Artificial intelligence has emerged as a central theme at the 2026 World Economic Forum in Davos, reflecting its growing influence on economic competitiveness, industrial transformation and sustainability strategies worldwide. China is positioning AI as a core engine of national productivity growth, low-carbon transition and international engagement, while also seeking a stronger role in shaping global norms around AI governance.

As global attention focuses on how AI can balance economic gains with environmental and social responsibility, China’s approach combines large-scale industrial deployment with policy-led coordination across energy, manufacturing and digital infrastructure.

AI Accelerates Industrial Modernisation Across Energy Systems

AI adoption is reshaping both traditional and advanced industrial sectors in China, with early deployments concentrated in energy infrastructure where efficiency and reliability are critical. In Jiangsu province, China’s first salt cavern-type underground gas storage facility has integrated AI-driven optimisation systems to manage gas injection and extraction processes. By narrowing thousands of operational variables into a smaller set of critical decision points, the system enables real-time monitoring, predictive control and automated execution, improving operational stability and supply management.

In renewable energy, AI-based forecasting and control systems have enhanced resilience against extreme weather. During Typhoon Matmo in 2025, wind farms in Guangdong province relied on large-model early warning systems that allowed engineers to remotely adjust turbine positioning, reducing damage risks and maintaining grid stability. These applications highlight AI’s growing role in managing climate-related operational risks.

Digital Twins Support Low-Carbon Energy Production

China has also deployed AI-enabled digital twin systems across oil and gas operations, integrating underground reservoir modelling with surface infrastructure simulations. These systems allow operators to predict reservoir behaviour, monitor mixed oil, gas and water flows in real time, and identify potential risks such as water or gas breakthroughs before they affect production.

In the petrochemical sector, Sinopec has integrated AI optimisation tools with carbon capture, utilisation and storage technologies at its Shengli Oilfield. By dynamically adjusting temperature and pressure parameters, the system improves carbon capture efficiency while using digital simulations to model CO2 injection pathways. This enables simultaneous oil recovery and long-term carbon sequestration, aligning production objectives with emissions reduction goals.

Read more: China Unveils ISSB-Aligned Climate Disclosure Standard, Investors Urge Phased Rollout

Manufacturing Efficiency Gains Support Sustainability Goals

AI is also reshaping China’s manufacturing base, where efficiency improvements translate directly into lower resource use and reduced waste. In Shandong province, AI-powered monitoring systems deployed at an industrial tyre factory track production in real time, from raw material input to final delivery. These systems have increased production efficiency by around 30 percent while cutting product defects by roughly half.

Automation driven by AI has reduced manual intervention, improving workplace safety and lowering environmental impact through tighter process control. These developments are part of a broader national effort to integrate AI with the industrial internet, strengthening manufacturing competitiveness while supporting cleaner production models.

AI as a Pillar of China’s Sustainability Strategy

China’s use of AI is closely linked to its sustainability agenda, particularly in energy efficiency, emissions reduction and resource optimisation. By embedding AI into energy systems, manufacturing and infrastructure planning, the country is seeking to decouple productivity growth from resource intensity.

This approach reflects a broader policy direction that treats digitalisation and sustainability as mutually reinforcing objectives rather than competing priorities. AI is increasingly viewed as a tool for managing complex trade-offs between economic expansion, environmental constraints and system resilience.

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Shaping Global AI Governance and Cooperation

Beyond domestic deployment, China is positioning itself as an active participant in global AI governance. In 2023, the country introduced the Global AI Governance Initiative, calling for international cooperation on AI safety, ethics and regulation. The initiative emphasises transparency, inclusivity and responsible deployment as AI capabilities scale.

In July 2025, China hosted the World Artificial Intelligence Conference in Shanghai, where the Global AI Governance Action Plan was released. The plan urges governments and industries to unlock AI’s economic potential while ensuring reliability, controllability and fairness. Later that year, China proposed the AI Plus International Cooperation Initiative, signalling its intention to collaborate with other countries on AI-enabled industrial development.

China has also launched capacity-building programmes aimed at developing economies, offering training and policy dialogues through initiatives such as the AI Capacity-Building Action Plan for Good and for All. These efforts focus on knowledge transfer, technical skills and responsible AI deployment, positioning AI as a shared development tool rather than a concentrated advantage.

AI, Sustainability and Strategic Positioning

China’s expanding use of AI across productivity, energy and sustainability reflects a strategic effort to integrate digital technologies into long-term economic planning. By combining large-scale industrial deployment with international governance initiatives, the country is seeking to shape both how AI is used domestically and how it is regulated globally.

As AI continues to redefine competitiveness and sustainability outcomes, China’s approach offers a case study in state-coordinated digital transformation that links economic growth, environmental performance and geopolitical influence.

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