China aims for AI-powered energy dominance by 2030

China has announced plans to accelerate artificial intelligence integration across its energy sector, with goals of widespread application by 2027 and global leadership in AI-powered energy systems by 2030. This strategy positions China to dominate both the energy inputs that AI consumes and the renewable technology exports that could reshape global energy markets, potentially challenging U.S. leadership in the worldwide AI competition.

The big picture: China’s National Development and Reform Commission and National Energy Administration jointly released plans to integrate AI across hydropower, nuclear, thermal, oil, gas, and coal sectors as part of a broader strategy to achieve energy independence while maintaining its position as a leading green technology exporter.

Why this matters: The initiative represents a fundamental shift in how nations approach AI development, with China focusing on infrastructure optimization rather than just model advancement, potentially allowing it to “wrest the future of energy from Washington’s hands” by attracting energy-hungry nations as customers.

Key energy dynamics: China currently relies heavily on Russian energy imports while simultaneously building renewable capacity.

• China remains the largest global buyer of Russian fossil fuels, accounting for 40% of Russia’s export revenue as of August 2025.
• Of China’s Russian energy purchases, 58% are crude oil imports, followed by 15% coal, 12% pipeline gas, and 10% oil products.
• Despite seeing 25% growth in wind and solar electricity generation between 2024 and 2025, renewable energy remains insufficient for China’s growing industrial and household demands.

How AI will be deployed: The strategy targets specific applications across multiple energy sectors to address China’s baseload power challenges.

• In hydropower: AI will enhance weather and water flow forecasting accuracy, optimize decision-making, and support station maintenance in cold, high-altitude regions.
• In nuclear power: AI will strengthen safety support systems, including early warning mechanisms, operational analysis, and automated startup and shutdown processes.
• In thermal power: AI applications focus on fuel management, operational control, equipment maintenance, and accelerating plant construction.

U.S. competitive position: American renewable energy integration lags significantly behind China’s efforts, with implementation challenges hampering progress.

• The U.S. remains a global leader in AI chips and model development, but widespread implementation has lagged in utilities and infrastructure.
• American firms like Constellation Energy, Google, and Duke Energy have started AI integration processes, but most remain far from achieving AI maturity.
• High upfront costs, limited technical expertise, and fragmented investment strategies have led to underwhelming pilot programs.

Strategic implications: The two nations are pursuing fundamentally different AI approaches that reflect distinct philosophies about technology deployment and economic returns.

• America’s AI strategy revolves around massive investments to boost productivity and reduce expenses through wage, waste, and overhead reductions.
• China’s approach focuses on reinvestment into energy inputs that AI consumes and distribution across systems with less promise for revolutionary change.
• American over-investment risks creating a bubble where productivity gains don’t justify investments, while China’s model risks difficulties from lack of short to medium-term monetization.