Frontline A.I. - A Guide for Manufacturers
Retention and recruitment in the frontline workforce is a challenge for US manufacturers, both large and small. Some firms are turning to automation to solve these problems, but initial research shows that deploying automation without also making job quality improvements may do more harm than good.
For manufacturers that are considering integrating automation, be it artificial intelligence (AI) or otherwise, into their operations, the recommendations presented here provide guidance. They are based on interviews with experts, research, and best practices from leading firms in the field on how to deploy automation in a way that raises job quality, improves retention and recruitment, and protects their bottom line.
Automation deployment in manufacturing can lead to deskilling and higher churn, intensifying retention challenges for the industry and contributing to institutional brain drain.
Manufacturers are turning to AI tools to increase the productivity of plants (reducing downtime, reducing waste, increasing capacity per line) while reducing the amount of human capital (both number of workers and hours worked) required to perform certain tasks. The tax structure in the US incentivizes automation, since taxes are higher for labor and lower for capital. Severe production disruptions driven in part by the COVID-19 pandemic have created a very strong incentive to automate work. A study by Oxford Economics estimates that 20 million manufacturing jobs will be automated by 2030. Given the industry’s challenging history with employee retention and recruiting, some companies are looking at automation as a silver bullet for all of their workforce challenges.
