New Report: Reshoring Will Fail Unless AI Becomes the Operating System of the American Factory
Applied Artificial Intelligence LLC and Black Book Insights report that 88% of manufacturing executives say reshoring now depends materially on AI-enabled automation, analytics, or digital operations
CHICAGO, IL / ACCESS Newswire / August 19, 2026 / Applied Artificial Intelligence LLC and Black Book Insights LLC today released a joint report concluding that America’s reshoring movement has crossed a decisive threshold: bringing production back to the United States is no longer enough. To compete, domestic manufacturing must be rebuilt around AI-enabled operating systems that connect capital planning, workforce productivity, plant-floor execution, supplier resilience, and real-time decision intelligence.
The report, “AI-Enabled Reshoring: Why America’s Manufacturing Return Requires an Intelligent Operating System,” is based on polling conducted during Q2 and Q3 2026 among 321 industry respondents, including 229 manufacturing executives and 92 AI professionals working in manufacturing.
The report’s central finding is clear: 88% of manufacturing executives say their reshoring or nearshoring strategies depend materially on AI-enabled automation, analytics, or digital operations. An additional 74% say at least one reshoring business case would fail, stall, or require substantial redesign without productivity gains from AI or automation. Among the AI professionals surveyed, 96% say most reshoring projects underestimate their data-readiness requirements.
“Reshoring is now a systems-engineering challenge, and AI must function as the intelligence layer of the industrial operating model,” said Vasyl Harasymiv, founder of Applied Artificial Intelligence LLC. “The question is no longer whether manufacturers can launch isolated models or automation pilots. The real test is whether they can deploy governed, production-grade AI across capital planning, industrial data, quality, maintenance, scheduling, workforce augmentation, energy management, and supplier risk-and connect those systems to measurable improvements in throughput, yield, uptime, working capital, and recovery time.”
“For AI practitioners, the standard should be uncompromising: a system that is not embedded in an operational workflow, evaluated against known failure modes, and monitored against business, safety, and quality outcomes is not yet industrial AI; it is a demonstration,” Harasymiv added. “For business leaders, policymakers, and the public, the implication is equally clear: the United States will not create durable manufacturing advantage by relocating yesterday’s operating model. It must build factories that improve continuously through intelligence.”
The report concludes that traditional reshoring plans are too often based on outdated assumptions about labor availability, data quality, supplier stability, predictable power access, and static cost models. In practice, modern domestic production must contend with labor scarcity, technical skills gaps, fragmented operational data, supplier volatility, power constraints, cybersecurity exposure, and ramp-up risk.
“The old model relied on wage arbitrage. The new model will rely on intelligence arbitrage,” Harasymiv said. “AI is the productivity layer that enables reshored factories to compete. It increases worker leverage, converts fragmented data into operational visibility, transforms static spreadsheets into continuously updated total-cost models, and helps turn plant announcements into productive capacity.”
The report defines AI-enabled reshoring as a full-stack operating transformation rather than a single technology purchase. The required capabilities include AI-driven total-cost modeling, site and power analytics, digital twins, machine vision, predictive maintenance, autonomous scheduling, technician copilots, supplier-risk intelligence, industrial data backbones, and human-in-the-loop governance.
“A reshoring strategy without an AI architecture is a capital request with unpriced execution risk,” Harasymiv said. “Boards should ask not only where a factory will be built, but which data, automation, governance, and decision systems will make that factory competitive after launch.”
The findings also reveal a significant manufacturing maturity gap. Many companies have introduced AI pilots in quality, maintenance, planning, or analytics, but far fewer have connected AI to capital allocation, site selection, workforce design, supplier localization, and factory execution. The report warns that isolated pilots will not be sufficient to support the next phase of U.S. industrial growth.
“AI pilots do not create a durable reshoring advantage unless they are integrated into the operating workflow: the MES, CMMS, QMS, ERP, supply chain, frontline work, and board-level investment model,” Harasymiv said. “That is where AI moves from experimentation to industrial infrastructure.”
The report calls on boards, manufacturers, policymakers, and economic development leaders to treat AI readiness as a prerequisite for credible reshoring. It recommends that reshoring proposals include a quantified AI productivity assumption, data-readiness score, automation payback model, power-risk assessment, workforce augmentation plan, cybersecurity baseline, and roadmap for scaling AI across factory and supplier networks.
“The next manufacturing race will not be won by the country that simply brings back the most production,” Harasymiv said. “It will be won by the country that builds the most intelligent domestic production system. Reshoring brings the factory home. AI makes the factory competitive.”
Key Findings from the Report
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88% of manufacturing executives say reshoring or nearshoring depends materially on AI-enabled automation, analytics, or digital operations.
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74% say at least one reshoring business case would fail, stall, or require substantial redesign without AI or automation productivity gains.
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79% identify labor availability or technical skills shortages as a top-two reshoring constraint.
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75% say traditional landed-cost models understate the full cost and risk of offshore production.
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69% say their ERP, MES, supply-chain, or plant-floor data is not sufficiently clean or integrated to scale AI confidently.
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96% of AI professionals say most reshoring projects underestimate data-readiness requirements.
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86% of AI professionals say human-in-the-loop AI governance is essential in safety-, quality-, or compliance-sensitive factories.
Download the full report: https://blackbookinsights.com/research/
About Applied Artificial Intelligence LLC
Applied Artificial Intelligence LLC, founded by Vasyl Harasymiv, is a Chicago-based AI implementation consulting firm that helps organizations translate artificial intelligence from concept into practical operating capability. The company works with organizations in manufacturing, banking and finance, and reshoring on AI strategy, readiness assessments, workflow automation, governance, analytics, and implementation planning.
About Black Book Insights LLC
Black Book Insights LLC is a reshoring and manufacturing advisory and research organization providing analysis on industrial policy, supply-chain redesign, factory investment, domestic manufacturing momentum, and the evolving economics of global production. Founder Doug Brown is also the author of the Amazon Business bestseller “The Black Book of Reshoring: The Essential Resource for America’s Next Manufacturing Boom,” published by Wiley and available where books are sold https://www.wiley.com/en-us/shop/general-introductory-business-management/the-black-book-of-reshoring-the-essential-guide-to-america’s-new-manufacturing-boom-p-9781394393749
Media Contact
Doug Brown
Black Book Insights LLC
Douglas.Brown@BlackBookInsights.com
1-800-863-7590
www.BlackBookInsights.com
SOURCE: Black Book Research
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