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A Perfect Storm: The Automated Manufacturing Skills Crisis

The workforce crisis faced by the manufacturing sector really has no precedent. It is estimated that the manufacturing industry will need around 3.8 million new employees between 2024 and 2033. And nearly half of these positions—1.9 million jobs—could remain unfilled if manufacturers can’t address current skill and applicant gaps.

Demographics are partly to blame: up to 25% of the manufacturing workforce is set to retire in the next decade, taking irreplaceable knowledge with them. But the industry is also shifting rapidly with the arrival of artificial intelligence, predictive analytics, and collaborative robotics, and only about 30% of today’s frontline manufacturing workers have skills aligned to these evolving needs.

“The automation landscape is shifting faster than educational institutions can adapt,” explains Eclipse Automation’s Chief Human Resources Officer Michelle Sangster. “We’re seeing millwrights with decades of experience suddenly needing to understand complex control systems and data analytics. Traditional trades are being redefined before our eyes.”
To give one historical example: In the 1980s, the graphic design industry also faced fears about automation. Designers who adapted to digital tools thrived; those who resisted change were left behind. Manufacturing today is at a similar inflection point, where it too needs workers who see automation as an opportunity rather than a threat.”

Successful workforce development must balance technical training with fostering adaptability, critical thinking, and problem-solving capabilities. Workers need both the skills to operate today’s automated manufacturing systems and the mindset to evolve as those systems inevitably change.

Information and complexity are the biggest obstacles

In part, you can blame poor communication. Success stories like these aren’t as widely known as they should be. The lack of familiarity with the technologies can also be daunting, even for veteran engineers: the transition to AI can feel like a much bigger leap than the incremental improvements brought by earlier waves of innovation.

The perceived complexity might be an even bigger factor. In a recent survey, 65% of automation engineers reported dealing with long setup times for product changes of all sorts. The real problem, it turns out, may not necessarily be with AI, but with making changes in general.

This is why rapid reconfiguration is so crucial to the future of AI-enabled automation. One of the great promises of AI—besides efficiency and uptime—is flexibility. Especially as motor vehicles themselves become more advanced, being able to rapidly reconfigure a factory to accommodate improvements is critical. But for many factories, throwing AI into the mix adds yet another layer of complexity, making it appear less nimble, not more.

Educational Institutions Behind the Automation Curve

Traditional universities, colleges, and trade schools—the institutions we’ve long relied on to prepare workers for industrial careers—are struggling to keep pace with technological change.

“A growing number of universities do offer AI courses,” notes Sangster, “but with technology applications rapidly developing, it’s challenging for them to stay current. This often leaves a skills gap, where they have trouble consistently meeting the needs of industry.”

One result is that enrollment in traditional three- and four-year programs in automation has dropped significantly in recent years, while demand for one- and two-year certificates has risen. “Many colleges have increased their certificate and two-year diploma programs,” notes John Tielemans, Program Coordinator of Robotics & Automation at Conestoga College in Ontario.

This educational lag is a particular problem for manufacturers implementing custom automation solutions, which include collaborative robots, vision systems, and machine learning systems. “AI learns what you give it, so human capital remains crucial,” explains Sangster. The ability to analyze AI-generated data, apply critical thinking to automation outputs, and solve tangible problems within complex systems are increasingly valuable skills—skills that traditional educational paths aren’t consistently delivering.

Bridging the Gap: Innovative Approaches to Workforce Development

Forward-thinking manufacturers aren’t waiting for educational institutions to catch up—they’re creating their own solutions. Several approaches are showing particular promise:

1. Industry Partnerships

Manufacturers are forging direct partnerships with educational institutions to influence programming and create talent pipelines. These range from equipment donations and curriculum development to co-op programs that provide students with hands-on experience in automated environments.

Yaskawa Motoman, for example, have partnered with the Robotics and Advanced Manufacturing Technology Education Collaborative (RAMTEC) to develop STEM-aligned curriculum in Industry 4.0 technologies.

Here at Eclipse Automation, we’ve formed a partnership with Conestoga College to develop training programs that ensure students graduate with both theoretical knowledge and practical credentials in automation competencies.

“A key point in education in the technology fields is the requirement to stay current,” explains Tielemans. “One possible structure for micro-credentials would be a modular education. Students would tackle modules individually to build a diploma or degree. A diploma or degree would be issued upon completion of all required modules. In theory, this would be very efficient and desirable. In my experience, our program sees significant changes roughly every five years. Conestoga is working on similar program designs to attract enrollment and prepare students for the rapidly changing world.”

2. Internal Academies

With ready-made talent difficult to find, some manufacturers are establishing in-house training programs focused on specific automation skills. These often combine virtual learning with hands-on application, allowing workers to develop expertise while contributing to actual production.

“Eclipse Automation is excited to share that we have developed an in-house apprenticeship training program aimed at supporting both current and future apprentices across various disciplines”, says Jennifer Russell, Sr. Human Resources Business Partner. “This initiative is designed to bridge the gap between classroom learning and real-world application in the automation industry. By investing in this program, we are not only strengthening our workforce but also contributing to the development of the next generation of skilled professionals in automation”, added Jennifer

“We’re seeing significant ROI when companies invest in internal training,” says Sangster. “It’s not just technical skills—it’s developing a workforce that understands your specific automation infrastructure and manufacturing challenges.”

3. Experiential Learning

Looking to the near future, simulated factory environments are proving invaluable for workforce development. Companies like Emerson are investing in physical labs that allow workers to learn automation technologies through real-world experiences; others are using virtual reality to create immersive training scenarios.

It’s also likely that the most sought-after graduates from manufacturing automation programs will be those who get real-world experience as part of their training. “Technologists must be industry-ready, gain experience through project work, and complete a real-life project during their college education,” notes Michael Waldeck, Professor of Engineering, Technology & Trades at Conestoga College. “Our partnership with Eclipse Automation helps bridge this gap for students by providing bursaries and co-op opportunities to work on real-life projects.”

4. Alternative Pathways

As traditional four-year degrees show diminishing returns for certain manufacturing roles, alternatives like bootcamps, micro-certifications, and apprenticeships are gaining traction. These focused programs deliver specific automation skills in condensed timeframes, often with direct pathways to employment. Waldeck, however, emphasizes that while micro-credentials can be a viable option, they should not be the only path available.

“We’re beginning to hire and test for specific automation-related skills rather than traditional credentials,” says Sangster. “Someone with six months of intensive training in collaborative robotics might be more valuable than a candidate with an engineering degree but no hands-on automation experience.”

Rethinking Workforce Planning for the Automated Era