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. 

Food and drinkware manufacturer Stanley 1913 is tapping artificial intelligence software from Kinaxis to predict and prevent supply chain disruptions. 

By using Kinaxis’ Maestro platform, Stanley 1913 aims to identify supply chain hurdles in real-time and implement swift mitigation actions, according to an Oct. 28, 2024 press release from the technology company.

“We have explored the use of advanced predictive analytics through machine learning and artificial intelligence, allowing us to gain end-to-end supply chain visibility and enabling powerful scenario planning to facilitate sustainable growth,” Karthik Sivakumar, VP of supply chain and operations at Stanley 1913, said in the release.

Leveraging the supply chain solution will also help Stanley 1913 keep its “carbon footprint to a minimum,” Sivakumar added.

Kinaxis introduced the Maestro platform at its Kinexions 2024 event.

To break down supply chain planning silos, Maestro takes in data from a full supply chain ecosystem — including functions like procurement, production, planning and fulfillment — to provide a real-time view of a company’s supply chains, Kinaxis President and CEO John Sicard said during a Q2 earnings call in August 2024.

“Maestro is our AI-infused supply chain orchestration platform that provides full real-time transparency and agility across the entire supply chain, fusing together planning and execution and managing everything from multi-year planning horizons, down to the second factory execution and last mile delivery,” Sicard said on the call.

Widespread AI adoption is rapidly changing the workforce, and the manufacturing industry is no exception. 

These changes have sparked anxiety in many workers. More than four in 10 frontline workers fear AI technologies could replace their job in the next decade, according to a June 2024 Boston Consulting Group survey.

Generative AI is expected to significantly change half of all jobs, according to research by Cognizant and Oxford Economics. As a result, 9% of the current U.S. workforce could be displaced.

Such displacement fears could also cause more workers to leave their posts. A 2023 Gartner survey found that workers who fear AI will replace their jobs are 27% less likely to stay with their employer, potentially exacerbating the manufacturing workforce shortage. 

To avoid such concerns and ease worker anxiety, manufacturers integrating AI are taking proactive steps to ensure the rollout of the tech doesn’t significantly disrupt existing workflows so productivity is enhanced, not replaced, by AI.

Involving workers in the process

A key strategy in rolling out AI is involving workers in the process from the outset. 

“When workers feel they have a say in adopting new technology, they tend to engage more positively,” said Kate Field, global head of human and social sustainability at BSI. “Conversely, if it feels ‘forced’ on them, they may be more resistant.”

Freudenberg, a manufacturer of household, automotive and other products, has involved its team early in tech integration through tasks such as data collection and consultations to eliminate uncertainties and give workers a sense of ownership in the process, said Vishwanath Hegadekatte, senior manager of future technologies at Freudenberg North America.

“It is about keeping them in the loop from the beginning so they know what to expect and how it will improve their work environment,” Hegadekatte said. “People need to feel comfortable and confident with the technology if it is to work effectively.”

SmartSKN, a personalized skincare manufacturer, found it easier to implement this from day one as its entire production model is AI-based. 

“Our employees were hired specifically to operate AI robots, so there was no anxiety about being replaced by AI,” said Val Neicu, CEO of SmartSKN. “Our human employees and AI robots now work together as a cohesive team — the humans even named the robots and count them as part of the floor team.”

Training is vital to success

However, not all manufacturers have been AI-focused from the start, so many experience a learning curve while adopting new technology and upskilling workers to use it effectively. This training period can make or break successful AI adoption.

“Providing effective training is crucial — not just an initial session, but ongoing Q&A and refreshers,” said Field from BSI. “Designating some workers as ‘champions’ of the new technology, with additional training, can also be highly effective." 

Freudenberg takes this a step further by offering workers an inner look into just how the AI works. 

“We’re demonstrating what systems we’re using, what software is being implemented and really giving them that insight into the back end so AI isn’t a scary unknown,” Hegadekatte said.

The company uses both external AI tools like the Microsoft CoPilot and internally developed AI models specifically tailored to address unique challenges at Freudenberg. These internal tools can be particularly crucial, as external resources to learn may not be available considering the proprietary nature of the software, Hegadekatte added.

Along with ongoing training, maintaining open communication throughout the process can ensure a smooth transition.

“Communication is key, we’ve found,” Hegadekatte said. “We have direct conversations with employees to let them know our exact intention for using AI (optimizing processes) and how we plan on using it. We involve them in the process, so these changes are coming slowly and with their full knowledge.”

SmartSKN also prioritizes transparency and communication when introducing AI. 

“Creating an open environment where team members can ask questions and provide feedback helps ease concerns and encourages adoption,” Neicu said.

Tackling persistent fears

Still, sudden change can overwhelm factory workers already fearing AI replacement. To ease the transition, many manufacturers should adopt AI gradually, one process at a time, ensuring both decision-makers and workers feel confident in the new workflow, said Praveen Rao, global head of manufacturing solutions at Google Cloud, which offers AI-driven manufacturing software solutions.

“Choosing technologies that integrate with existing systems and workflows reduces friction, while providing ongoing support and resources empowers employees to troubleshoot issues and optimize their use of the new tools,” Rao said.

Companies should then begin with a small-scale pilot to demonstrate value and gather feedback prior to a full rollout,” Rao added. 

Ultimately, it is an employer’s responsibility to ensure workers understand AI should help enhance their job, not replace it. 

“Most anxiety comes from the fact employees fear AI will displace their job but we are very transparent that AI is not meant to replace our workforce," Hegadekatte. "Rather, AI is a resource that can help us do our jobs more efficiently.”

Stellantis has been busy rolling out new artificial intelligence-enabled technologies on factory floors in recent months, one of many manufacturers experimenting with AI as a way to boost production speed and ease workers' physical labor. 

In September 2024, the automaker hosted its annual Factory Booster Day, bringing together technology startups and suppliers with proposals for Stellantis' manufacturing team. The annual event, now in its ninth year, is one of the key ways the company taps new potential technologies to bring into its factories. 

Anna Valeria Anllo, head of innovation for vehicle process engineering at Stellantis, said the company prioritizes technologies that enable them to improve plant efficiency and product quality, as well as cut costs. 

At the 2024 factory day, Anllo said Stellantis was particularly interested in quality control and energy management. 

"How can we help our plants and our factories and associates do better, be better, have better quality, and cut costs?" Anllo said.

Robot guidance tools help boost factory accuracy

In recent months, Stellantis rolled out a robot guidance tool from France-based startup Inbolt that uses 3D-vision systems to help robots adjust their trajectory and operations to avoid potential conflicts or impacts mid-manufacturing process. 

Inbolt's technology has been installed at multiple Stellantis powertrain factories thus far, such as in the automaker's Szentgotthárd, Hungary, factory.

The guiding tech, chosen from the 2021 Factory Booster Day, is being used there to help autonomous mobile robots pick cylinder heads from pallets and load them onto the production line. The Inbolt technology locates each cylinder head, realigns the robot’s trajectory and ensures correct pick-and-place operations onto the production line, according to Inbolt. 

Anllo said Stellantis is hoping to scale Inbolt's technology across 20 or 30 other plants around the globe. The automaker looks for use cases for technologies like Inbolt's in other aspects of its factories, including body shops and paint shops, she added. 

When evaluating a new tech program for factories, Anllo said the company analyzes the cost of integration, its potential cost savings and the time needed to roll out the product. Once finished with that process, research and development teams can move forward with a proof of concept that can be reviewed by plant managers for approval. Stellantis aims for projects to reach their first proof of concept within one to two years. 

Another AI-enabled technology that Stellantis has rolled out in recent months are autonomous wheels from Norway-based startup wheel.me, which convert current carts and dollies into AMRs. The tech was first integrated at Stellantis' Sterling Heights, Michigan, plant, after being chosen from the automaker's 2022 Factory Booster Day. 

"We are in the process of looking at different locations where we can also install this," Anllo said.

One of wheel.me's advantages for integration is that the technology didn't require any adaptions to the shopfloor layout, Anllo said. This more seamless integration is a factor in how Stellantis chooses experimental process technology, as it helps lower upfront costs. 

"We take innovation seriously, we are really about transforming, moving forward, making things better for associates, improving quality and being more cost efficient," Anllo said.

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.

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:

• Seismic shifts in IT infrastructure could trigger a chip shortage over the next several years, according to Bain & Company’s fifth annual global technology report, published in September 2024.
• The management consulting firm expects artificial intelligence workloads to grow 25% to 35% annually over the next several years, pushing the market for AI-related hardware and software to between $780 billion and $990 billion by 2027.
• Demand for AI components could grow 30% or more by next year, outpacing current production capacity. “If data center demand for current-generation GPUs were to double by 2026, not only would suppliers of key components need to increase their output, but makers of chip packaging components would need to nearly triple their production capacity to keep up with demand,” the report said.

Dive Insight:

As enterprises move AI plans forward, the technology is reshaping infrastructure on every level, from tiny microprocessors to massive data centers. The software market, too, has felt the impact, with major vendors like Microsoft, SAP and Salesforce racing to infuse CRMs, ERPs and office productivity tools with large language model capabilities.

Bigger models and larger data centers coupled with a proliferation of enterprise applications could push the overall AI market to nearly $1 trillion in just three years, up from under $200 billion in 2023, according to Bain. The firm expects AI hardware and software to experience a 40% to 55% growth spike each year through 2027.

“We have a genuine surge in demand and, within that demand, there's a meaningful mix change towards parallel compute and towards compute with advanced packaging,” David Crawford, chairman of Bain’s global technology practice and lead author of the report, told sister publication CIO Dive.

While downstream effects on the enterprise are hard to foretell, Bain has already detected constraints on the GPU supply chain, according to Crawford.

“We have had our clients complaining about access to components — particularly to GPUs — for at least 12 to 18 months,” Crawford said.

Vendors have long limited access to GPUs amid high demand. “It's become a strategic advantage if you do have access to the amount and number that you want.”

As data and application modernization drives up enterprise cloud spend, IT and finance executives are grappling with budget constraints. The AI boom has made rising cloud bills unmanageable for most companies, according to a recent Tangoe report.

The immediate costs are reflected in an acceleration of multibillion-dollar cloud infrastructure investments by hyperscalers AWS, Microsoft and Google Cloud — and by record lows in commercial data center vacancy rates. Capital spending on cloud facilities is expected to grow by 36% year over year in 2024, per the Bain report.

At the data-center level, those investments face electrical grid capacity bottlenecks and a potential shortage of specialized workers, according to Bain’s analysis. “Utilities are already fielding requests from hyperscaler customers to significantly expand electrical capacity over the next five years,” the firm said.