China has set itself a bold goal: to become a global leader in AI by 2030. By 2030, AI could potentially bring $600 billion to the Chinese economy annually. The country welcomed more than 4,500 AI corporations in 2024, accounting for 15% of the global total. China also tops the 2024 Nature Index of global clinical contributions; and driving global discovery in terms of the number of patents in the AI category over the next decade. Moreover, in 2024, overall personal investment in generative AI in China will nearly quintuple, from $650 million in 2023 to around $3. 15 billion in 2024, according to Statista’s market forecasts.
China is not just a competitor in the AI race; it is a force that is reshaping the global landscape. With unprecedented government support, a thriving ecosystem of cutting-edge enterprises, and a special offering on industry-specific applications, China presents immense opportunities and urgent and demanding situations for global leaders.
China’s AI dominance is not limited to flashy models. It is a strategic game. In my studies with major Chinese AI players, current and new entrants, I see four emerging AI strategies for China in 2025:
China’s AI sector has seen explosive growth, fueled by a tough combination of government support, personal sector innovation and a vast pool of data.
The main players in the Chinese GenAI space can be divided into four groups:
Tech giants like Baidu, Alibaba, Tencent and Huawei are at the forefront of this AI revolution, introducing complicated extended language models (LLMs) that are starting to rival their Western counterparts in terms of capability and scale.
One of the most striking aspects of China’s AI landscape is the diversity and specialization of its models. From Baidu’s ERNIE Bot (the most frequently used GenAI product by domestic users, with an 11.5 per cent share) to Alibaba’s Tongyi Qianwen, these AI powerhouses are not just replicating existing technologies but innovating in ways that cater to the unique linguistic and cultural nuances of the Chinese market.
One of the main drivers of China’s AI boom is the immediate progression of an available AI infrastructure. Cloud giants such as Alibaba Cloud, Huawei Cloud, and Tencent Cloud will offer AI-as-a-Service (AIaaS) answers that democratize access to complex AI. This shift from classic infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) models to AI-centric platforms is lowering barriers to entry for businesses to leverage AI technologies.
For instance, Huawei Cloud’s Ascend service has dramatically reduced the development time for large model training from five months to just one, while Moonshot AI’s collaboration with Alibaba Cloud has significantly boosted model inference efficiency. Then, Baidu’s Qianfan platform offers 54 pre-configured models and a comprehensive toolchain (a collection of software development tools used together to perform a complex task) for customization, potentially reducing training costs by up to 90% compared to in-house development.
This approach – Model-as-a-Service – not only reduces costs but also accelerates the adoption of AI across various industries.
China is making significant strides in developing industry-specific AI applications. From finance and healthcare to education and manufacturing, Chinese companies are customizing AI solutions to address sector-specific challenges.
For example, Yilian’s MedGPT AI Doctor demonstrated professional-grade functions comparable to human doctors in real-world tests, demonstrating the possibilities of AI in medical diagnosis. Similarly, Shanghai Xuhui City’s mammoth government services model, introduced in June 2024, focuses on business lifecycle consulting, largely the powerhouse of government services.
Another case in point is global appliances manufacturer Haier: the focus is on integration of AI across its entire ecosystem, from product development to customer interaction. HomeGPT, their lead AI, uses advanced natural language processing and multimodal interaction capabilities to enhance user experiences by enabling more intuitive and responsive interactions with smart home devices.
This trend toward vertical integration and specialization gives global leaders the opportunity to explore partnerships or collaborations with Chinese AI corporations with deep sector experience.
The Chinese government has adopted a proactive approach to AI governance, balancing innovation and threat prevention. The 2023 “Interim Measures for the Management of Generative Artificial Intelligence Services” marks China’s leadership in global AI regulation, offering transparent guidance for AI progress and governance.
Furthermore, China’s publication of the “Global AI Governance Initiative” in October 2023 demonstrates its commitment to foreign cooperation in AI governance. This initiative describes China’s relationship with AI governance from a regulatory, security and progression perspective, thus contributing to the fabric of a world. framework for the guilty progression of AI.
More recently, in May 2024, the Technical Committee on National Information Security Standards (NISSTC) published a new draft regulation titled Cybersecurity Technology: Basic Security Requirements for Generative Artificial Intelligence (AI) Services. It covers protective AI models, data protection, and implementation of general security protocols. Provides guidance for safety testing and standard-setting for service providers and regulators.
As China continues to push the boundaries of AI application, global executives who can navigate this complex landscape stand to gain significant advantages in the AI-driven future of business. But, China’s AI development in 2025 is not without challenges.
First, the ongoing technological rivalry between the United States and China has led to significant export controls, specifically on complex semiconductors for AI development. To what extent will this have any effect on the capabilities of China’s cyber force?
Second, attracting and retaining top AI talent remains a challenge. Although China produces a significant number of AI graduates, competition with global tech hubs and a diverging geopolitical reality, can deter talent from staying or returning to China.
Third, the availability of knowledge. Contrary to popular belief, China has a knowledge problem. Much of the knowledge is fragmented between sectors and government agencies. Furthermore, the quality of knowledge is a constant concern. Finally, due to geopolitical tensions and constraints, Chinese corporations would likely have limited access to global knowledge sets that are widespread and competitive AI models.
By leveraging the unique characteristics of China’s AI ecosystem and adapting their methods accordingly, business leaders can position their organizations at the forefront of the global AI revolution.
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