Automation in Manufacturing Operations

While the increasing use of AI has been making news in the U.S. manufacturing industry, countries such as China and Japan have been running fully automated factories that require minimal human intervention for decades.

These so-called “dark” or “lights-out” factories use machines, robots and automated systems to operate 24/7 without breaks, lighting, heating or other conditions humans require.

A famous example is a Fanuc factory in Japan, which reportedly runs for a month without much human input to build robots at the rate of 50 per 24-hour shift. Philips is doing something similar at its razor-manufacturing plant in the Netherlands, where 120-plus robots run the fully automated factory and require fewer than 10 workers for quality assurance. 

Could the U.S. implement such concepts to help alleviate some of the industry’s persistent issues, like labor shortages and supply chain disruptions?

Increasing use of AI and automation in the U.S.

U.S. manufacturing companies have increasingly begun experimenting with automation in recent years as the pandemic drove interest in artificial intelligence and digitization. However, adoption is slower and there’s no fully automated plant in the region as of yet. 

According to experts, the closest U.S. manufacturers have come to “dark” factories is Tesla’s heavily automated gigafactories. The company reports 90% automation at its Nevada plant, according to the Reno Gazette Journal, and even higher in China.

“Most U.S. manufacturers pursue gradual automation — they extend lights-out operations step by step rather than build entirely new dark factories,” said Daryl Edwards, a former plant manager and the founder of Agent Impact, a company working with manufacturers to implement AI solutions.

This is the opposite approach to China and Japan, where many lights-out factories were built from the ground up for new products, said Craig Melrose, global managing partner of advanced technologies and mobility at Htec, a company providing AI and embedded product engineering services.

“In contrast, the U.S. would largely be retrofitting existing facilities, which were designed for human operations,” said Melrose.

This comes with its own upfront costs, which many companies may not be ready to bear. 

“Implementing automation is expensive and most manufacturers must phase it in gradually to make it financially viable and ensure a clear return on investment,” said Stephanie Scearce, vice president of workforce innovation at the Georgia Association of Manufacturers, via email.

“Budget constraints, organizational understanding, process continuity, and (perhaps most importantly) leadership buy-in all play critical roles in adoption,” she said. “Aligning these factors is challenging and achieving that often takes significant time and resources.”

That’s why hybrid models are on the rise in the U.S., where some aspects of manufacturing are automated under human supervision.

“We’re not going to see a whole shift to dark factories in the next five years, but hybrid models with smart automation, digital twins, and AI copilots are accelerating rapidly,” said Alex Shikany, executive vice president of the Association for Advancing Automation, or A3.

That has given rise to collaborative robots, known as cobots, which require a tech-trained human operator. In Q2 , nearly a quarter of the units ordered in North America were “collaborative,” Shikany said, noting larger demand from automotive manufacturers. “They’re a clear signal that manufacturers are building automation with people, not just instead of them.”

Edwards interviewed 20 manufacturing executives about their automation journeys and found that one of his clients, a discrete manufacturing company, had begun implementing lights-out manufacturing at night.

“In the last hour or two of every shift, they initiate operations in all the semi-automatic machinery like CNC machines so they run lights-out overnight unsupervised,” he said.

This benefits the operators who prefer daytime shifts and want to avoid shift rotation. It also benefits the company since it can manufacture much more in a given time period without increasing costs, Edwards added. 

Currently, automation is the most common application in U.S. manufacturing sectors with high-volume, repeatable tasks such as electronics, automotive components, semiconductors and pharmaceuticals.

These sectors benefit from precision, consistency and around-the-clock uptime, Shikany said. As AI-powered digital twins improve, he added, dark-factory readiness will grow in industries where safety and optimization are critical, like food and beverage, and chemical manufacturing. 

Is AI taking away jobs?

When asked about what happens to the workers as factories increasingly adopt automation, experts said it doesn't eliminate the need for humans, but shifts their roles.

“Even in a highly automated environment, people are still essential for maintaining equipment, programming systems, troubleshooting issues and managing the complex touchpoints that make manufacturing run smoothly,” Scearce said. “Rather than aiming for completely unmanned facilities, I see the real opportunity in leveraging automation to create a balance between our shrinking labor supply and the growing demands of manufacturing.”

In practice, Scearce said, “automation will likely replace the types of manufacturing jobs we struggle to retain, which are often entry-level, highly repetitive, or physically demanding roles and jobs that fall into the ‘4 Ds’: Dark, dirty, dull and dangerous.”

Changes in the workforce are inevitable as more companies adopt AI and automation, but that doesn’t necessarily have to mean sending all the workers home. 

This is apparent in the upcoming U.S. factories as companies are hiring workers to implement certain automation systems as well as continuing manual processes still untouched by AI. 

“Our industry’s focus should be on upskilling and reskilling, not replacement,” Shikany said. “The manufacturing jobs of the future involve operating and maintaining automation systems, interpreting data from AI models and designing new workflows.”

To help with this change, A3 has begun offering certification and training programs in robotics, machine vision, motion control, and automation. The organization also hosts conferences and events, webinars, and online courses focused on implementation solutions. 

Many community and technical colleges, as well as company training centers, have started similar initiatives to match the growing need for an AI-ready workforce. 

Such transformation is natural and unavoidable as industries evolve from hand tools to mass production, and now to AI and lights-out manufacturing, Melrose said. 

“Digital was considered the four industrial revolution and AI could be viewed as the fifth,” he added. “With each revolution, workers were asked to change, adapt and learn new skills, which will continue to be true.”

A survey of more than 500 manufacturing executives found that 93% believe the world is on the brink of the next industrial revolution and must reinvent how their companies operate in order to survive, according to PwC’s new Future of Industrials rreport.

Industrial leaders are looking to reimagine their operations with an emphasis on supply chain resiliency, modular manufacturing, energy independence and autonomous systems as major shifts in technology, policy and global competitiveness take place.

PwC surveyed industrials and C-suite leaders across aerospace and defense, automotive, chemicals, engineering and construction, oil and gas and energy. About 73% of the respondents agreed the companies that fail to embrace industrial realignment will be irrelevant within a decade.

Considering the fast advancements in artificial intelligence and the move away from supply chain globalization to geopolitical sovereignty, “those who don’t change … I think do face a level of irrelevance,” said Ryan Hawk, an industrial products and services leader at PwC.

“People are becoming much more internally focused and doing things that are … within a national interest because they see it as a competitive advantage,” Hawk said.

The so-called industrial revolution starts with bringing production closer to major markets. Manufacturers across sectors, such as Apple, Eli Lilly, TSMC and more, have committed billions of dollars in U.S. investments. Automation has lowered the cost of reshoring and U.S. tariffs and tax incentives are driving the change, according to PwC. Additionally, local production promises better quality control and speed to market.

If no action is taken, about 90% of executives believe companies relying on distant suppliers in 2030 “will be extinct by 2035,” according to PwC’s survey.

Beyond supply chain realignment, factories are becoming more autonomous and worker skillsets are changing. Over the next five years, nearly half of the surveyed leaders expect their operations to be fully modular, a strategy that breaks production into separate modules for added flexibility. That is up from about 6% of C-level decisionmakers who consider their operations fully modular today.

Executives are also backing “self-healing supply chains” that can automatically detect, diagnose and correct disruptions, according to PwC. Technologies with self-healing capabilities such as predictive maintenance and digital twins have the potential to bolster supply chain resiliency and reduce downtime costs.

As technology advances, robotics are augmenting human jobs. Nine out of 10 executives believe AI is forcing them to rethink job roles in the sector, and preparing employees for this shift has become a top workforce development priority.

“I think the work changes. I think the skills change. I think in some cases, the skill level changes,” Hawk said. “I think in other cases, the very way we educate people might have to change.”

By 2030, about half of the surveyed leaders believe AI will have taken root within their workforces, with 33% thinking most roles will be enhanced with intelligent tools or AI augmentation, according to PwC. In this future, “chips are the new oil” and “data centers are the new factories.”

Reflecting on the overall survey, Hawk said that he was surprised to find that executives overwhelmingly agreed they are at the “tipping point” of the next industrial revolution.

“Just how prevalent this feeling is, that things are going to change in some pretty big ways, and I think pretty fast too,” Hawk said.

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By Alithya

Manufacturing is undergoing rapid change, driven by technology adoption, labor pressures, quality demands, sustainability and supply chain volatility. The Alithya Manufacturing Survey highlights how these forces are reshaping investment in operations and talent.

Surveyed manufacturers are prioritizing supply chain tech, AI, automation, machine learning, IoT and analytics to stay competitive.

Accelerating Technology Adoption

Over half of respondents cite operational efficiency, driven by data and automation, as their top innovation priority. In a related survey, 62% of manufacturers say they have already adopted IoT technologies in their assembly or manufacturing operations¹.

This aligns with global technology adoption trends. With 18.8 billion IoT devices in use (2024), manufacturers have a strong foundation for data-driven operations².

AI and machine learning appear central in future roadmaps. According to Forbes, 93% of manufacturers see AI as a transformative force for the year ahead³. The Alithya survey reflects the same sentiment, with predictive analytics, Copilot/AI and process automation ranking among the most expected technology deployments.

Core AI/ML use cases gaining traction:

• AI vision for quality: Machine-vision systems driven by AI can detect assembly defects, weld anomalies, incorrect part installs and other quality escapes, helping reduce recalls and rework.
• Predictive maintenance & operational reliability: Combining sensor networks with ML models allows manufacturers to forecast equipment failures (motors, gearboxes, conveyors) before they occur—thereby reducing unplanned downtime and spare-parts cost.
• Throughput and yield optimization: AI supports production scheduling, yield improvement across batch and continuous processes, and alignment of demand signals with manufacturing operations.

As enterprise IoT spending is projected to grow ~14% CAGR through 2030⁴, AI adoption is expected to scale in parallel, supported by increasingly connected plants.

Human–Machine Collaboration and Industry 5.0

Industry 5.0 principles are gaining momentum, emphasizing human-machine collaboration instead of full labor displacement. Alithya’s survey reinforces that choice, with less than 5% of respondents prioritizing using technology to replace workers. Most view AI as a tool to augment human capability, not eliminate it.

• Collaborative robots (cobots) are a focal point of this shift. The global cobot market is projected to grow from $2.14B in 2024 to $11.64B by 2030 (31.6% CAGR), driven by use in machine tending, assembly and packaging⁵.
• Solutions such as augmented reality (AR) work instructions, AI-based vision “poka-yoke” (mistake-proofing) checks and digital assistance help address skill gaps, reduce human error, and speed changeovers.
• Ergonomics & safety: Advances in power-and-force-limited robotic modes, quick-teach interfaces and reconfigurable tooling help accelerate deployment and improve worker well-being.

These developments reflect a shift in mindset: automation that complements rather than replaces human workers, aligning with human-centric manufacturing philosophies.

Workforce Development: A Parallel Investment

• Technology is only one pillar of modernization. Half of Alithya respondents plan to cross-train workers and expand skill redundancy, enabling staff to flex into multiple roles and ensuring continuity.
• Talent attraction and retention remain critical—skilled labor is harder to find, and the automation wave means new skills are needed (data analytics, automation maintenance, robotics).
• Cybersecurity training is also rising in importance: as systems become more connected (IoT, edge computing, AI), human security factors are increasingly critical. 45% of Alithya’s survey respondents conduct regular cybersecurity training, underscoring the fact that personnel investment is now tightly linked to operational resilience.

In short, workforce investment is no longer optional — technology needs to deliver value.

Supply Chain Resilience and Risk Management

The Alithya survey highlights continued supply chain anxiety: 35% of manufacturers cite disruption risk, and over 30% point to market uncertainty and cost management as persistent concerns.

Supporting this trend, ongoing geopolitical disruptions have pushed many manufacturers toward nearshoring/reshoring and supplier diversification.

Respondents identified cloud computing as essential for real-time data management and collaboration. Broader industry research reinforces this direction, as manufacturers increasingly apply cloud platforms to ERP, analytics, digital twins and cybersecurity initiatives⁶.

What This Means for Mid-to-Enterprise Manufacturers

• Build the foundation first – sensors, data pipelines, connectivity and unified models before scaling AI/ML.
• Start with high-payoff, proven use cases – e.g., AI-vision quality inspection and predictive maintenance often self-fund further deployment.
• Design for scale and repeatability – adopt architecture standards, data standards and training protocols to avoid “pilot purgatory.”
• Embrace human-centric automation – design cobot cells, AR workflows and change-over systems with worker ergonomics and flexibility in mind.

Conclusion

The industry is aligning around a blended strategy: automate smarter, digitalize deeper and develop people continuously. The Alithya survey confirms that manufacturers are not just investing in systems — they are investing in adaptability, resilience and long-term competitive strength.

Download the complete Alithya Manufacturing Survey & Analysis Report. Learn how Alithya and our team of manufacturing technology experts can best serve as your trusted advisor for strategic consulting, enterprise transformation and business enablement.

Article Sources:

• 1 - Ubisense+1
• 2, 4 – IOT Analytics
• 3 – Forbes
• 5 – Grand View Research  
• 6 - Comarch

As digital technologies are increasingly converging with physical ones, robotics vendors are looking at the next phase — physical AI, the convergence of physical and decision-making automation. At the same time, companies are looking to how their artificial intelligence can operate in a physical world.

Multiple recent developments highlight efforts to introduce a next generation of technology combining physical and decision-making capabilities. These investments and efforts will lead to a new generation of solutions that will make integrating automation into the manufacturing process easier and more flexible.

Nvidia’s physical AI partnerships

In a major announcement for Japan’s tech sector, Fujitsu and Nvidia recently launched a partnership to co-develop a next-generation AI chip by 2030. This will combine Fujitsu’s high performance compute capabilities with NVIDA’s graphics processing units.

Significantly, the companies said they’re also exploring a collaboration with robot manufacturer Yaskawa Electric. The integration of new AI technologies into its robot systems will allow Yaskawa to leverage the Fujitsu–Nvidia alliance into real-world “physical AI” applications on the factory floors. It will also give Yaskawa customers access to digital twin technology through Nvidia's Omniverse platform.

Nvidia also recently announced plans to support technologies for designing and simulating factory digital twins, including the simulation of robot fleets, as an expansion of its Mega Nvidia Omniverse Blueprint. The company also referenced Fanuc and Foxconn as early supporters of its OpenUSD technology for 3D-based robot digital twins. 

Softbank’s ABB investment

ABB Group also announced plans to spin off its ABB Robotics division as a separate entity that will be sold to SoftBank for nearly $5.4 billion. The deal, which is expected to close in “mid-to-late 2026” will combine one of the top two industrial robot’s vendors with SoftBank’s expansive portfolio of AI and compute capabilities, driving new developments in AI-enabled robotics.

The robots of today aren’t the ones of tomorrow

Industrial robots in factories are commonplace supporting the automation of work, especially in sectors such as automotive and electronics, and increasingly in consumer-packaged goods. But they still require human effort, skills and resources that can be both expensive and in short supply. 

Traditional robots are programmed to perform predetermined tasks with limited flexibility, necessitating exact positioning and static environments. Any changes to a production line, the products produced, or their form factors means reprogramming the robot. This often requires manual intervention in a changeover as well as effort to set up and commission robots into new environments.

This recent investment and partnership news, along with efforts of other robot vendors in developing intelligent machines, is the latest sign that industrial robotics are maturing.

Starting with blind and unintelligent robots, the market is currently seeing the integration of machine vision capabilities enabling robots to “see” and respond to their surroundings. This enables them to identify objects, check positioning and make basic adjustments. This visual capability is enabling robots to become more involved in quality control applications and more complex manufacturing tasks that require environmental awareness.

Physical AI, or adaptive robotics, can help manufacturers that are battling with a more volatile supply chain, as well as demand for a greater variety of goods and product customization. This requires greater flexibility in production and automation that can adapt quickly to a dynamic environment without extended downtime and the costs associated with additional robot programming. 

As new adaptive robots are introduced, they will enable rapid adaptation to a greater breadth of products, production lines and changing environments by self-adjusting taught trajectories with no human involvement.

With the use of digital twins, companies can also simulate entire robotic workflows in a virtual environment before deploying on actual production lines. This significantly reduces time and expense in the trial-and-error phase of new automation implementations, whilst eliminating the risk and expense associated with disrupting live production, and allows companies to optimize how and where robots can be best introduced most quickly.

Looking ahead

Developments in physical AI will lead to robots that can operate more collaboratively and intelligently with a human workforce. This will optimize work and reduce some of the need for safety zones around the equipment, thereby reducing the overall footprint of systems. The skillsets required by manufacturers will evolve, reducing the reliance on specialized robotics programmers and increasing the demand for professionals with AI expertise. 

Omdia also expects to see continued activity on the supply-side landscape as robot vendors invest to ensure their portfolio goes beyond manual task automation to extend into decision-making through AI capabilities. We expect to see further acquisitions and investments as many hardware vendors have found challenges with building up their in-house AI capabilities.

As Nvidia CEO Jensen Huang said in 2024, “the next wave of AI is physical AI.” In an interesting twist, as illustrated by this month’s partnership announcements, this time we may see AI companies buying in physical automation capabilities.

As manufacturers look to adopt the latest artificial intelligence and automated technologies to drive efficiency on the shop floor and remain competitive, one of the biggest challenges is convincing their workers that the changes are a good idea.

Today’s U.S. workforce is more worried than hopeful about future AI use — about a third of those surveyed recently by the Pew Research Center say it will lead to fewer job opportunities in the long run.

Manufacturing leaders convened at the North American Manufacturing Excellence Summit in Fort Worth, Texas, in April 2025 to discuss their strategies around how to quell anxieties and job security concerns. This includes tactics such as as implementing technologies that expedite tedious tasks and processes, like picking up parts or distilling hundreds of pages of business documents.

In some cases, the technology has even opened up the possibility for factories to operate shifts without human supervision, allowing for a shorter work week.

Here are some examples of how manufacturers are incorporating AI, automation and robotics to not only boost productivity, but to improve company culture and help workers upskill for the future.

Automating dull tasks and Deere’s cranky robot

Heather Bishop, global director of manufacturing and operations at John Deere Power Systems, said during the manufacturing conference that the farm equipment maker is leveraging autonomous business technologies not to eliminate jobs, but to free up its workforce capacity for other types of tasks.

For example, Deere & Co. is using large language models to help its supplier quality engineers read through stacks of warranty claims at faster rates. Typically, they can spend up to 15 hours a week combing through claims, Bishop said, but with AI tools looking for key words and phrases that time has shrunk to two hours.

“What a way for us to then take the remaining 10-plus hours and say, ‘Here's some other problems we need to solve,’ or as we're experiencing attrition, just filling in that particular space and funding something else that leads to innovation,” Bishop said.

On the factory floor, Deere is looking for other improvements by encouraging its workers to experiment with automated technology — within reason. Bishop said she is cultivating a “gamification” culture and a safe space to experiment, try and fail, but without it leading to engine failures and other manufacturing costs. 

Importantly, Bishop said she wants to make her workers excited about embracing AI tools and other advanced technologies, in part, by making it fun.

At one factory, Deere’s employees were encouraged to name one of the engine robots as if it was a pet or family member. The team decided on “Cranky” not because of the robot’s disposition, Bishop said, but because “he picks up cranks and puts them on the line.”

It’s a minor thing to name a robot, but the act has the potential to warm employees to the idea of working with, rather than against autonomous technologies.

“We are going to struggle more with individuals not embracing the new technology and not bringing it in because of their fear, their concerns, their lack of excitement, their lack of us tying the value proposition to it,” she said. “The people’s readiness level is all associated with the cultures we create.”

‘Lights out’ manufacturing with Procter & Gamble

Consumer products giant Procter & Gamble is leveraging robotics and automation to shorten the manufacturing work week for its employees by running a four-hour unattended night shift at a Berlin, Germany, factory.

Rather than have five, eight-hour shifts, the company introduced a four-day work week with two 10-hour days to lower costs and create a better work-life balance for its employees, Amy Rardin, global senior director of supply chain digitization and external strategic partnerships, said at the Fort Worth conference.

P&G employees galvanized around the idea with a focus on reducing losses and touches on the factory equipment, according to a company presentation. The first unattended shift ran successfully on July 1, 2024.

“We’ve been running almost a year now at that site, and we have several other sites that are running with other opportunities as well,” Rardin said. P&G has been able to replicate similar programs at six to eight plants so far.

“It really is about thinking differently with a growth mindset about how to collectively come together and solve a problem that meets multiple audiences,” Rardin said.

The U.S. manufacturing industry lost 78,000 jobs over the past year with 12,000 cuts in August alone, according to the latest federal data. This comes as automation is ramping up in factories, but it’s far from the only factor.

While the September employment data wasn’t released due to the government shutdown, the August 2025 labor turnover survey shows a 12% dip in job openings compared to 2024, with 313,000 job separations in manufacturing.

Experts say this isn’t new. Manufacturing jobs have been declining since February 2023, now reaching the lowest level since the onset of the COVID-19 pandemic.

The numbers have been going down since 1979. Now, factors such as the increasing use of AI and automation, tariff changes, tightening immigration policies, and an aging workforce are leading to further decline. 

AI and automation

Manufacturing companies have been facing a labor shortage for years. Nearly 2 million jobs — half of all new positions created — could be unfilled by the end of the decade, according to data from Deloitte and The Manufacturing Institute. 

Many companies have turned to artificial intelligence and automation to bridge the gap, with some countries like China and Japan running fully automated factories. Some plants in the U.S., like Tesla’s Gigafactories, are also implementing similar models.

Sectors with high-volume production and repetitive tasks, such as automotive, semiconductors, electronics, aerospace and pharmaceuticals, are experiencing the highest adoption of AI and automation. Experts say other divisions will follow suit as implementing this technology becomes more accessible and financially viable. 

While this has helped keep operations running as manufacturers struggle to hire and retain workers, it raises the question of what happens to the labor force replaced by machines. Is technological advancement stealing people’s jobs?

According to the latest SHRM analysis, 15% of jobs in the U.S. across all industries, about 23 million total, are at a high risk of being displaced due to automation. 

Many experts point to reskilling as a solution, saying workers’ responsibilities could change rather than be completely eliminated. 

“Factories will keep getting smarter and more automated, but people will not disappear from the equation,” said Janelle Bieler, U.S. head of tech talent solutions at Akkodis, a digital engineering consulting company that is part of The Adecco Group.

“The larger shift is that there are not just fewer jobs, but different jobs,” she said. “Traditional assembly roles are declining while demand is growing for technicians who can work with robotics, maintain advanced equipment and use data to keep production running smoothly.”

Due to this, even though automation is making some positions redundant it’s also creating new roles that didn’t exist before. 

Several programs, including the Akkodis Academy, are offering resources to support this transition. But many manufacturers aren’t in a position to make drastic changes. 

“This transition will be more gradual as not all companies can afford to invest in automation so there will still be a need for people to support manufacturing, especially for small and medium enterprises where investment capital is scarce,” said Sumeet Kaul, a managing director in FTI Consulting’s corporate finance and restructuring segment.

“Reskilling is a potential solution but we need to remember that this is not a one-to-one replacement,” said Kaul.

This means a lot of jobs will continue to be replaced by machines, said Wafa Hakim Orman, associate dean of the College of Business and associate professor of economics at the University of Alabama in Huntsville, noting that this has happened before.

“In 1870, over half the U.S. labor force worked in agriculture but today, it's less than 2%,” said Orman.

The labor force moved into manufacturing and services as agriculture mechanized. Orman said we should expect to see the same pattern continue in manufacturing, where factories are increasingly automated, and reducing the reliance on human labor.

While some workers are being reskilled to work on these automation systems, the only option for others might be transitioning to a different industry. 

Tariffs and tighter immigration policies

While AI and automation are bringing long-term changes that will change the very core of how the manufacturing industry operates, two other factors have also affected production recently.

First, the uncertainty around tariff policies has put some manufacturers in a “wait-and-see” mode, leading to stalled projects and hiring freezes, industry experts said. 

“Exporters can't forecast demand, importers are uncertain about the price and how much of the tariffs consumers and foreign suppliers will bear, and manufacturers who use imported materials, tools, or components are dealing with large swings in their costs,” Orman said. It is difficult for businesses to plan long-term investments in such a volatile environment, she added. 

Amidst the recent policy changes, some plants have shut down, paused operations, changed locations, consolidated or discontinued certain production lines, all of which contributed to layoffs. 

Second, President Donald Trump’s administration has implemented several changes to tighten immigration policies, making it harder for new foreign workers to enter and for those already here to stay. Some of these changes include a $100,000 fee for new H-1B visas, increased scrutiny of visa applicants’ social media activity, plans to end birthright citizenship, limiting access to health insurance benefits, and additional funding for detention and deportation. 

There’s also been an increase in U.S. Immigration and Customs Enforcement raids at major facilities, such as the Hyundai plant in Georgia, where nearly 500 foreign workers were detained in September. Some factories across the country have reported delayed shipments and reduced production as a result.

The administration’s stated goal is to prioritize domestic hiring. Orman said this could possibly increase hiring, but it could also boost the pace of automation as some firms replace immigrant workers with machines, especially if local workers expect higher wages. 

All of this has made 2025 an unpredictable year for manufacturers, with experts forecasting many more changes ahead.

“In the long run, new technology has typically made us more productive,” Orman said, “but in the short run, it can lead to significant disruption as people need to switch industries or occupations, and frequently retrain and learn new skills.”

Akkodis’ Bieler said this will require ongoing adaptability by all involved.

“The best safeguard for both workers and employers is steady investment in skills, so people are prepared to move into the roles that the market continues to demand,” she said. “Jobs will disappear, yes, but history shows us that new jobs always take their place.”

Uncertainty surrounding tariffs and the economy is driving manufacturing CEOs to prioritize supply chain resilience and AI investments, according to a 2025 CEO Outlook survey conducted by KPMG in September.

Among the 400 leaders surveyed, 63% of manufacturing CEOs said supply chain challenges, including disruptions to global supply chains, are hindering their ability to innovate at scale. Despite challenges in innovation, 68% of surveyed CEOs named AI as a top investment priority for their organization, and 69% plan to spend up to 20% of their budget on AI over the next year.

Uncertainty in the business operating environment is “casting a very, very long shadow for manufacturers,” said Brian Higgins, KPMG’s U.S. industrial manufacturing sector leader. “Economic policy uncertainty has been difficult to navigate, to say the least.”

Tariff uncertainty has weakened demand in the manufacturing sector. The industry contracted for the seventh consecutive month in September, as measured by the Institute for Supply Management’s Purchasing Managers’ Index, and companies have reported declines in orders as tariffs weigh on exports.

But manufacturing executives aren’t sitting on the sidelines waiting for better times to come along. Rather, they’re putting supply chain resilience “front and center,” Higgins said, noting that manufacturers are deploying various strategies to guard against supply chain risks.

Some are refining or renegotiating their agreements with suppliers to incorporate tariff-related costs. Others are using dynamic pricing or financial hedging. Some manufacturers are looking to move production or reshoring to improve the resilience of their supply chains. General Motors, for one, plans to spend more than $10 billion over the next two years to onshore more of its production, and other companies have announced their own major pledges.

Restructuring the supply chain, however, is less common than financial engineering, Higgins noted. Supply chain alterations take time and could come with higher labor costs or upfront capital to expand manufacturing capacity. With tariffs fluctuating frequently, a long-term investment may not make sense for many businesses, according to Dan Cannistra, a partner at international law firm Crowell & Moring.

“It's very difficult to make changes in supply chains without knowing where exactly the tariffs are going to be a year from now,” Cannistra said.

In fact, only 18% of manufacturing CEOs in KPMG’s survey named reconfiguring the supply chain among their top priorities. “There's a little bit of a wait-and-see approach that's prevalent,” Higgins said.

As manufacturers battle tariff-related cost hikes, they’re focusing on efficiency – and one way to do that is via automation and AI. Businesses are taking the next step from generative AI, which includes large language models and chatbots, to agentic AI, in which bots automatically complete actions or tasks based on instructions.

KPMG’s survey revealed that many CEOs expect to embed AI agents across their organizations, with leaders managing multiple AI agents as part of their roles. More than half (54%) of the surveyed manufacturing CEOs anticipate agentic AI will significantly improve efficiency or drive growth.

Procurement is particularly ripe for AI, Higgins noted. AI can help design and manage contracts while also preventing contract value leakage, in which a contract's potential value differs from the actual value due to flawed management or execution.

Higgins also sees promise in AI for manufacturers’ financial planning and forecasting, as well as on the production floor.

“Automation, AI, humanoids, robotics – that is very needed,” Higgins said.

Manufacturing CEOs recognize that AI investments come with some up-front costs, but they expect to see a return on investment within one to three years, per KPMG’s survey