systems are built and deployed.
Major AI models trained in eastern China increasingly rely on computing infrastructure located in the northwest. Some of these systems already process international workloads, serving clients in North America, Europe and the Asia-Pacific region.
This creates a cross-regional value chain in which data, computation and revenue are distributed across different parts of the country.
In this emerging model, computing power becomes a tradable economic resource — similar to energy or raw materials in traditional industries.
Domestic Chips and Technology Deployment
Northwestern computing hubs are also serving as testing grounds for domestic semiconductor technologies.
Homegrown AI chips from companies such as Huawei and other Chinese developers are being deployed at scale in data centers across the region. These systems are designed to support large AI workloads, including image processing, model inference and generative AI applications.
During peak demand periods, these clusters have demonstrated the ability to handle massive surges in computing requests, highlighting their growing importance in China’s AI infrastructure ecosystem.
Challenges in Scaling the Western AI Cloud
Despite rapid expansion, the development of large-scale computing hubs in northwest China still faces structural challenges.
One key issue is the mismatch between hardware and human resources. While infrastructure investment has accelerated, there remains a shortage of skilled technical personnel to operate and manage complex AI systems.
Logistics and supply chain limitations also present constraints, as rapid data center construction places pressure on local equipment availability and maintenance capacity.
In addition, not all digital workloads can be relocated westward. Applications requiring ultra-low latency must remain in eastern China, preserving a long-term geographic division of digital functions.
A Long-Term Structural Shift
Despite these challenges, industry forecasts suggest strong long-term growth potential. Global financial institutions project that data center expansion in China’s western regions will continue accelerating through 2026 and beyond, contributing a significant share of new computing capacity.
More broadly, the rise of northwest computing hubs reflects a structural transformation in China’s digital economy: one where energy, geography and artificial intelligence are becoming tightly integrated.
What is emerging is not just a new wave of infrastructure investment, but a reconfiguration of how computing power is produced, distributed and monetized.
In this new landscape, China’s northwest is no longer just an energy base.
It is becoming a core engine of the AI economy.