Pennings, A.J. (2026, Jun 03) Beyond the China Price: Can Democrats Shape a New Industrial Strategy for the AI World? apennings.com https://apennings.com/global-e-commerce/beyond-the-china-price-can-democrats-shape-industrial-policy-for-a-new-globalization-strategy/

Introduction

China is changing and slowly going away. The Democrats need to do something about it. Democrats need to stop relying on billionaires for industrial policy. They need to define an agenda for labor in an AI world, materials in a high-tech world, and democracy in a social media/behavioral modification world.

For nearly four decades, the global economy benefited from what became known as the “China price,” the ability to manufacture vast quantities of consumer goods at remarkably low cost. China’s combination of abundant labor, export-oriented infrastructure, industrial clustering, and relatively inexpensive energy enabled multinational corporations to build supply chains that delivered affordable products to consumers around the world. The result was an era of low inflation, rising consumer purchasing power, and unprecedented access to manufactured goods.

Today, however, many of the conditions that made this model possible are changing. Rising tariffs, geopolitical tensions, demographic decline, increasing labor costs, and higher energy prices have led many observers to argue that the age of cheap Chinese goods is coming to an end. If that assessment proves correct, the United States faces an important challenge. It must ask how can it continue to provide affordable consumer goods without relying on the same global labor arbitrage that defined the first era of globalization?

The answer will not be found simply by moving factories back to American soil. Rather, it will emerge through a profound transformation in how goods are produced, distributed, and consumed. New trade relationships, artificial intelligence, additive manufacturing, advanced materials, and automated production systems are collectively creating the foundations of a new economic model—one in which computation, energy, and machine intelligence increasingly replace low-cost labor as the primary drivers of manufacturing competitiveness.[1]

The first response to the erosion of China’s manufacturing dominance has been the search for alternative production locations. Countries such as Vietnam, India, Indonesia, and Mexico have become increasingly attractive destinations for manufacturers seeking lower labor costs and reduced geopolitical risk. Yet replacing China is not as simple as relocating production. China did not become the world’s factory merely because wages were low. It developed an extraordinarily sophisticated industrial economy composed of suppliers, logistics networks, ports, engineering talent, and manufacturing expertise that emerged over several decades.

No single country currently offers the same combination of scale and industrial depth. As a result, many companies are discovering that diversification rather than replacement is the more realistic strategy. Production is spreading across multiple countries, creating more resilient supply chains but often at higher cost.

This raises an important question. If labor costs are increasing everywhere, how can manufacturers continue to produce inexpensive goods? The answer increasingly lies in recognizing the diminishing importance of labor itself. Not creativity and organization, but the reliance on the human body as a major source of energy and site of productivity.[2] The original globalization model depended on moving production to places where workers were inexpensive. The emerging model depends on transforming production through automation so that labor becomes a smaller component of total costs. In this sense, artificial intelligence may become the successor to labor arbitrage.

AI-enabled manufacturing systems can coordinate production schedules, monitor quality, predict equipment failures, optimize inventories, and continuously improve factory performance. Rather than employing large numbers of workers to supervise industrial processes, manufacturers can increasingly rely on software systems that analyze enormous volumes of operational data in real time. This transformation shifts competition away from wages and toward computational efficiency.

The implications are profound. For much of modern economic history, nations competed by offering cheaper labor. In the future, nations may compete by offering cheaper computation and more abundant energy. Manufacturing competitiveness may become less dependent on labor markets and more dependent on access to advanced digital infrastructure, data centers, semiconductor technologies, and electricity.

This transformation is already visible in the rise of highly automated factories. The long-discussed concept of the “lights-out factorym,” a production facility capable of operating with minimal human intervention, is gradually becoming a reality. While complete automation remains rare, many advanced manufacturing facilities already rely heavily on robotics, machine vision systems, and AI-driven process management. In such environments, labor costs become a much smaller factor in determining the final cost of production.

At the same time, additive manufacturing, commonly known as 3-D printing, is challenging some of the basic assumptions that have governed global supply chains for decades. Traditional manufacturing relies on economies of scale. Companies invest heavily in tooling, produce large batches of products, ship them across oceans, and store them in warehouses before they reach consumers. This model rewards centralized production and extensive logistics networks.

Additive manufacturing offers a different approach. Instead of producing goods in massive quantities at distant locations, digital designs can be transmitted electronically and manufactured closer to the point of consumption. Products become information before they become physical objects. In this sense, manufacturing begins to resemble software distribution.

While 3-D printing is unlikely to replace conventional mass production entirely, it has the potential to transform significant sectors of the economy. Spare parts, medical devices, aerospace components, customized consumer products, and industrial tools can increasingly be produced on demand rather than stored in inventory. As a result, transportation costs, warehousing requirements, and supply chain complexity can all be reduced.

The broader significance of additive manufacturing lies in its potential to shorten supply chains. For decades, globalization sought to minimize production costs by extending supply chains across continents. Emerging technologies may achieve similar cost reductions by compressing supply chains and producing goods closer to where they are needed.

Nanotechnology introduces another dimension to this transformation by changing the material foundations of manufacturing itself. Throughout industrial history, productivity improvements have often resulted from better machines. In the future, productivity improvements may increasingly result from better materials.

Advanced nanomaterials can create products that are stronger, lighter, more durable, and more energy efficient than conventional alternatives. New battery chemistries may lower energy costs. Lightweight composites may reduce transportation expenses. Self-healing materials may extend product lifespans. Programmable materials may eventually enable entirely new manufacturing processes.

These developments matter because they reduce costs independently of labor. If products require fewer raw materials, consume less energy, last longer, and require fewer replacement cycles, affordability can be maintained even when wages rise.

Energy itself is becoming a central factor in manufacturing competitiveness. Industrial production in the twentieth century was often constrained by labor availability. Twenty-first-century production may be constrained by access to reliable and inexpensive electricity. Artificial intelligence systems, robotics, semiconductor fabrication plants, and advanced manufacturing facilities all require substantial amounts of energy.

This reality creates new opportunities for the United States. Unlike many advanced economies, the United States possesses significant energy resources, including natural gas, nuclear capacity, solar generation, and wind power. As production becomes more automated, access to low-cost energy may become more important than access to low-cost labor.

This shift helps explain why investment in semiconductor fabrication, data centers, and advanced manufacturing increasingly focuses on regions with abundant electricity. In a highly automated economy, energy effectively becomes a substitute for labor. The nation that can generate and distribute electricity efficiently may gain advantages similar to those once enjoyed by countries with large supplies of inexpensive workers.

At the same time, the United States is likely to deepen economic integration within North America. Mexico is particularly well positioned to become a critical manufacturing partner, combining lower labor costs with geographic proximity and established industrial capabilities. Rather than relying on trans-Pacific supply chains, firms can increasingly organize production across a continental manufacturing system in which design, engineering, software development, and advanced technologies remain concentrated in the United States while selected manufacturing activities occur throughout North America.

Such arrangements do not eliminate globalization; they reorganize it. Production networks become shorter, more resilient, and less dependent on geopolitical rivals. The objective is not autarky but strategic interdependence among trusted partners.

What emerges from these developments is not simply a new manufacturing strategy but a new economic reality. The original era of globalization was built upon the equation of cheap labor plus global shipping. The emerging model is based on a different formula. It combines cheap energy, artificial intelligence, advanced automation, digital design, and smart materials.

In this new environment, goods remain affordable not because millions of workers are paid low wages but because production systems become extraordinarily efficient. Algorithms optimize factory operations. Robots perform repetitive tasks. Additive manufacturing reduces inventory and transportation costs. Nanotechnology improves material performance. Energy replaces labor as a central production input.

From the perspective of digital disruption, this transition represents a movement from labor-intensive globalization toward what might be called computational production. Just as the information economy transformed communication by converting media into digital information, advanced manufacturing is transforming production by converting industrial processes into computational systems.

The countries that successfully integrate artificial intelligence, automation, additive manufacturing, advanced materials, and abundant energy into coherent production ecosystems will shape the next era of economic development. Their competitive advantage will not rest primarily on low wages but on their ability to transform information into physical goods with unprecedented efficiency.

The age of cheap Chinese labor may be ending, but the age of cheap goods is not necessarily ending with it. Rather, the source of affordability is shifting from human labor to machine intelligence. China could easily stay in the game. The next chapter of globalization may therefore be defined not by where factories are located, but by how effectively computation itself becomes a factor of production.

By building an economy where clean energy replaces cheap labor, and sovereign material networks replace fragile global logistics, we can lower consumer costs while strengthening worker power. This strategy positions the Democratic Party as the true champions of working families, delivering an economy built by American ingenuity and owned by the American people.

Notes

[1] I having been teaching Technological Systems Management and ICT for Sustainable Development for the last ten years for SUNY in Korea.
[2] Zuboff’s early writing on work and IT was very instructive. Zuboff, S. (1990) In the Age of the Smart Machine: The Future of Work
and Power. (New York: Basic Books).

© ALL RIGHTS RESERVED

Not to be considered financial advice. AI is often used, and results are thoroughly interrogated. Links are used for some citations.

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Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information management at New York University. His first position was at Victoria University in New Zealand. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

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Category: artificial intelligence, automatrix, blockchain, creative cities, creative industries, crisis communications, cryptocurrencies, data analytics and meaning, democratic political economies, digital coordination, digital destruction, digital geography, enabling frameworks, enterprise systems, food policy and security, global communications, global e-commerce, technology management, telecom policy and net neutrality, the smith effect
Tags: additive manufacturing > advanced materials > and automated production systems > indusrial policy

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