China AI Strategy: Policy, Regulation & Global Impact in 2025

China is scaling up its artificial intelligence ambitions at an unprecedented pace. Morgan Stanley projects its domestic AI market could reach $1.4 trillion by 2030, a target that aligns with Beijing’s explicit goal of global AI leadership. 

In 2024 alone, it accounted for 61.5% of new global generative AI patents, while the core AI industry exceeded ¥700 billion ($96 billion), supported by an AI chip market worth more than ¥140 billion ($19 billion). As of April 2025, China had filed 1.57 million AI patents — 38.6% of the global total, the highest worldwide. 

The government has paired massive state funding with strict regulation, while working closely with major tech firms and local governments to accelerate adoption. China’s strategy rests on three pillars:

• Building a self-sufficient AI ecosystem to reduce foreign dependence on chips, hardware, and algorithms.
• Embedding AI across the economy and defense, from healthcare and transport to smart cities and intelligentized warfare.
• Exporting governance models worldwide, using initiatives like the Global AI Governance Initiative (2023) and the Shanghai Declaration on Global AI Governance (2024) to shape global rules.

This article examines the strategy through three lenses: the policy timeline shaping its evolution, the regulatory framework enforcing development, and the global impact of China’s expanding influence.

Key Takeaways of China AI Strategy

Here’s a brief overview of the following article:

• Definition of China’s AI Strategy: China’s approach combines self-reliance in chips and algorithms, economy-wide AI adoption, and global governance leadership by 2030.
• Policy Timeline: National plans since 2017, city pilots in Shanghai and Shenzhen, and new governance rules in 2023–24 shaped today’s regulatory framework.
• Role of Tech Giants: Baidu, Alibaba, Tencent, and Huawei drive large models, infrastructure, and compliance, while aligning closely with government priorities.
• Military and Security Uses: The PLA integrates AI into drones, logistics, and cyber operations, though heavy reliance on imported hardware remains a challenge.
• Global Impact: Beijing exports AI governance models through UN initiatives, BRICS, and the Belt and Road, creating both influence and geopolitical friction.

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Timeline of China’s AI Strategy

China’s AI strategy has evolved through successive national plans and regulations:

2017 – New Generation AI Development Plan (AIDP)

The State Council issued this landmark plan, setting staged goals for 2020, 2025, and 2030. Targets included a ¥1 trillion ($140 billion) domestic AI industry and ¥10 trillion ($1.4T) in related industries by 2030. The plan mobilized state resources to grow talent, R&D, and markets.

2018–2020 – Provincial and municipal AI plans

Local governments began translating the national AI plan into city-level strategies. Shanghai, Shenzhen, Hangzhou, and Beijing launched early pilot zones, AI parks, and data centers, laying the groundwork for regional competition and experimentation.

2021–2025 – 14th Five-Year Plan (2021-25)

The 14th Five-Year Plan elevated AI as a strategic priority, requiring the digital economy’s core industries to reach 10% of GDP by 2025. Policies directed heavy investment into semiconductors, workforce training, and national computing networks. 

By the end of 2024, China had built the world’s largest 5G and fiber-optic broadband network, supported by 4.25M 5G base stations, 200M gigabit users, and 280 EFLOPs of computing power.

2022–2023 – Local Governance Experiments

Shanghai enacted the Shanghai AI Development Regulations (2022), China’s first local-level AI law. It mandated ethics committees for AI projects, dataset exchanges to regulate data flows, and industrial zones like the Lingang AI Zone to attract startups. 

Shenzhen piloted blockchain-based licensing for algorithms in fintech, pioneering China’s first algorithm governance sandbox. These city-level experiments acted as regulatory laboratories for national AI lawmaking.

2023–2024 – New governance rules and model frameworks

China shifted from plans to enforcement. The Cyberspace Administration of China introduced rules for deep synthesis and generative AI, requiring content labeling, user consent, and security reviews. 

In 2024, standards bodies such as TC260 issued technical guides, while the State Council launched new coordinating agencies—the Central Science & Technology Commission and the National Data Administration.

2024–2025 – International Governance Push

China began exporting its governance model abroad. In 2023, it launched the Global AI Governance Initiative at the UN. At the 2024 World AI Conference, Beijing co-authored the Shanghai Declaration on Global AI Governance, later echoed in UN resolutions on AI and human rights. 

By mid-2025, China led joint statements at the UN Human Rights Council on AI for accessibility, disability rights, and children’s protection.

Strategic Goals and National Priorities

Agriculture AI techno

China’s AI strategy revolves around four clear priorities: leadership by 2030, self-reliance in core technologies, economy-wide integration, and talent development. Each supports broader goals of security, stability, and influence.

• Global AI leadership by 2030 – the central milestone guiding national funding, local pilots, and regulatory frameworks.
• Self-reliance in core technologies – building domestic chips, computing networks, and AI models to reduce dependence on foreign supply chains.
• Integration across the economy and defense – AI is embedded into national priorities:
  • Smart manufacturing – automation, robotics, predictive maintenance
  • Healthcare – diagnostic tools, drug discovery, eldercare technologies
  • Transportation – autonomous driving, traffic optimization
  • Education – personalized learning and intelligent tutoring
  • Defense – surveillance, logistics, and decision-support systems
• Infrastructure and talent – expanding national supercomputing power, AI degree programs, and workforce retraining to sustain rapid growth.
• Social and security priorities – embedding AI in public services, urban management, and national defense to advance state-led development goals.

Regulatory Architecture and Governing Bodies

Manufacturing plant of the automobile industry

China’s AI governance relies on a network of agencies and Party bodies, with the Cyberspace Administration of China (CAC) at the center. Oversight covers data, algorithms, ethics, and industrial policy, all framed within state-led priorities.

Lead Regulators

• Cyberspace Administration of China (CAC) – Oversees online content, algorithm rules, and emerging frameworks for deep synthesis and generative AI. Recent regulations require deepfake labeling, chatbot filtering, and pre-release security reviews.
• Ministry of Science and Technology (MOST) – Guides national research priorities, chairs AI committees, and leads ethics frameworks.
• Ministry of Industry and Information Technology (MIIT) – Manages telecom integration, AI labs, and industrial deployments through institutes such as CAICT.
• National Development and Reform Commission (NDRC): This commission Aligns AI projects with economic planning, infrastructure funding, and industrial transformation goals.
• New coordinating agencies (2023–24) – The Central Science & Technology Commission and the National Data Administration centralize authority, balancing Party leadership with technical oversight.

Local Governance as Testbeds

Local governments serve as policy testbeds for AI regulation. Pilots first introduced in Shanghai and Shenzhen during 2022–23 have since shaped national standards on ethics oversight, data management, and algorithm licensing. Beijing now treats these city-level innovations as templates for broader compliance frameworks.

Global Governance and Diplomacy

Beijing increasingly exports its governance model abroad. Key initiatives include:

• The Global AI Governance Initiative (2023) – A proposal at the UN emphasizing state sovereignty in data and algorithm oversight.
• The Shanghai Declaration on Global AI Governance (2024) – Adopted at the World AI Conference, calling for “inclusive, secure, and fair AI.”
• UN engagement (2024–25) – China co-led joint statements at the UN Human Rights Council on AI promoting disability rights, children’s protection, women’s rights, and accessibility. Over 70 countries supported Beijing’s call for inclusive governance.

Think Tanks and Standards Bodies

Institutions such as CAICT and Tsinghua’s AI Governance Institute provide technical advice and draft standards, which are funneled into the TC260 committee. The standards cover watermarking, transparency, and algorithm risk classification and gradually expand into full compliance audits for foundation models.

Ethical and Social Governance of AI

China frames AI ethics around the principle of “secure, controllable, and beneficial AI”, designed to align with socialist values and prevent social disruption. Unlike the EU’s rights-centric model, China emphasizes state oversight, collective stability, and compliance with national priorities.

Core Rules and Frameworks

• Data Protection – The Personal Information Protection Law (2021) requires explicit consent for AI use of personal and biometric data.
• Algorithmic Fairness – AI systems must not discriminate by gender, ethnicity, or religion, with particular protections for children, workers, and other vulnerable groups.
• Content Responsibility – Under CAC’s deep synthesis regulations (2023–24), AI-generated media must carry watermarks, deepfakes must be labeled, and chatbots must filter prohibited content.
• Corporate Accountability – Companies developing high-risk AI must establish internal ethics committees and compliance boards. Regulators retain the authority to audit or suspend non-compliant systems.

City-Level Governance Pilots

Shanghai and Shenzhen, already pioneers in early governance pilots, are now scaling their frameworks. Shanghai enforces ethics committees citywide, while Shenzhen’s fintech sandbox informs Beijing’s plans for national algorithm licensing.

Social Responsibility and Inclusion

China’s approach to AI ethics is not limited to technical safety. It ties into broader social governance goals:

• AI is being used to extend healthcare access in underserved regions through remote consultations.
• Smart city platforms like Hangzhou’s City Brain are tested for pollution reduction, traffic safety, and emergency response, aligning AI adoption with collective welfare.
• The government actively promotes AI literacy campaigns in schools and vocational training, linking social equity with long-term governance.

Military and Dual-Use Applications

Image from Brookings. PLA’s Strategic Support Force and AI Innovation

Artificial intelligence is central to China’s civil–military fusion strategy, which channels university research and private-sector innovation into defense. The People’s Liberation Army (PLA) refers to this as “intelligentized warfare,” leveraging AI to improve decision-making, battlefield awareness, logistics, and cyber operations.

Current Capabilities

Recent PLA demonstrations highlight progress in:

• Drone swarms — palm-sized reconnaissance drones and larger jet-powered swarms for surveillance or payload delivery.
• AI-driven logistics — predictive maintenance and automated supply chains to enhance operational efficiency.
• Autonomous guidance systems — AI integration into vehicles and missiles for real-time navigation and targeting.
• Cyber and cognitive operations — AI-enabled tools for information dominance and psychological operations.

Many of these advances originate from civilian labs and startups before being adapted for defense use, underscoring the depth of civil–military integration.

Strategic Risks

Despite rapid progress, China remains dependent on foreign suppliers for critical defense-related hardware:

• Nearly 90% of high-performance radars, ultrasonic sensors, and chips are imported from the U.S., EU, and Japan.
• Frameless torque motors — considered the “heart” of humanoid robots — are dominated by U.S., German, and Swiss firms. A single advanced humanoid robot can require 28 such motors, leaving China vulnerable to supply chain disruptions.
• Coreless motors used in robotic actuators remain largely monopolized by U.S. and Japanese companies.

These dependencies pose risks to China’s ability to scale next-generation defense AI systems and highlight the strategic importance of domestic substitution programs.

Regulatory Gaps and Global Risks

Unlike civilian AI, military AI lacks a formal regulatory framework in China. Ethical guidelines such as the 2021 AI ethics norms do not apply to the PLA, and Beijing has not joined international treaties on autonomous weapons. This opacity raises global concerns:

• Escalation risk in military AI competition with the U.S. and Russia.
• Potential fragmentation of global norms, as China pushes for sovereignty-based governance while Western actors emphasize arms-control agreements.

Outlook

Beijing’s position is clear: AI must strengthen sovereignty and military readiness. With civil–military fusion accelerating, the PLA is positioned to rapidly adapt breakthroughs from the civilian ecosystem. Yet the absence of binding oversight mechanisms adds uncertainty to how China’s AI-enabled warfare capabilities will evolve on the global stage.

Role of Chinese Tech Giants in the AI Ecosystem

China’s private tech sector — led by a handful of national champions — drives much of the country’s AI innovation while aligning closely with state priorities. These firms not only develop large-scale models and infrastructure but also act as policy executors, translating government directives into market-ready deployments.

Baidu: LLM Pioneer

Baidu has shifted from search to serious AI muscle. Its ERNIE models (especially ERNIE Bot) became central to its cloud strategy, pulling in ¥656 million ($90M) in late 2023. With plans to open-source ERNIE 4.5 in 2025, Baidu is positioning itself as a key player in both commercial and strategic AI.

It also collaborates closely with the government, co-authoring policy blueprints and running national AI labs like the Baidu–Tsinghua Joint Lab.

Alibaba: Enterprise AI for Scale

Alibaba’s AI strategy runs through DAMO Academy and Alibaba Cloud, anchored by its Tongyi Qianwen large model. By mid-2024, over 90,000 enterprises were using it for chat, analysis, and automation. 

DAMO also develops open-source models such as Qwen-VL for multimodal tasks, reinforcing Alibaba’s role in scaling AI across Chinese business ecosystems. The company works closely with universities and research institutes, aligning with national tech priorities.

Tencent: Quiet but Deep Integration

Tencent integrates AI across WeChat, gaming, and fintech through its Hunyuan multimodal models. While less public about its AI strategy, Tencent’s AI Lab and Research Institute work on cutting-edge generative systems and national research initiatives. 

Tencent also partners with government agencies on AI safety and compliance pilots, embedding itself into regulatory frameworks while monetizing consumer-facing applications.

Huawei: Infrastructure Backbone

Huawei underpins China’s AI ecosystem from the ground up. Its Ascend chips, MindSpore AI framework, and ModelArts platform are cornerstones of domestic compute independence. Huawei also powers the West–East AI Compute Project, which redistributes computing workloads across China to address regional imbalances. 

Internationally, Huawei exports its Safe City platforms, which are already deployed across Africa and the Middle East. These platforms provide surveillance and urban management solutions and extend Beijing’s AI governance model abroad.

Other Notable AI Firms

China’s AI field also includes specialized unicorns:

• SenseTime – facial recognition and vision AI
• iFLYTEK – speech recognition and LLMs
• Megvii and CloudWalk – surveillance and biometric AI

Most receive state-aligned funding and collaborate on research, making them key contributors to China’s applied AI ecosystem.

Companies as Policy Executors

Chinese tech giants are not just market players; they act as policy partners. When Beijing restricted foreign LLMs in 2023, domestic firms accelerated chatbot launches. When AI healthcare became a priority, Baidu and Tencent introduced diagnostic and eldercare tools. In exchange, these companies gain:

• Fast-track regulatory approvals
• Privileged access to training data
• Lucrative state contracts for surveillance, transport, and smart city systems

This symbiotic relationship creates a two-way pipeline: Corporate innovation advances government objectives, while government support ensures these firms dominate the domestic market and expand China’s influence abroad.

Local Government Pilots and City-Level Innovation

Homepage of the Shanghai Cooperation Organization

This is where you expand with all the city-specific examples, so readers see how pilots evolved:

• Beijing – National AI capital with 2,400+ AI companies, 33,000 PFlop/s of compute, and institutes like the Beijing Academy of AI. Hosts massive datasets and R&D hubs.
• Shanghai – First city to codify AI law (2022), requiring ethics committees and dataset exchanges; developed Lingang AI Zone and launched pilot services like autonomous buses.
• Shenzhen – HQ for Tencent & Huawei R&D; pioneered blockchain-based licensing for algorithms and deployed AI across fintech, factories, and airports.
• Hangzhou – Home to Alibaba’s City Brain, used to optimize traffic, pollution, and logistics (notably scaled during the 2024 Asian Games).
• Other hubs are Guangzhou (healthcare AI), Jiangsu and Sichuan (algorithm sandboxes), and Wuhan and Chongqing (industrial IoT and drones).

Local Labs as National Sandboxes

These local pilots are more than city branding—they’re field tests for national policy. Beijing sets standards, but cities test what works. Whether Shanghai codifies AI law, Shenzhen licenses fintech algorithms, or Sichuan trials edtech audits, this experimentation helps shape how China governs and deploys AI at scale.

Global Positioning and Tech Geopolitics

China frames AI as both a domestic growth driver and a tool of global influence. Competition with the U.S. remains central—Washington leads in chips and models, while Beijing emphasizes deployment scale and regulatory sovereignty. With the EU prioritizing rights-based rules, China positions itself as an alternative model built on state-led oversight.

Homepage of Hikvision

Regional Cooperation: BRICS, ASEAN, and Belt & Road

Beijing also leverages multilateral blocs to extend its AI footprint:

• Established the BRICS AI Development & Cooperation Center and the China–ASEAN AI Innovation Center, both serving as platforms for regional collaboration in R&D and talent training.
• Advanced Belt and Road Digital Cooperation, exporting infrastructure such as Huawei’s Safe City surveillance platforms and Alibaba DAMO’s SeaLLM model, the first large-scale AI system trained on Southeast Asian languages.
• Partnered with Egypt on the Digital Egypt Builders Program, helping train AI professionals and accelerating digital transformation in the Middle East.

Partnerships and Training

China funds AI research centers, scholarships, and fellowships abroad. In 2024, it co-launched Africa’s first Center of Excellence in AI and Digital Economy with the UN. Chinese firms also provide low-cost AI tools for translation, fraud detection, and agriculture, embedding themselves as long-term partners rather than short-term vendors.

Standards and Global Governance

In global standards bodies such as ISO, ITU, and WTO, China promotes its governance model—emphasizing algorithm oversight, data sovereignty, and state-led accountability. These technical standards complement its diplomatic initiatives (Global AI Governance Initiative and Shanghai Declaration), giving Beijing influence over both rules and infrastructure.

Outlook

China’s global AI push involves infrastructure, exports, and diplomacy. Its approach resonates in the Global South but fuels friction with Western powers. The long-term question is whether these efforts lead to a fragmented AI ecosystem or a broader acceptance of state-centered governance models.

Future Outlook (2025–2030)

humanoid robot with smartphone at technology

Looking ahead, China’s AI strategy is shifting from planning to execution. The state-backed “AI+” programs will expand deployments across manufacturing, agriculture, healthcare, and urban management while shaping new governance standards at home and abroad.

Execution Across Core Sectors

• Manufacturing – Automated factories, predictive supply chains, and industrial IoT systems are scaling under the AI+ Manufacturing initiative.
• Agriculture – Precision farming, drone spraying, and AI-driven yield prediction will support food security in rural regions.
• Healthcare – Diagnostic platforms are expanding beyond major hospitals, with AI raising cancer detection rates by 25% and enabling nationwide remote consultations.
• Smart cities—Following its success during the 2024 Asian Games, Platforms such as Hangzhou’s City Brain will extend from logistics to waste, pollution, and energy management.
• Elder care – Assistive robotics and monitoring systems are positioned to address China’s rapidly aging population.

Emerging Trends Shaping 2025–2030

Analysts predict several new trends will define China’s AI trajectory:

• Open-Source Generative AI – Sparked by DeepSeek in 2025, open GenAI is expected to account for half of China’s AI ecosystem by 2026, fueling collaboration and low-cost adoption.
• Frugal AI – Cost-efficient, compute-light AI solutions will lower barriers for SMEs and rural adoption, aligning with Beijing’s inclusion goals.
• “Build Your Own” AI Strategy – By 2028, demand for in-house AI development skills will grow 50%, as companies favor internal teams over off-the-shelf models.
• Agent-Based AI – By 2028, 33% of enterprise software will embed agent-based AI (up from <1% in 2024), enhancing automation in finance, logistics, and customer service.
• Collaborative AI Defense Systems – By 2028, 60% of firms will adopt cross-departmental AI security frameworks, reflecting rising concern over cyber and algorithmic risks.
• Ubiquitous AI in Society – By 2030, AI penetration across daily life in China is forecast to exceed 50%, integrating into consumer services, governance, and education.
• Data Ecosystems as Differentiators—As models become standardized, companies will compete on unique proprietary data, shifting the focus from algorithm superiority to data ecosystems.

Opportunities and Risks Ahead

If executed as planned, China’s AI sector could add ¥6.7 trillion ($930B) in labor value by 2030, supporting its $1.4 trillion AI market target. However, dependency risks remain: nearly 90% of advanced chips and sensors are imported, and brain drain continues, with 54% of Chinese-origin AI scientists working abroad. These vulnerabilities could delay progress if global tech bifurcation deepens.

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If you’re looking to deepen your strategic insight into China’s integrated AI ecosystem—from regulation and tech self-reliance to exports, standards, and innovation models—Ashley Dudarenok brings unparalleled relevance and credentials.

Proven Track Record in AI-Relevant Keynotes & Strategy

Recognized as a “Guru on digital marketing and fast‑evolving trends in China” by Thinkers50. Her most-requested talks include Tech in Action and Learn from China, explicitly addressing themes like AI-powered tech, smart cities, digital transformation, and China’s AI-led modernization.

Ashley is the founder of ChoZan and Alarice, strategy consultancies that have helped global clients navigate China’s AI-powered consumer platforms and B2B ecosystems—especially as Beijing tightened algorithm controls and reshaped the AI export narrative.

If you need to:

• Understand how China’s AI laws affect product launches, IP strategy, or AI stack partnerships
• Decode the political logic behind algorithmic governance
• Or a brief leadership on what China’s push for AI norms means for global risk planning

Ashley is your fastest path to clarity. No jargon, no hype—just sharp, situational intelligence.

Book Ashley Dudarenok for a strategic session or invite her to speak where AI, regulation, and power intersect. Because decoding China’s next AI move requires someone who’s already tracking it from the inside.

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