Artificial intelligence is becoming an infrastructure issue for the energy sector as utilities contend with renewable generation, distributed power resources and rapidly growing electricity demand from data centers. At HUAWEI CONNECT 2026, Huawei presented a strategy for applying AI and digital infrastructure across the power system, with particular attention to the low-voltage networks that connect utilities with end users.
Huawei’s 2026 Global Electric Power Summit brought together more than 600 representatives from utilities, industry organizations, technology partners and media to examine how AI and digital technologies could reshape electricity generation, distribution and consumption.
The central theme was a transition from using digital technology to improve individual power-system functions toward closer coordination between electricity infrastructure and computing infrastructure.
That shift is becoming increasingly important. AI data centers are creating new electricity demand while renewable energy introduces more variable and distributed sources of generation. At the same time, power networks must manage increasingly complex flows between utilities, businesses, households and distributed energy resources.
Huawei argues that the low-voltage side of the grid will become a particularly important area for intelligent infrastructure. Unlike high-voltage transmission networks, low-voltage systems involve enormous numbers of endpoints and traditionally provide less visibility into real-time operating conditions.
The company’s proposed approach centers on six capabilities: observability, measurability, controllability, adjustability, tradability and traceability. Together, these capabilities are intended to give utilities better visibility into distributed assets and more options for managing demand and supply.
Huawei Electric Power Digitalization Business Unit CEO David Sun described the objective as improving data speed and quality while reducing operational costs. The company is also emphasizing digital skills and infrastructure alongside regulatory treatment of digital assets.
The summit’s six showcased projects illustrate how that strategy translates into different operating environments. They include a digital grid project with Brazil’s CEMIG, distribution-grid and microgrid coordination at China Southern Power Grid’s Guangzhou Baiyun Power Supply Bureau, intelligent distribution-network operations in Shaoshan, intelligent electricity supply and consumption in Jiangxi, a ±800 kV ultra-high-voltage digital converter station in Zhejiang and a power communications network in Liaoning.
These projects span generation, transmission, distribution, communications and consumption rather than focusing on a single AI application.
The broader technology trend is significant for AI infrastructure vendors. Companies such as Microsoft, Google, Amazon and NVIDIA are investing heavily in the computing infrastructure required for AI workloads, while utilities increasingly need digital systems capable of forecasting demand, monitoring assets and coordinating increasingly distributed energy resources.
For energy companies, however, AI adoption is unlikely to be determined by models alone. Sensors, communications networks, edge computing, data quality, cybersecurity and integration with legacy operational technology will determine whether intelligent systems can function reliably across critical infrastructure.
Huawei’s approach therefore places AI within a much larger modernization effort: building the digital foundation needed for power systems to become more observable, responsive and software-driven.
Market Landscape
The convergence of AI infrastructure and energy infrastructure is creating a new technology layer around the modern power grid. AI data centers are increasing electricity demand, while renewable generation, batteries, microgrids and distributed energy resources are making grid management more complex.
This creates opportunities for AI across forecasting, predictive maintenance, asset monitoring, grid optimization and demand management. It also increases the importance of edge computing and industrial connectivity because many power-system decisions require low-latency data and high reliability.
For utilities, the technology challenge extends beyond deploying an AI model. Modernization requires interoperable operational technology, communications infrastructure, cybersecurity, high-quality data and employees capable of managing increasingly software-defined power networks.
Huawei’s six showcased projects reflect that broader systems approach, positioning AI as one component within a larger digital transformation of electricity infrastructure.
Top Insights
- Huawei is positioning AI and digital infrastructure as foundational technologies for managing renewable generation, distributed energy resources and increasingly complex power networks.
- The company’s low-voltage strategy emphasizes visibility, measurement and control as utilities seek greater intelligence across highly distributed electricity infrastructure.
- Six global showcases demonstrate applications spanning digital grids, microgrids, intelligent distribution, high-voltage infrastructure and power communications networks.
- AI data centers are adding electricity demand while renewable energy is increasing grid complexity, creating stronger links between computing infrastructure and power-system planning.
- Enterprise-scale AI adoption in utilities will depend on connectivity, data quality, cybersecurity, edge computing and operational-technology integration as much as AI models.
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