China’s AI + Manufacturing Roadmap: Securing Core Technologies by 2027

• 3-5 general large-scale models deployed in manufacturing
• 100 high-quality industrial datasets established
• 500 typical application scenarios implemented
• 2-3 ecology-dominant enterprises with global influence formed
• 1,000 diagnostic benchmark enterprises identified

Eight Chinese government departments just dropped a major blueprint for AI dominance in manufacturing.

The Ministry of Industry and Information Technology (Gongye he Xinxihaobu 工业和信息化部) alongside seven other departments released the “Implementation Opinions on the ‘Artificial Intelligence (AI) + Manufacturing’ Special Action.”

Here’s what matters: by 2027, China is targeting a complete overhaul of how AI integrates into the manufacturing sector—and they’re backing it with real capital and infrastructure investment.

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The 2027 Vision: AI Supply Chain Independence

Let’s break down what China is actually trying to achieve here.

By 2027, the goal is crystal clear:

• Secure and reliable supply of key core AI technologies — essentially manufacturing independence from foreign AI hardware and software
• Industrial scale and capability ranking — positioned among global leaders in AI manufacturing integration
• Talent and ecosystem development — building the infrastructure to sustain this momentum long-term

The ambition isn’t subtle.

This is about vertical integration across the entire AI value chain.

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The Concrete Targets Breaking Down China’s AI Manufacturing Strategy

Numbers make strategy real.

Here are the specific benchmarks the government is targeting:

• 3–5 general large-scale models — deployed across manufacturing with specialized, industry-specific variants
• 100 high-quality industrial datasets — foundational data infrastructure for training and deployment
• 500 typical application scenarios — real-world use cases proving ROI across different manufacturing verticals
• 2–3 ecology-dominant enterprises with global influence — think Alibaba (Aliyababa 阿里巴巴) and Tencent (Tengxun 腾讯) scale players in AI manufacturing
• Group of “Specialized, Refined, Differential, and Innovative” (Zhuanjingtexin 专精特新) SMEs — the mid-market players building niche AI solutions
• 1,000 diagnostic benchmark enterprises — companies adopting AI diagnostics and predictive maintenance
• Globally leading open-source ecosystem — positioning China as the hub for AI development tools and frameworks

This isn’t theoretical.

These targets create economic incentives and market pull.

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AI Computing Power: The Hardware Foundation

You can’t run advanced AI without the chips and infrastructure to back it up.

The directive prioritizes reinforcing AI computing power supply through coordinated hardware and software development.

Key focus areas:

• High-end training chips — the processors needed to train large language models and AI systems
• Edge-side inference chips — putting AI compute where manufacturing happens, not just in the cloud
• AI servers — purpose-built infrastructure for running industrial AI workloads
• High-speed interconnects — faster data transfer between systems and devices
• Intelligent computing cloud operating systems — the software layer orchestrating everything

Beyond chips, the plan includes infrastructure buildout:

• High-level intelligent computing facilities (think data centers optimized for AI)
• Computing power interconnect platforms — connecting regional AI compute resources
• National integrated computing power network monitoring and dispatch platform — centralized coordination
• Pilot programs for intelligent computing cloud services
• Deployment of AI all-in-one machines and edge computing (Bianyuan Jisuan 边缘计算) servers
• Industrial cloud computing power infrastructure

Translation: China is building the nervous system that lets AI talk to manufacturing operations in real time.

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Algorithm Development: Building Manufacturing-Specific AI Models

Generic AI models don’t cut it for manufacturing.

Real-time decision-making, reliability, and security requirements are different in a factory than in a chatbot.

The plan calls for high-performance algorithm innovation tailored to manufacturing constraints:

• High-performance industry models — algorithms designed specifically for manufacturing workflows
• Advanced model training and reasoning methods — novel approaches to improve accuracy and speed
• “Cloud-Edge-End” model system — running AI at different layers (cloud for heavy compute, edge for real-time decisions, end-device for local processing)
• Small models for specific industrial sub-scenarios — lightweight AI for specific factory tasks
• Collaborative innovation between large and small models — mixing general-purpose and specialized AI

This means enterprises won’t be forced into one-size-fits-all solutions.

They get flexibility.

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Industrial Robotics and Automation: Where AI Gets Physical

AI integration into physical manufacturing equipment is the real game-changer.

The plan accelerates AI integration into:

• Industrial mother machines (Gongye Mu Ji 工业母机) — the foundational equipment used to make other machines
• Industrial robots (Gongye Jiqiren 工业机器人) — faster decision-making and autonomy

Specifically, the focus is on developing next-generation AI-driven Numerical Control (NC) systems to improve:

• Autonomous decision-making
• Advanced analysis capabilities
• Faster execution

Beyond factory floors, AI is being integrated into:

• Surgical robots — precision healthcare manufacturing
• Intelligent diagnostic systems — medical sector AI
• Large aircraft (Da Feiji 大飞机) and ships — research, manufacturing, and operations
• Drones (Wurenji 无人机) — autonomous delivery and inspection
• Intelligent low-altitude equipment — autonomous systems operating below traditional flight altitudes
• Intelligent Connected Vehicles (ICVs) — testing and safety assessment of autonomous driving tech

This spans aerospace, maritime, logistics, and transportation.

The breadth is intentional.

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Consumer Tech and Humanoid Robots: The Next Frontier

Manufacturing isn’t just about factories anymore.

The plan includes edge-side AI model breakthroughs for consumer devices:

• AI-enhanced smartphones — more processing on-device, less reliance on cloud
• AI PCs and tablets — personal computing gets smarter locally
• Smart home (Zhinenghuajiaju 智能家居) devices — coordinated AI ecosystem in homes

For specialized scenarios, accelerated commercialization of:

• AR/VR wearables — industrial inspection and remote medicine applications
• Brain-computer interfaces — early-stage tech for specialized use cases

And then there’s the headline-grabbing piece: “Embodied Intelligence.”

The directive calls for humanoid robot (Renxing Jiqiren 人形机器人) pilot bases and training grounds to:

• Create benchmark production lines
• Test humanoid robots in typical manufacturing environments
• Build the supply chain and ecosystem

This is China signaling that humanoid robots aren’t just R&D projects—they’re manufacturing integration targets.

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Going Global: The “China Solution” Export Strategy

This isn’t just about domestic manufacturing dominance.

The plan includes global expansion mechanisms:

• Customized AI products for different countries and regions — localized solutions, not one-size-fits-all exports
• Professional institutions providing overseas services — the infrastructure to support international deployment
• Technical verification and compliance certifications — helping enterprises navigate regulatory requirements globally
• “China Solution” going global — branding these systems as superior alternatives to existing solutions

This positions Chinese AI manufacturing tech as an exportable advantage.

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Funding and Market Mechanisms: How It Gets Paid For

Strategy without capital is just PowerPoint.

The government is using multiple levers to finance this:

• National Artificial Intelligence Industry Investment Fund — direct government capital
• Attracting social capital — private investment alongside public funding
• Local government measures — regional implementation with local flexibility
• Preventing “internal friction” (involution) — discouraging wasteful regional competition
• Large-scale demonstration actions — government purchasing and deployment to prove viability
• “First-set” equipment policies — incentives for first movers and early adopters

This creates a pull-through market.

Companies know government will buy and deploy new AI manufacturing tech if it works.

That’s a powerful signal.

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What This Means for Investors and Founders

Here’s the actual implication:

This is a top-down AI manufacturing transformation backed by government capital and coordinated across eight departments.

For investors, it means:

• Bet on companies targeting those 500 application scenarios — that’s where market demand gets created
• Watch for “Specialized, Refined, Differential, and Innovative” (Zhuanjingtexin 专精特新) SMEs — these are the government-backed mid-market winners
• Hardware plays (chips, servers, edge devices) will get funded through this initiative
• Industrial robotics and autonomous systems companies should expect tailwinds

For founders, the signal is:

• Build industry-specific AI solutions — generic tools won’t compete
• Target manufacturing verticals where government shows policy interest
• Consider manufacturing automation and diagnostics as core product areas
• Humanoid robotics and embodied AI are no longer speculative — they’re policy priorities

The 2027 timeline is aggressive but achievable given Chinese government capacity for coordination and capital deployment.

This is AI + Manufacturing as a strategic priority, not an afterthought.

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References

• Eight departments: By 2027, China’s key core AI technologies will achieve secure and reliable supply – Jiemian News
• Official Website – Ministry of Industry and Information Technology of the People’s Republic of China
• Implementation Opinions on AI + Manufacturing Special Action – East Money (Dongfang Caifu 东方财富)
• China Accelerates AI + Manufacturing Integration Strategy – Caixin Global