This originally appeared in Smart Industry.
We’ve all seen the AI headlines. How to apply its wide-ranging capabilities to business is top of mind for leaders across every industry—particularly in manufacturing.
Leaders in the industry aren’t quite ready to fully commit to the technology but still understand the underlying value. In fact, 57% of manufacturing companies are still experimenting with AI technology to identify how best it can be applied and managed. With that said, nearly all respondents (96%) believe that AI investment by companies in the manufacturing industry will increase in 2023.
With a vast amount of industrial available data that’s difficult to sort through and determine how to use, there’s an opportunity to leverage AI to help us expand our thinking. In the case of manufacturing, there’s not a single element of the industry that won’t be affected and improved by generative AI—and it could actually humanize the industry at the same time.
AI is bound to have a profound impact on the manufacturing industry—larger than mobile phones or cloud technology—from the value chain to day-to-day operations to the technology being used. The examples cited below are along the value chain—product design and thought sales. There are also “back office” functions that AI will support such as finance and IT.
The manufacturing industry is leveraging AI in several ways:
Generative AI will likely have two major implications for the manufacturing workforce: It will first increase the productivity of specific jobs and it will free up time to create new ones. Jobs that include repetitive tasks and minimal training or education (i.e. assembly line work) will likely be replaced by AI, which can perform those same tasks more efficiently and accurately than humans.
We recently partnered with a leading beverage manufacturer to keep up with increasing customer demand for their hard seltzers. By implementing a roadmap for them to become a digital shopfloor—enabling data-driven manufacturing operations—the company is now projecting a 5-10% labor productivity improvement and an 18% capacity-utilization increase, which will lead to $36 million revenue annually over five years.
As AI and automation take over routine tasks, there will be a growing demand for highly skilled jobs such as engineers, data scientists, and software developers to develop, maintain, and improve AI systems. New jobs will be created and some existing jobs in manufacturing will evolve as workers adapt to new technologies that require human skills like creativity, problem-solving, and empathy.
While many leaders are itching to get into AI, it’s important to consider two initial steps: ground yourself in what AI is (and isn’t) and start small.
Ensuring you and the other key stakeholders within an organization understand the technology and what it can and cannot do is key to kicking off an AI program. Having that knowledge, and setting clear goals and metrics to measure progress sets up the project for success and continual optimization along the way. Testing and learning are key to creating a functional program that will deliver real business value.