"New Factories Would Also Need New Workers"
By Dr. Jeonghwan (Jerry) Choi, A response to McKinsey's Ramping Up Manufacturing in America?
Introduction
A recent McKinsey report on reshoring U.S. manufacturing put a number on what many already suspected: reducing America’s dependence on $3 trillion in annual manufactured imports would require doubling domestic production of critical goods and roughly $2 trillion in new capital investment (Anderson, 2026). The analysis is sobering in scale. Building the required industrial footprint demands specialized skills, physical infrastructure, and reliable energy — and the report is direct that workforce availability poses as significant a constraint as financing.
That framing deserves more attention than it has received.
Problem
Among the report’s many concerns, its treatment of new factories requiring new workers cuts to the core of the challenge. The looming labor shortfall is not reducible to a simple numbers problem. A full reindustrialization effort could produce close to one million new manufacturing jobs — but the current pool of unemployed manufacturing workers stands at roughly half that figure. Semiconductors illustrate the severity most sharply: some 67,000 projected openings may go unfilled simply because today’s degree pipelines cannot produce graduates fast enough. The gap is real and the math is uncomfortable. But fixating on the deficit in quantity risks obscuring what is actually at stake — because the character of the gap tells us far more than its size ever could.
The factories that reindustrialization builds will bear little resemblance to the ones that defined the last century. AI-driven systems have already absorbed much of what once required a human hand — scheduling, procurement, maintenance forecasting, inventory flow. What the automated floor cannot do is “think”.
The work left for human beings is the harder kind: reading the signals an algorithm misses, holding quality standards when complexity exceeds a system’s parameters, and making sound calls at the point where engineering knowledge, live data, and irreducible uncertainty all converge at once.
Against that backdrop, the productivity gap between the United States and its competitors becomes more than a statistic — it becomes a warning. The McKinsey report is candid that America has significant room to close the distance.
South Korea and Singapore, the two most robot-intensive economies in the world, run manufacturing floors with more than three times and twice as many robots per worker as U.S. facilities, respectively. China’s output per manufacturing worker is estimated at two to three times the American rate. In electronics, the contrast with Singapore is almost jarring: capital productivity there runs 4.1 times higher than in the United States, and worker output roughly 4.6 times greater.
Taken together, these comparisons do not merely describe a technology deficit. They reveal the true nature of the workforce challenge ahead. The question is not whether America can hire enough people to fill new factory floors. It is whether those workers — and the organizations that employ them — will be capable of performing at the level that advanced automation demands. Filling seats was always the easier part.
This is not a simply training gap. It is a meta-skill gap.
In a recent piece published in this forum, I proposed the concept of hyper meta skills — higher-order developmental capabilities essential for human-AI augmented workplaces. Five anchor the framework: learning agility, systems thinking, human-AI collaboration, ethical judgment, and sensemaking under uncertainty (Choi, 2026).
These are not static competencies acquired once. They are dynamic capabilities built through experiential learning, sustained HRD intervention, and ongoing critical engagement with intelligent systems. Henry Ford replaced craftsmen with line workers. The next industrial transition does not simply replace line workers with machines. It demands human-AI augmented professionals capable of orchestrating, evaluating, and governing intelligent systems responsibly.
Capital can build a factory. It cannot supply the human capability required to run one well.
Conclusion
Reindustrialization without commensurate investment in human capability development is infrastructure without the people capable of running it. The $2 trillion conversation is already underway in policy circles, in financial markets, and in corporate boardrooms. The workforce development conversation is not keeping pace — and that asymmetry is where the strategy breaks down.
Workforce development is not a downstream concern to be addressed once the factories are built. It is a co-equal strategic imperative, one that demands the same urgency, investment, and institutional seriousness we bring to capital formation. If the United States is serious about reindustrialization, it must be equally serious about the human systems that make industrial capacity function. The harder problem was never the money.
Reference:
Anderson, K. (2026, May 21). Ramping up manufacturing in America? McKinsey & Company.https://www.mckinsey.com/mgi/our-research/ramping-up-manufacturing-in-america?stcr=E8BF192B1F0B4F3AA5C6E575BA2E1DEC&cid=mgp_opr-eml-alt-mgi-mgp-glb--&hlkid=baa8774bb9464d3da80204bae4b360b2&hdpid=304300a5-c52e-4f41-a85b-8c2b89b40bb5
Choi, J. (2026). Hyper meta skills for human-AI augmented workplaces. K-GSP Forum.
Prof. Dr. Jeonghwan (Jerry) Choi — Editor-in-Coordination of K-Global Scholars and Professional Forum & Associate Professor, University of Maine at Presque Isle
Jeonghwan (Jerry) Choi, PhD is an Associate Professor of Business at the University of Maine at Presque Isle and Editor-in-Coordination of K-GSP Forum. With over 25 years of industry and consulting experience, he specializes in leadership development, human resource management, organizational behavior, and social entrepreneurship. His research focuses on workforce resilience, organizational health, and self-directed leadership — bridging rigorous scholarship with practical insight to cultivate leaders who create meaningful, sustainable, and humane organizations.
© K-Global Schoalrs and Professionals Forum. All rights reserved. Content published in the K-GSP Forum may not be reproduced, distributed, or transmitted in any form without prior written permission from the K-GSP Forum, except for brief quotations with full attribution.