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China's "AI+" Plan: The Roadmap to an Intelligent Economy by 2035

Updated: 20 hours ago

I read China's national AI strategy so you don't have to. It is the most systematic government AI plan I've seen. Here is what leaders should take from it.

Introduction

On August 26, 2025, China's State Council published a landmark document. Its official title: "Opinions on Deeply Implementing the 'Artificial Intelligence+' Action" (State Council, August 26, 2025).

This is not another declaration of intent. It is a detailed roadmap for transforming an entire economy and society. The goal: make China the global leader of the "intelligent economy" by 2035.

I work with executives on AI adoption every day. This document deserves your attention. Not because it's Chinese. Because it's systematic.

The Philosophy: From Digitization to Intelligence

"AI+" is the successor to "Internet+", which shaped Chinese policy for a decade. "Internet+" was about connectivity and digitization. "AI+" goes deeper. It aims to embed AI into everything — from research labs to daily life.

The core idea is a new formation: an "intelligent economy and intelligent society." It rests on three principles:

  • Human-machine collaboration

  • Cross-industry integration

  • Joint value creation

Notice the shift. Technology no longer adapts to humans. Humans and AI form a symbiosis. AI becomes an extension of human capability.

The Three-Stage Roadmap: 2027, 2030, 2035

The plan is structured by time horizons. That makes progress measurable and course correction possible. This alone is a lesson for most corporate strategies I see.

Stage 1: By 2027 — Foundation and Acceleration

The first milestone targets critical mass. By 2027, China plans to:

  • Reach 70%+ penetration of AI terminals and AI agents across people and businesses

  • Deeply integrate AI with six key domains: science and technology, industry, consumption, social welfare, governance, and international cooperation

  • Achieve rapid growth in the core industries of the intelligent economy

  • Significantly strengthen AI's role in public administration

The task here is fixing bottlenecks and laying foundations. Two years to build the infrastructure for mass adoption.

Stage 2: By 2030 — Scale and Leadership

The mid-term stage assumes exponential growth:

  • Penetration of intelligent solutions rises above 90%

  • The intelligent economy becomes the main engine of national growth

  • Advanced AI becomes universally accessible, across all social groups

  • A full ecosystem for sharing AI results takes shape

By 2030, China wants a transformation mechanism: "from pressure to opportunity, from opportunity to strength." The aim is to compete with the US as an equal. And to win in selected niches of the global AI market.

Stage 3: By 2035 — A New Stage of Development

The long-term goal is maximal. China fully enters the era of the intelligent economy and society. AI becomes so woven into the social fabric that it provides "powerful support for basically achieving socialist modernization."

Read that carefully. AI is not treated as a technology. It is an instrument of national strategy — from labor productivity to geopolitical standing.

The Six Pillars of "AI+"

The document defines six priority domains. Each gets concrete tasks and mechanisms.

1. AI + Science and Technology. The goal: accelerate discovery. Key measures: develop foundation models (theory, training and inference efficiency, evaluation systems); apply AI to research — simulating complex processes, discovering new materials and drugs; build "AI accelerators for science" that automate routine research work. For the first time, AI4Science gets priority status in Chinese policy. That signals real understanding of AI's potential for fundamental science.

2. AI + Industrial Development. This covers all three sectors of the economy at once. In manufacturing: AI across the full cycle — design, pilot production, operations, maintenance; smart factories with autonomous lines; industrial IoT built on AI analytics. In agriculture: mass deployment of smart machinery — robots, drones, automated harvesters; precision farming with AI yield forecasting; digital transformation from seeding to logistics. In services: a shift from "digital enhancement" to "intelligent management"; personal AI assistants for education, healthcare, finance; new AI-as-a-Service business models. The key point: all three sectors transform simultaneously, reinforcing each other.

3. AI + Consumption Upgrading. New products and new experiences. Next-generation intelligent terminals: phones, cars, appliances with built-in AI and multimodal interaction. AI agents that understand context, plan, and act autonomously. New consumption formats: smart homes, autonomous transport, personalized entertainment. The document speaks of a "better, beautiful life" through AI. That means emotional connection with intelligent systems, not just convenience.

4. AI + Social Welfare. The most socially oriented section. In education: personalized learning adapted to each student; VR/AR for immersive study; AI assistants that free teachers from grading and prep. In healthcare: AI diagnostics supporting doctors in remote regions; medical care robots; telemedicine with AI consultants; AI-accelerated drug development. In employment: new jobs in AI development, data management, and ethics auditing; reskilling platforms; AI simulators for training in complex professions. In elderly care: health-monitoring devices, companion robots, AI-driven emergency response. The guiding principle: equal access to AI benefits for everyone, including the most vulnerable.

5. AI + Governance Capability. Smart cities with integrated transport, energy, and security management. Predictive analytics for anticipating social problems. Automated digital public services with intelligent advisors for citizens. Early-warning systems for emergencies and disaster resource management. China wants "a government that thinks" — decisions driven by data, not only by officials' experience.

6. AI + Global Cooperation. For the first time, the international dimension is a standalone pillar. China backs UN-based AI governance: an Independent International Scientific Panel on AI and a Global Dialogue on AI Governance. The "AI+ international cooperation" initiative helps developing countries build AI infrastructure and share data and models. The stated principle is inclusiveness: all countries should shape the rules, so the digital divide doesn't deepen. This is soft power — an alternative ecosystem attractive to the Global South.

The Eight Foundational Supports

Six domains need infrastructure. The document defines eight supports.

1. Foundation models and algorithms. Advance machine learning theory. Build efficient training and inference systems. Standardize model evaluation.

2. High-quality data. Industry datasets for AI training. Copyright and IP reform to encourage data sharing. New incentives for opening data. China is honest here: data is its weak link versus the US. The US has roughly 300,000 open datasets on government platforms. In China, over 70% of valuable data sits with the state, poorly structured for AI training.

3. Computing power. AI chips and clusters. A stronger national computing network. Cloud standardization. Supply that is inclusive, efficient, green, and secure. The "Eastern Data, Western Computing" strategy places energy-hungry data centers in western regions with surplus green energy.

4. Application ecosystem. AI-as-a-Service platforms, testing grounds for new solutions, new standards for AI applications.

5. Open-source ecosystem. This one stands out. Support for open-source communities. Open-source contributions counted in evaluating students and researchers. Ambition to build globally influential ecosystems. Open source elevated to state policy is a strong signal.

6. Talent and education. Mass training of AI specialists. AI literacy in school and university curricula. Recruitment of international talent.

7. Legal and ethical frameworks. Legislation for safe AI development. Ethical standards. Accountability mechanisms for AI systems. China already has the "Ethical Norms for New Generation AI" (2021) and the "Interim Measures for Generative AI Services" (2023). It is ahead of most on regulation.

8. Policy and financial support. Tax incentives for AI companies. State funding for promising R&D. A friendly environment for startups.

China's Unique Advantages

The plan builds on three competitive advantages.

1. Data richness and scale. China generated over 41 zettabytes of data in 2024 — up 25% year on year. The largest volume of any country. Drivers: 1.4 billion people, deeply digitized daily life, giant platforms (Alibaba, Tencent, ByteDance). The catch is structure. Structured data grows fast — 36% a year — but is still only 18.7% of the total.

2. A complete industrial system. China is the only country with all 41 industrial categories in the UN classification. That means unmatched diversity of AI application scenarios — from steel mills to EV plants. Chinese developers test on real industrial data competitors simply cannot access.

3. Breadth and depth of adoption. 83% of Chinese believe AI will do more good than harm. In the US: 39%. That trust creates an ideal environment for mass testing and iteration. 50% of Chinese companies actively use AI, versus 33% in the US. The public sector is active too: over 540 billion AI service calls have run through the national data-sharing platform.

China vs the US vs Europe

China

Strengths:

  • Leads in AI research publications (12,450 in 2023)

  • Dominates patents — four times more than the US

  • Fast growth of top-tier researchers; 47% of the world's elite AI specialists trained in China

  • A huge market with diverse application scenarios

  • Ahead in autonomous transport: 900 million Baidu robotaxi rides versus 500 million for Waymo

Weaknesses:

  • Lags in fundamental theory — Transformer, Diffusion, RLHF all came from the US

  • Shortage of high-quality structured Chinese-language datasets

  • Dependence on Western chips; US sanctions restrict access to advanced GPUs

  • Lower density of top scientists per capita

The US

Strengths:

  • Leads in theoretical breakthroughs and base architectures

  • Dominates high-performance chips (NVIDIA, AMD)

  • The strongest universities and corporate labs

  • A culture of open innovation and venture capital

  • Massive resources of tech giants (OpenAI, Google, Meta)

Weaknesses:

  • Lower public trust and readiness for AI

  • Market fragmentation and regulatory barriers between states

  • Weaker state coordination compared with China

Europe

Strengths:

  • Strong research institutes (32 leading centers)

  • Focus on ethics and human rights in AI

  • First mover in regulation (the AI Act)

Weaknesses:

  • No platforms at Chinese or American scale

  • Few AI unicorns

  • Market fragmentation and language barriers

My takeaway: China and the US dominate the first tier, with different edges. The US wins on theory and hardware. China wins on scale of application and state coordination.

Challenges and Risks

The plan is ambitious. The obstacles are real.

1. Data quality. Volumes are huge, but much data sits with the state and is poorly structured. Chinese open-source datasets amount to only 11% of English-language ones. That gap is critical.

2. Technological dependence. US chip sanctions bite. Huawei Ascend and Moore Threads build alternatives. They have not yet matched NVIDIA's A100/H100.

3. Innovation versus control. Strict regulation of content and algorithms can slow innovation. China must balance safety with room for experiment.

4. International isolation. Escalating tech competition with the West may cut access to advanced research and talent.

Conclusion: A New Development Paradigm

"AI+" is more than a strategy document. It is a manifesto for a different model of modernization. The classic Western approach bets on market competition and breakthrough companies. The Chinese model bets on state coordination, mass application, and social focus.

Four features define the approach:

  • Synchronized transformation. All sectors change at once, not through isolated breakthroughs.

  • Social inclusiveness. AI must reach everyone, including the elderly and vulnerable groups.

  • Global responsibility. China positions itself as the leader of inclusive AI governance through the UN.

  • Pragmatism. Mass application beats fundamental breakthroughs. DeepSeek showed results are possible at a fraction of the cost.

By 2035, China aims not just to catch up. It wants to surpass the West in specific areas, with its own ecosystem of technologies, standards, and applications. Success depends on overcoming today's bottlenecks: chips, fundamental research, international cooperation. One thing is clear to me. The battle for the AI future will shape geopolitics for decades. And China is playing the long game.

P.S. How "AI+" Relates to Strategy 1397

I wrote earlier about China's Strategy 1397. The two documents do not contradict each other. They form a hierarchy.

"AI+" is the national strategy to 2035. It answers "what" and "why": six application domains, eight systemic supports, transformation of economy, society, and governance.

"1397" is the subordinate operational framework. It answers "how" and "with what": intelligent computing, data infrastructure, foundation models, and the organizational mechanisms that turn goals into programs.

They share the same base: compute, quality data, foundation models, talent, and legal-ethical regulation. Both link AI4Science with industrial intelligence and mass deployment. Both have an international track: "AI+" through global AI governance, "1397" through self-reliance plus open cooperation in big science.

In short: "AI+" sets the milestones — 2027, 2030, 2035 — and the requirements for the six domains. "1397" delivers them through a national distributed computing system, open-data hubs, and short transfer chains into industry. "AI+" defines strategic outcomes. "1397" is the engine that achieves them.

Sources

This material was prepared with the help of artificial intelligence technologies.

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