Closing the manufacturing skills gap with generative AI

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Manufacturers often tell us how workforce challenges affect their organizational productivity. If you feel this way, you are not alone. Every quarter, the U.S. National Association of Manufacturers, the trade association that consolidates manufacturer interests, polls CEOs on their primary business challenges. In the latest poll (2023 Fourth Quarter Manufacturers’ Outlook Survey), more than 71% of manufacturers cited the “inability to attract and retain a quality workforce”, more than any other issue, as the challenge most affecting their business. As the top concern for many years, it even has its own branding: “the manufacturing skills gap”. Simply put, 30-year manufacturing industry veterans are retiring, the next generation didn’t come in, and the current generation has different views and expectations, resulting in a net 20% attrition on the shop floor; a situation only exacerbated by the pandemic.

Manufacturers must constantly train new employees, and do so quickly, to maintain productivity in an era of high attrition rates; they must upskill or reskill existing employees to keep up with the pace of innovation and shifting skillset needs; and they must capture and institutionalize existing knowledge soon, or risk it being lost through the departure and retirement of domain experts (sometimes referred to as “the silver tsunami”). For multi-national enterprises, there are more challenges, as institutional knowledge may be entered in one language but need to be consumed in another language.