Transforming industries with AI: Lessons from China’s journey

By Guardian Correspondent , The Guardian
Published at 06:00 AM Jan 24 2025
China balances safety and innovation when it comes to AI
Photo: Agencies
China balances safety and innovation when it comes to AI

ARTIFICIAL intelligence (AI) is rapidly reshaping industries worldwide, with China emerging as a key player in demonstrating how AI can drive industrial transformation at scale.

With a growing AI industry valued at over $70 billion and a dynamic ecosystem of over 4,300 companies, China provides insights into how nations can align strategy, innovation, and ecosystem development to harness AI's transformative potential.

The newly released whitepaper Industries in the Intelligent Age - Blueprint to Action: China's Path to AI-powered Industry Transformation from the World Economic Forum's AI Governance Alliance highlights how the country uses AI to address industry-specific challenges while illustrating the complexities of responsibly scaling AI innovations.

While China’s model may not be universally applicable, it offers valuable lessons on fostering industry-specific innovation and integrating AI into complex ecosystems.

Strategic foundations for AI growth

China’s trajectory in AI is underpinned by a structured and phased approach. The Next Generation AI Development Plan, launched in 2017, sets ambitious goals, aiming to position AI as a core driver of economic transformation by 2025 and establish the country as a global hub for AI innovation by 2030.

This plan reflects an emphasis on long-term planning, which includes balancing innovation with safety through adaptive regulations.

For example, initiatives such as the Interim Measures for the Management of Generative AI Services (2023) and the AI Safety Governance Framework address emerging risks while fostering technological advancement.

These frameworks enable experimentation with AI applications while ensuring alignment with ethical principles – a balance many nations seek to achieve.

The role of ecosystem enablers

China’s progress in AI is facilitated by a robust ecosystem that integrates infrastructure, data, talent, and innovation. Investments in advanced technologies, such as its expansive 5G networks and energy-efficient green data centres, provide a solid foundation for AI applications.

These infrastructural advances support the deployment of high-capacity computing power, which is essential for training large-scale AI models.

Data also plays a pivotal role. With one of the fastest-growing data ecosystems globally, China has developed strategies to improve data interoperability and accessibility across sectors.

Efforts to establish the National Data Administration demonstrate a commitment to ensuring that data becomes a cornerstone of technological innovation.

In parallel, China’s education and research institutions have significantly scaled AI-related programmes, reflecting the country’s recognition of the need for a skilled workforce.

AI’s industry-specific impact

China’s approach to AI emphasizes practical applications tailored to the unique needs of various industries.

By integrating AI technologies such as digital twins, predictive maintenance and generative AI, industries such as manufacturing, healthcare, transportation, retail and energy are witnessing transformative advancements.

These include optimizing production processes, enhancing diagnostics and patient care, enabling autonomous transport systems, personalizing consumer experiences and improving renewable energy management.

This sector-focused innovation exemplifies how AI can be applied at scale to drive efficiency, sustainability, and new business and operational models. The emphasis on tailoring AI solutions to specific needs showcases an approach other regions could adopt to maximize impact and overcome barriers to adoption.

Challenges and opportunities

Despite its successes, China’s AI development is not without obstacles. Issues such as fragmented data flows, uneven regional capabilities and a significant talent gap present ongoing challenges.

Addressing these will require collaborative efforts across sectors and borders. China’s experience also highlights the importance of maintaining interoperability and fostering partnerships to enable scalable AI adoption.

For global stakeholders, the lessons from China are not prescriptive but illustrative. They demonstrate how aligning strategy, ecosystem enablers and industry-specific innovation can help unlock AI’s potential.

However, the journey also emphasizes the need for responsible development and international collaboration to navigate the complex interplay between technology, society and governance.

The AI Governance Alliance continues to explore how AI can catalyze sustainable, inclusive growth. Through such platforms, stakeholders can collaborate to ensure that AI development adheres to high ethical standards while addressing global challenges effectively.

The path forward will require balancing innovation with responsibility – an endeavour that benefits from shared insights and collective action.