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‘AI Plus’ Is China’s Master Plan to Build an AI-Native Society by 2035 | Opinion

2025-11-24 06:00
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The race to the future will be won by whoever builds the smartest systems and who deploys them the fastest.

Mark MinevichBy Mark Minevich

AI Strategist

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As Washington obsesses over the next GPT breakthrough, and Silicon Valley continues its push toward artificial general intelligence, Beijing is on a mission to weave artificial intelligence (AI) into every layer of daily life. China’s new “AI Plus” plan, unveiled in August, marks its most ambitious societal redesign since the “Internet Plus” era a decade ago.

AI Plus is a national blueprint for building an AI-native civilization by 2035. While the United States measures progress in models and market caps, China measures it in total societal integration. China wants classrooms guided by AI tutors, clinics run on predictive diagnostics, completely autonomous factories and cities optimized by AI. That is complete connectivity of every aspect of daily life. 

Inside China’s 2035 AI Vision

Beijing declared artificial intelligence the “new productive force” of socialist modernization, embedding it into the national agenda for economic renewal and demographic adaptation. The roadmap is thoroughly structured and all encompassing.

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By 2027, China aims for AI integration across 70 percent of six major sectors, from industry and health care to public administration. By 2030, it targets over 90 percent adoption across the economy to create what policymakers call an “intelligent economy.” And by 2035, the country intends to transition into a fully “intelligent civilization” which represents a profound shift from “AI as strategy” to “AI as civilization design.” Data and machine intelligence are no longer tools but the organizing principles of productivity, governance and even social cohesion.

Six Pillars of AI Plus

AI Plus is built upon six interconnected pillars that rewire China’s national architecture. Industry will be powered by AI-native factories, or autonomous “dark manufacturing” lines that run continuously with minimal human intervention. Science will be driven by large-model research platforms such as DeepSeek, trained on open national datasets to accelerate discovery. Governments will lean on algorithmic policymaking and predictive monitoring to allocate resources and maintain stability.

In social services, AI copilots will assist doctors, robot teachers will personalize education and data-driven welfare systems will write the policies of public benefits. As a consumer, everything that enters someone’s feed and is marketed to them will be done so via AI driven data sets. Global cooperation under the AI+ International Cooperation Initiative will export this model abroad, linking developing nations into China’s AI ecosystem. China is working on increasing a global network and is interested in more countries being dependent on them. The U.S. seems to be interested in the opposite. 

Chinese Infrastructure Machine

America innovates, while China deploys. AI Plus lets Beijing do what it does best, rapid infrastructure mobilization. China is investing heavily in compute power, domestic chip production and the integration of AI into “utility rails” such as national identity, payment systems and data infrastructure. Their goal is full interoperability across every citizen’s digital footprint. State-backed funding ensures these systems reach from urban megacities all the way through to local governments, farms and factories.

Global Stakes

Globally we can now clearly see three different AI implementation playbooks at work. The U.S. leads in capability-max innovation, focused on frontier models. China pursues deployment-max mobilization, embedding AI into every economic and civic process. And India emphasizes infrastructure-max pragmatism, using AI to modernize public services at scale. The question for global leadership is whether AI becomes a shared global infrastructure or a new axis of geopolitical division.

Lessons for the U.S.

If Beijing’s execution outpaces the West’s innovation, the future may not be written in code, but in policy. For America to remain competitive, it must move from breakthrough-max to deployment-max thinking. That begins with treating energy, data and AI talent as strategic national assets. The U.S. must streamline energy permitting, establish compute zones for AI training and build a secure, consistent and reliably accurate data ecosystem.

The U.S. must also accelerate AI adoption in real-world sectors like manufacturing, health care and agriculture, and not just in labs and startups. Workforce training, STEM education and AI literacy need national-scale coordination, alongside a comprehensive infrastructure strategy that matches China’s pace.

The U.S. should continue leading in foundational research and open-source AI, but couple that leadership with better government-industry coordination for scaling solutions. The regulatory approach needs to be modernized and moved away from fragmented state rules toward clear, federal standards that enable safe, rapid deployment. Finally, Washington needs to reassert leadership in global AI governance, setting norms for ethics, safety and cooperation.

A Civilization Built on Code

AI Plus is not merely about automation, but about civilization design. By 2035, China envisions a world where algorithmic intelligence powers not just products, but people, policy and progress. The West still leads in creativity and innovation, but China leads in cohesion and execution.

The race to the future will not be won by whoever builds the smartest machines, but by whoever builds the smartest systems and who deploys them the fastest.

Mark Minevich is recognized globally as a digital cognitive AI strategist, global social innovation and technology executive, U.N. advisor, author, columnist, private investor and venture capitalist. Minevich is also a strategic advisor to Mayfield, a leading VC in Silicon Valley. Minevich is president of Going Global Ventures (GGV), a New York-based investment, technology and strategic advisory firm.

The views expressed in this article are the writer's own.

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