The Rise of AI in Manufacturing

Manufacturers across the U.S. are leaning into artificial intelligence as a pivotal aspect of business growth. It’s not surprising then that 87% of those surveyed in a Deloitte report on AI in manufacturing have adopted the technology or plan to do so in the next two years. 

However, a key challenge to implementing AI is training a workforce to leverage the technology, especially factory-level employees. A 2023 Boston Consulting Group study found that only 14% of frontline workers say they have received AI upskilling, compared to 44% of leaders.

“While approximately 70% of the current US workforce is concentrated in frontline roles that are seeing an increase in the demand for AI proficiency, AI skilling offerings to date have been almost exclusively geared toward non-frontline populations including roles like data scientists, executives, and engineers,” said Matthew Daniel, senior principal for talent strategy at Guild, a workforce training organization.

As more manufacturers navigate upskilling workers to use AI in everything from R&D to assembly and maintenance needs on the factory floor, here’s how some companies are tackling the workforce training challenge. 

Online programs can offer workers flexible training

Offering training that can help workers upskill to leverage AI in their daily functions is a key way companies can ease anxieties in workers around the technology replacing their jobs, Daniel said. Doing so could be key for companies, as 36% of respondents in BCG’s study believe their job could be eliminated by AI.

“Organizations should proactively create avenues for employees to upskill with AI and reframe the narrative to not fear AI and the unknown but to showcase what's possible — their workforce leading, adapting, and adding unprecedented value.”

Workforce training organization Guild offers bundled AI training programs focused on related topics, such as AI literacy and ethics, workplace applications, technical programming and executing AI-driven strategies. 

The programs are fully online and offer a flexible schedule so frontline workers can participate without disrupting work. Online training options that fit into the workflow of employees can make the process easier for individuals to tackle.

“It's not just about adapting to AI — it's about empowering the frontline workforce to thrive alongside it and giving them the tools and resources to do so,” Daniel said. 

Leveraging digital tools to upskill workers

Upskilling is important for workers that may not be familiar with AI or other digital tools, said Bill Rokos, chief technology officer at Parsec Automation Corp., an organization working with more than 11,000 manufacturing companies to integrate AI into their workflows.

“For many floor workers, powerful tools like the Internet of Things, automation and digitalization are brand-new concepts,” Rokos said.

Augmented reality, virtual reality and other digital resources can offer helpful simulation platforms for workers to practice these new skills. 

“Using augmented reality and virtual reality, manufacturing leaders can provide workers with on-the-job training and enable them to learn new skills in a safe and controlled environment,” Rokos said.

That’s exactly what digital solutions firm UST is doing. The company is using the metaverse as a virtual training environment with gamified learning to teach how to use AI for tasks like data analysis, predictive maintenance, quality control and optimization. 

“We simulate real-world scenarios and problem statements in a virtual world and get workers to solve complex problems with a higher level of retention due to experiential learning,” said Ramya Kannan, vice president and industry head of manufacturing at UST. “The metaverse provides an interactive and immersive learning experience.”

This kind of learning also allows for easy collaboration and real-time communication between multiple workers and trainers.

“We can share feedback, add learnings from mistakes back into the training program and constantly improve the experience,” Kannan said.

Manufacturers are also using “AI-powered predictive maintenance, which analyzes equipment sensor data to forecast maintenance needs to reduce operational downtime, improve equipment reliability, and enhance worker productivity,” Rokos said. 

Many of these training programs, whether online or in-person, focus on safety and control, ensuring workers know how to protect company data as operations become more connected, according to a May 2024 report from the National Association of Manufacturers. 

”The most effective AI models are humancentered, allowing them to learn and unlearn, continuously improving to meet the needs of their human operators,” the report said. 

The Department of Commerce will open a research and development competition — offering up to $1.6 billion in CHIPS and Science Act funding — to establish and spur domestic capacity for semiconductor advanced packaging, the agency announced July 9, 2024. 

The notice mentioned an increased need to improve semiconductor advanced packaging. 

In the past, the semiconductor industry has addressed chip performance needs by increasing the number and density of transistors on a chip, a process known as miniaturization.

“However, the previous pace of miniaturization, as expressed by Moore’s Law, is slowing and cannot alone provide the performance improvements needed for emerging microelectronics technologies,” according to the notice.

Emerging technologies like high performance computing and low power electronics, which are needed to drive artificial intelligence, are driving the push for innovation.

The funding will be split into multiple awards of up to $150 million with a performance period of up to 5 years per award, according to the notice.

Once the notice of funding is published, concept papers are due approximately 60 days after.

“Advanced packaging allows manufacturers to make improvements in all aspects of system performance and function and to shorten time to market,” the release stated.

The department mentioned how packaging can reduce physical footprint, lower power, decreased costs and increased chiplet reuse.

The funding focuses on five R&D areas, according to the notice:

• Equipment, tools, processes and process integration
• Power delivery and thermal management
• Connector technology, including photonics and radio frequency
• Chiplets ecosystem
• Co-design or electronic design automation

In addition to the R&D areas, the funding is expected to include opportunities for prototyping in areas such as high-performance computing and low-power systems needed for AI, the notice stated.

The new competition is a much higher price point than a similar CHIPS funding opportunity announced in February 2024 when the White House unveiled $300 million for research and development projects related to semiconductor packaging. 

The Biden administration has also been investing in semiconductor advanced packaging companies. In May 2024, $75 million went to glass substrate manufacturer Absolics for its Covington, Georgia, facility to develop substrates for semiconductor advanced packaging. 

Samsung also scored big, getting $6.4 billion in April 2024 for four different chip plant developments — one being a packaging plant in Taylor, Texas. The plant will manufacture 3D high-bandwidth memory and 2.5D packaging, key for AI applications.

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By West Monroe

Despite years of discussion, the manufacturing industry is still far from delivering on the vision of Industry 4.0. Although the value of Industry 4.0 has been highlighted for over 20 years, companies continue to face challenges in driving progress and, for some, even getting started.

There’s a natural tendency to want to have a cohesive plan or strategy for moving ahead. In the MLC’s recent study, "Manufacturers Go All-In on AI," 42% of manufacturing executives cited the lack of a comprehensive M4.0 strategy as the top challenge to adopting and using those technologies. Another 37% said the biggest hurdle is their ability to assess the cost/benefit of deployment.

Navigating through the wide array of technologies to develop an M4.0 strategy is challenging. Thinking too broadly can lead to analysis paralysis; thinking too narrowly can make it difficult to demonstrate a level of ROI needed to justify investment. So, how can manufacturers begin to effectively implement Industry 4.0 technologies and make meaningful progress?

Start simple: Connect

The first step is to connect. This means integrating sensors, devices and machines to collect data. Start with a pilot project that focuses on a specific process or piece of equipment. By connecting these elements, manufacturers can begin to gather data that provides insights into operations. This data forms the foundation upon which all subsequent steps are built.

For example, consider a production line where downtime is a significant issue. Installing sensors to monitor equipment performance can provide real-time data on operating conditions, helping to identify patterns or anomalies that may lead to failures. By starting small and focusing on specific issues, manufacturers can quickly see the benefits of connectivity and build confidence in their Industry 4.0 journey.

Analyze: Turning data into insights

Once data is being collected, the next step is to analyze it. This involves using advanced analytics, including artificial intelligence and machine learning, to interpret the data and generate actionable insights. The key here is to focus on specific, measurable outcomes.

For instance, predictive maintenance can be a game-changer. By analyzing data from equipment sensors, manufacturers can predict when a machine is likely to fail and perform maintenance before it breaks down. This not only reduces downtime but also extends the life of the equipment, leading to cost savings and improved efficiency.

Improve: Implement changes

With insights in hand, the next step is to implement changes. This could mean adjusting processes, scheduling maintenance, or retraining staff based on the data analysis. The goal is continuous improvement, making incremental changes that collectively lead to significant advancements.

Take, for example, a manufacturer that identifies a bottleneck in their production line through data analysis. By making targeted adjustments, such as reallocating resources or fine-tuning machine settings, they can improve throughput and reduce delays. The key is to be flexible and willing to iterate based on what the data reveals.

Rinse and repeat

Industry 4.0 implementation is not a one-time effort. It requires a cycle of continuous improvement: connect, analyze, improve and then repeat the process. Each iteration provides new data and insights, enabling manufacturers to refine their strategies and make more informed decisions.

The rinse-and-repeat approach ensures that manufacturers are always evolving, adapting to new challenges and opportunities as they arise. This iterative process helps build a culture of continuous improvement, where data-driven decision-making becomes the norm.

Overcoming common challenges

Despite the clear benefits, manufacturers often face several challenges in implementing Industry 4.0. As mentioned earlier, a significant barrier is the lack of a comprehensive strategy. To overcome this, companies should start with small, manageable projects that demonstrate quick wins. These successes can then be scaled up and used to build a broader strategy over time.

Another common challenge is the difficulty in assessing the cost/benefit of deployment. Manufacturers should focus on projects with clear, measurable outcomes. For instance, improving machine uptime or reducing energy consumption can provide tangible ROI that justifies further investment.

Finally, cultural resistance can be a hurdle. Change is always difficult, and employees may be hesitant to adopt new technologies. To address this, manufacturers should invest in training and change management programs to help staff understand the benefits of Industry 4.0 and how it will positively impact their work.

Conclusion

Implementing Industry 4.0 in manufacturing is a journey, not a destination. By taking a practical approach—starting with connectivity, analyzing data, making improvements and iterating—manufacturers can make meaningful progress and stay competitive in an increasingly digital world. The key is to start small, demonstrate value, and build on success. With a clear, data-driven strategy, the vision of Industry 4.0 can become a reality.

The global talent trends Mercer researchers have highlighted are the ones that have already made headlines: Inflation’s strain on workers’ wallets, their desire for more pay to keep up with the cost of living and the continued impact of AI. Employers and employees also still spar over new work models. 

But, in a Feb. 29, 2024 webinar cracking open the report, Mercer’s Global Talent Advisory Leader Kate Bravery noted, “We've certainly got more uncertainty on the horizon. But at the same time, we've also seen greater convergence in views this year across generations and geographies.”

Here are a few key findings from Mercer’s report, which polled 12,200 HR professionals, as well as executives, employees and investors.

Artificial intelligence demands different human talent

A lot of the employers polled mentioned looking at AI as a matter of product integration. But generative AI is becoming a part of the fabric of work in general.

Mercer noted 20 priorities for HR leaders in 2024; no. 5 was “Redesigning work to incorporate AI and automation.” This means 40% of HR professionals polled by Mercer have AI workflows on their people agenda. (Also in the top 10 HR pro priorities were enhancing EX, improved health benefits, workforce planning and people analytics.)

In covering the report, Bravery noted the significance of the AI at work conversation. Referencing Mercer’s approach to researching humans in a “machine-augmented world,” Bravery said, “We know that it's humans [who] will effectively unlock AI’s real potential.” 

More than 50% of executives polled by Mercer expressed their belief that their businesses won’t survive past 2030 without “embracing AI at scale.” 

What are gold standard C-suites doing to successfully embrace AI? They prioritize human-centric productivity, foster trust, ensure equitable work practice and lean into a “digitally-infused future,” the report found.

“As risks become more connected and less predictable, [organizations that outpace their competitors] understand that a new level of risk awareness and mitigation is essential to building a ready and resilient workforce,” researchers said in the report.

As new work models emerge, EX should be re-examined

“I don't think you'll be surprised, but HR’s top concerns this year are rising labor costs, and ensuring new work models — flex, gig, short-term work models — are really delivering long-term value,” Bravery said. 

A whopping 98% of employers are planning “work design changes” for 2024. The main goal is to tweak workflow to increase productivity; Mercer identified the concept of fixed roles, flex roles or “agile roles that benefit from skills-based planning and credentialing.”

Hybrid work continued to reign as a key factor in productivity. “While it may seem that employers have finalized return-to-office plans and codified their post-pandemic flexible working policies, in fact 41% are planning further changes this year,” researchers said in the report.

Mercer broke down flexible work into “six dimensions:”

• Where, as in location and infrastructure;
• When, as in hours and scheduling;
• What, as in job content and sharing;
• Who, as in alternative workforce and automation;
• How, as in scaling and technology; and
• Why, as in mission and purpose.

The idea of value was persistent across the webinar. For one, more workers said they were sticking with their employer this year — which is poignant, given that panelists acknowledged the Great Resignation and how it changed the work landscape.

Bravery also highlighted, “More employees shared that their needs are not being met — especially older workers and Gen Z. We've got work to do there.” 

Engagement will be an area that stakeholders “need to watch out for this year,” across the board, Bravery said.

Dive Brief:

• Rockwell Automation will use Nvidia’s artificial intelligence software in its autonomous mobile robots, the two companies announced June 3, 2024. 
• The automation company will integrate Nvidia's AI robot development platform, dubbed Isaac, into Rockwell's Otto autonomous mobile robots, meant for use in manufacturing facilities.
• The project is part of an ongoing collaboration between the two companies to expand the use of AI in manufacturing. In March 2024, Nvidia and Rockwell announced they were working together to create digital twin software that incorporated the AI chipmaker's Omniverse cloud platform.

Dive Insight:

Rockwell is pushing to bring AI to more of its products as a way to better tap into customer needs. 

The company is also working with Microsoft to offer new AI-powered data solutions as it seeks to further its AI portfolio. Rockwell expanded its partnership with Microsoft in October 2023 to add the tech giant's OpenAI software to its industrial automation cloud platform.

“By combining Microsoft’s AI capabilities and trusted cloud platform with Rockwell’s industrial automation solutions, manufacturers will have the tools they need to speed up these objectives and create smart factories of the future,” Dominik Wee, corporate VP of manufacturing and mobility at Microsoft, said in an April 2024 statement. 

The work with both Nvidia and Microsoft is part of Rockwell’s strategy to focus on “specific customer use cases, especially those that will benefit from simulation and simplification using artificial intelligence,” Chairman and CEO Blake Moret said on a May 7, 2024 earnings call. 

“These partners recognize that machines and manufacturing processes represent an enormous largely untapped source of data,” Moret said. “They also know we have the manufacturing domain expertise to select the best use cases for their technology.”

Rockwell acquired the Otto bot as part of its acquisition of Clearpath Robotics in October 2023. The autonomous mobile robot is now part of Rockwell’s manufacturing portfolio, with customers including GE Aerospace, Cober Solutions and Mauser Packaging Solutions, according to its website. 

Companies have been using autonomous mobile robots for several years to boost warehouse efficiency and lower labor needs — Amazon and DHL Supply Chain both deploy the tech in their facilities. Now, however, more companies are integrating AI into robotics technology to boost its abilities.  

Nvidia, for example, boasts that more than a dozen robotics industry leaders are now using its Isaac platform, including BYD Electronics and Siemens. Siemens, which has multiple collaborations with Nvidia, is using the software to integrate vision AI into its industrial robotic ecosystem. Nvidia and Siemens plan to roll out new capabilities related to the tech later in 2024.

Mentions of AI and ChatGPT are proliferating on the dark web. 

The IBM X-Force Threat Intelligence Index 2024 report identified over 800,000 references to the emerging technology on illicit and dark web forums in 2023. The real threat, according to X-Force, will emerge when AI enterprise adoption matures.

Right now, there are simply too many AI systems at play. 

Though OpenAI's ChatGPT has become synonymous with generative AI, a competition is afoot to determine which large language models are the most effective and transparent. In a test of 10 popular AI models, Google's Gemini outpaced competitors, followed by OpenAI's GPT-4 and Meta's Llama 2, according to April 2024 research from Vero AI. The test measures the visibility, integrity, optimization, legislative preparedness, effectiveness and transparency of models. 

Businesses are leaning on their cloud and software providers to facilitate AI adoption. Coca-Cola has a $1.1 billion partnership with Microsoft to use its cloud and generative AI services. And General Mills used Google's PaLM 2 model to deploy a private generative AI tool to its employees. 

To this point, cybercriminals are focused on ransomware, business email compromise and cryptojacking, X-Force found. But the threat intelligence firm expects that when a single AI technology reaches 50% market share — or when there are no more than 3 primary AI offerings — the cybercrime ecosystem will start developing tools and attacks to go after AI. 

AI can boost already dominant attack campaigns

In February 2024, Microsoft reported that hackers from North Korea, Iran and Russia were using Open AI to mount cybersecurity attacks, which the company then said they shut down. 

That’s not surprising, Melissa Ruzzi, director of artificial intelligence at AppOmni, said. Generative AI can turbo boost social engineering and phishing attacks. 

Threat actors can tailor sophisticated phishing attacks by scraping data about users from all corners of the internet, matching pieces of information that might seem similar to know more about a person. For example, they could identify an Instagram handle that isn’t exactly a person’s real name. 

This isn’t just about sending spoof emails either, Ruzzi said. AI can be used to pretend to be a real person applying for a job at a company, which includes a nicely written cover letter and a PDF resume. 

Hackers can also use AI to determine how long a position has been open “so they can see how desperate you are,” she said. 

Threat actors can use generative AI to crack passwords, increase the launch volume of previously successful attacks, and get around cybersecurity defenses, she added. The sky is, unfortunately, the limit.

AI could be used to bend the truth

Generative AI is also being used to fuel disinformation and misinformation campaigns, said Adam Meyers, CrowdStrike’s senior vice president of counter adversary operations. In the Crowdstrike 2024 Global Threat Report, the company tracked AI images related to the Israel and Hamas war. 

While the faked images are relatively easy to spot — in some faked images, people having six fingers, for example — it’s still being used, and most likely will continue to be refined through 2024 to disrupt elections. According to Crowdstrike’s research, more than 42% of the global population will be voting in presidential, parliamentary and/or general elections in 2024.

“We’re already seeing the use of generative AI deep fakes for misinformation,” Meyers said, including fake President Biden robocalls that were deployed during the recent New Hampshire primaries. 

That doesn’t mean corporate cybersecurity professionals are off the hook, because attacks won’t just be contained in the political arena. 

If someone can make a deep fake of a country president, said Meyers, they can also potentially make a deep fake of a company president. A malicious actor could use that deep fake on a Zoom call to get employees to do things like make money transfers, and time it to when the hackers know, via social engineering, that the president will be unavailable at that time.

“The volume of attacks that they can create and the quality of the attacks is really starting to get kind of scary,” Ruzzi said.

Dive Brief:

• Mercedes-Benz and robotics company Apptronik have agreed to deploy humanoid robots at the automaker’s manufacturing facilities, Apptronik announced March 15.
• As part of the agreement, both companies will study the potential use cases for Apollo humanoid robots in logistics, such as delivering parts to assembly line workers.
• The robots can help automate tasks that are physically demanding, repetitive or hazardous for humans. They can also address labor shortages by performing less desirable tasks.

Dive Insight:

Advances in robotics technology can help make workplaces safer for humans and increase efficiency. In January 2024, BMW announced a similar project at its manufacturing facilities in South Carolina. Tesla is also considering deploying its AI-powered, humanoid “Tesla Bot” in its factories to work alongside humans.

"Mercedes plans to use robotics and Apollo for automating some low skill, physically challenging, manual labor – a model use case which we'll see other organizations replicate in the months and years to come,” Apollo CEO Jeff Cardenas said in the press release.

Apptronik was founded in 2016. The company spun out of the Human Centered Robotics Lab at the University of Texas at Austin. The humanoid Apollo robot resulted from Apptronik’s experience building over 10 previous robots, including the Valkyrie robot for NASA. 

The Apollo robot is around the size of a human worker, standing 5 foot 8 inches tall and weighing 160 pounds. It can lift objects weighing up to 55 pounds and work alongside humans in industrial settings, performing more physically demanding tasks in factories. The robot can operate with its onboard battery pack for up to four hours.

“This is a new frontier and we want to understand the potential both for robotics and automotive manufacturing to fill labor gaps in areas such as low skill, repetitive and physically demanding work and to free up our highly skilled team members on the line to build the world's most desirable cars,” Jörg Burzer, who’s in charge of the Production, Quality & Supply Chain Management division, said in the press release.

Dive Brief:

• Employers should implement artificial intelligence technologies transparently and with the “genuine input” of workers and their representatives, the U.S. Department of Labor said in a guidance document published May 16, 2024.
• DOL included these items in a set of eight “AI Principles for Developers and Employers.” The agency said the guidance would create a road map for balancing AI’s potential benefits for businesses and workers while protecting workers from potential harm.
• DOL specifically recommended that AI be designed, developed and trained in a way that protects workers and that employers have “clear governance systems, procedures, human oversight, and evaluation processes” for workplace AI. The agency also cautioned that AI should not violate workers’ rights, including the right to organize, and that any data collected, used or created by AI systems be limited in scope and location.

Dive Insight:

The guidance document is a direct follow-up to President Joe Biden’s 2023 executive order directing federal agencies to develop AI “principles and best practices” specifically targeted at mitigating potential harms and maximizing benefits for workers. DOL confirmed the link between the two documents in a press release.

“Workers must be at the heart of our nation’s approach to AI technology development and use,” Acting Secretary of Labor Julie Su said in the release. “These principles announced today reflect the Biden-Harris administration’s belief that, in addition to complying with existing laws, artificial intelligence should also enhance the quality of work and life for all workers.”

The guidance drew, at least in part, from the input of labor unions. In an email to sister publication HR Dive, the Retail, Wholesale and Department Store Union said it “contributed to the considerations” of DOL’s principles and said the guidance provides “a useful framework for understanding AI and the scope of its impact on working people and guiding solutions for reducing its impact.”

DOL said it also collected input from workers, researchers, academics, employers and developers through public listening sessions in advance of issuing the guidance.

A May 2024 Littler Mendelson survey of U.S. employers showed that while a sizable share used generative AI for HR processes, an almost equal number had not done so. Compliance risks were a key concern for respondents, the law firm said.

While most employers in Littler’s survey said they were not concerned about the potential for AI to displace workers, other organizations — including the Society for Human Resource Management — have cautioned that AI could affect myriad workforce priorities, head counts included.

As of May 2024, regulation of AI in the employment context has come courtesy of several state and local hiring laws as well as a few federal efforts. In May 2024, DOL issued separate guidance detailing AI’s potential interaction with laws such as the Family and Medical Leave Act and the Fair Labor Standards Act. In 2022, the Biden administration published a blueprint for addressing bias and discrimination by automated technologies including AI.