Author: Jeff DeBellis
Lost in the news and hype of Artificial Intelligence’s impact on office work is the current and potential effects AI and machine learning are having on manufacturers and production work. But before ChatGPT and the wave of generative AI, cutting edge manufacturers were beginning to utilize artificial intelligence and machine learning to dramatically reshape factories and work.
Both the implementation of AI in offices and its impact on jobs remain highly uncertain. In manufacturing, the use cases, potential, and even workforce implications of artificial intelligence are more defined, even as companies are working through the adoption and potential application of generative AI in their workplace. This article expands on the 2024 Best Practices for Growing Manufacturing in North Carolina report by the NC Department of Commerce and NC Manufacturing Extension Partnership (NCMEP) by exploring one element of Industry 4.0 specifically: artificial intelligence.
How AI Can Benefit Manufacturers
- Prediction – intelligence gathering using AI and data analysis to anticipate outcomes, risks, equipment failures, supply needs, and customer demand.
- Planning – application of AI's analytical power to improve strategic and tactical preparations across the business and supply chain.
- Production – utilizing AI in process and physical automation such as programing robots, cobots (collaborative robots), and technical equipment; managing product quality (through vision systems and other technologies); and assessing the production process for improvement.
- Performance – assessing and optimizing operational and financial performance (e.g. productivity, efficiency, cost savings, profits, etc.).
One way AI is currently being implemented through all four areas is in the creation of “digital twins.” The digital simulation of the manufacturing process allows manufacturers to experiment and test production systems and equipment virtually prior to physical execution.
Generative AI (Gen AI) – a subset of artificial intelligence and machine learning which generates new and original content (e.g. ChatGPT, Claude, Copilot, Gemini, etc.) – is making headlines for its impact or potential impact on office jobs. But manufacturers are finding potential in this new technology as well to help program software, develop virtual troubleshooting and support assistants, optimize production schedules, advise on decision-making, and document procedures and author process manuals.
Manufacturers’ Current AI Usage
Integrated use of AI remains low among businesses in general according to the U.S. Census Bureau’s September 2025 Business Trends and Outlooks Survey. Only 10% of all North Carolina businesses report using AI in the past two weeks in their production of goods or services. Among manufacturers nationally, half that rate, 4.8%, say they used AI – significantly lower than the 30% usage by the Information industry, the top adopter.
However, low current usage masks strong interest in AI among Manufacturing’s executives and plant managers, with ambitious future plans. According to the Manufacturing Leadership Council’s 2025 Future of Manufacturing Project, whether they’re an executive in the C-suite or supervisor on the factory floor, AI is not widely being used on a daily or regular basis. However, many companies’ senior leadership are aware and becoming educated on AI, even if that hasn’t trickled down through their organization yet (see Fig 1). This has resulted in the majority of companies having either an AI strategy in place (18%) or in the works (42%).
Looking ahead, 92% of manufacturers believe AI will impact their business and competitiveness, with 68% viewing it as essential to growth. Accordingly, 61% plan to increase AI investments over the next two years.
What about Generative AI?
Gen AI is predicted to have lower rates of worker adoption in industries that generate physical products than personal or digital services. This doesn’t necessarily mean that Gen AI won’t have a role in Manufacturing or that its impact won’t be profoundly felt by factories and workers.
“Traditional” AI tools and processes like vision systems and machine learning are most commonly deployed in Manufacturing. But Gen AI, large language models (LLMs like chatbots), and natural language processing (enabling computers to understand human language) are also being widely used and projected to grow – Figure 2. Next to machine learning, edge AI, where AI runs on local devices enabling real-time processing and powering the internet of things (IoT), is expected to grow the most as the technology evolves over the next two years.
Potential Impact of AI on NC Manufacturing
Despite AI's growing importance, many researchers suggest that production workers face relatively lower direct exposure to generative AI tools. But that doesn’t mean manufacturing jobs will be immune. Some – particularly white-collar positions in business operations, management, or technical programmers – are likely to see increased application in their work, whether augmenting or automating certain tasks.
AI deployment in robotics and systems would likely impact a much larger number of workers in production, repair and maintenance, and technical positions. The adoption of AI may lead to an acceleration of physical automation that has largely been predicted for years. In fact, previous LEAD analysis revealed that North Carolina’s workforce, partly due to its large Manufacturing sector, is more exposed to change due to automation than the nation overall.
However, according to a 2024 national survey by the Manufacturing Leadership Council, 77% predicted their overall headcount would not be impacted by AI (45%) or will actually grow (32%) by 2030. But still one-in-five manufacturers (21%) anticipate reducing overall jobs in their company as a result. An even larger number, 95%, “expect to retrain or reassign at least a portion of their workforce as a result of increased AI adoption” – with over a third believing this will impact at least 10% of its workers by 2030.
Implications for NC’s Workforce & Business Development Systems
While uncertainty remains about AI's specific impacts on employment, one conclusion is clear: AI will play a significant role in Manufacturing's future. North Carolina’s economic and workforce development professionals should be prepared so that our state can maximize the benefits of this new technology, while minimizing potential business and employment loss, starting with the following:
- Increase engagement with Manufacturers across North Carolina to better understand how AI and automation are being implemented in their company and industry.
- Serve as a connector between small- and mid-size businesses and technology solutions to help identify, capitalize, and implement solutions for companies to survive, compete, and thrive, in a highly competitive global industry.
- Assist Manufacturers in identifying opportunities for employees affected by new technologies or efficiencies to be reskilled and/or reassigned within their company.
- Work with Manufacturers in preparing workers who may adversely be impacted by technology to transition to new employment outside their firm with minimal employment disruption.
Industry-changing technology innovation and adoption is not new to Manufacturing, which has witnessed multiple revolutions in the past century. Through each change, companies and jobs have been lost and new ones have been created – more recently, resulting in a net decline in employment as efficiencies are gained. Adopting the lessons of the past, North Carolina’s workforce and economic development systems can better assist businesses and their employees to manage upcoming challenges and be a leader in the future of Manufacturing.