Blueprint to Action Chinas Path to AI-Powered Industry Transformation 2025

Key challenges in China’s AI development4 China’s journey towards impactful AI transformation calls for collaboration across sectors and borders to unlock its full potential. Infrastructure and computing power China has become one of the leading forces in global computing power development. China’s computing advantage is expected to extend beyond mere capacity to include higher computational efficiency, broader application of emerging technologies and more comprehensive infrastructure support. However, several challenges need to be addressed to maintain this momentum. These include improving network connectivity to facilitate seamless communication between distributed computing centres, managing the diversity of computing resources to ensure interoperability, optimizing compatibility across diverse chip architectures and instruction sets, and promoting greater collaboration among ecosystem stakeholders. Data use China’s extensive data resources are a cornerstone for its AI development. Despite this vast volume, challenges persist in data quality, interoperability and accessibility, which impact the effective training and deployment of AI models. Fragmented data flows across industries hinder the ability to consolidate data into a coherent, accessible resource pool for AI applications. These data islands prevent effective AI model training and limit insights across sectors. Government agents and companies are working to improve data interoperability and encourage cross- sector data sharing and structured cross-border data circulation under-regulated frameworks to unlock the full value of China’s data ecosystem. By tackling these data-related challenges, China can further bolster its AI ecosystem while contributing to a more cohesive and innovative global data landscape. Algorithms and model sophistication While China has made notable progress in both general-purpose and industry-specific AI models, there remains an opportunity to increase basic research and fundamental innovation. Given the complexities and demands of industrial applications, Chinese companies often find it beneficial to prioritize specialized, smaller models tailored for specific scenarios. This practical approach has helped strengthen China’s competitiveness in terms of product-market fit and affordability. However, it also suggests that there is further potential for pioneering breakthroughs and transformative advancements. Addressing this area of opportunity could involve continued innovation in core algorithmic capabilities, possibly through encouraging closer partnerships between industry and academic institutions. Such collaborations can accelerate the development of adaptable algorithms and enable China to further advance the sophistication of its AI capabilities. AI proficiency and talent Although China is home to nearly half of the world’s top AI researchers, the sheer demand for such talent has led to notable shortages. According to the country’s Ministry of Human Resources and Social Security, the talent gap in AI in China exceeds 5 million people, with a supply-demand ratio as high as 1:10.66 As AI integration across industries accelerates, the demand for interdisciplinary talent with a deep understanding of both AI and specific industry contexts is growing. Yet existing education and on- the-job training must scale up to meet this demand. Establishing joint initiatives between industry, academia and government can facilitate targeted training, on-the-job skill enhancement and tailored curriculum development. Looking ahead, global cooperation and open dialogue on talent development will be increasingly important. Engaging in international exchange programmes, research partnerships and best- practice sharing can help align global education standards and create a collaborative ecosystem for talent growth. As AI integration across industries accelerates, the demand for interdisciplinary talent with a deep understanding of both AI and specific industry contexts is growing. Blueprint to Action: China’s Path to AI-Powered Industry Transformation 25