Artificial intelligence (AI) and automation are transforming manufacturing operations, creating demand for engineers with skills extending beyond traditional mechanical and production expertise. However, workforce shortages and outdated training programs threaten to slow technology adoption across the industry.
In an interview with Machine Design, John Kraus, vice president of operations at Jabil, discusses the changing skills required in AI-enabled factories. Citing Deloitte research, the article notes that approximately 40% of core advanced manufacturing skills change within five years, highlighting the need for continuous learning.
Kraus emphasizes that successful automation begins with simplifying, optimizing, and standardizing manufacturing processes. Without these foundations, even sophisticated AI systems may fail to deliver consistent results. Engineers must therefore understand not only manufacturing fundamentals but also software, hardware, controls, and design for automation.
AI is also shifting engineering responsibilities from reactive troubleshooting toward predictive, data-driven optimization. Technologies such as automated visual inspection, advanced analytics, and predictive manufacturing enable engineers to identify potential problems before they disrupt production. Consequently, data literacy is becoming as important as conventional engineering knowledge.
Addressing these challenges requires manufacturers to invest in workforce development rather than relying exclusively on educational institutions. Jabil maintains relationships with technical schools, trade schools, or universities at more than 30 U.S. manufacturing sites, providing equipment, curriculum support, mentorship, and practical training opportunities.
Kraus particularly values partnerships with smaller trade schools and community colleges because they can adapt curricula more quickly to changing industrial requirements.
Upskilling existing employees is equally important. Experienced engineers and technicians possess institutional knowledge that cannot simply be replaced by software. Combining their expertise with AI training helps organizations preserve operational knowledge while developing new capabilities.
Ultimately, Kraus argues that manufacturers must invest in people alongside technology. Engineers who combine manufacturing expertise, automation knowledge, analytical skills, and adaptability will be better prepared to design, operate, and improve increasingly autonomous factories.
