About a year and a half ago, a bike parts manufacturer near Minneapolis called Wolf Tooth Components started dabbling with AI. Co-owner Brendan Moore said the company thought it might be able to help doing research on the market for new products.
“We want to design a trinket ‘A,’” Moore said. “What’s the competitive landscape of trinket ‘A’ out in the world, and what does the broader internet think about product offerings, and where are the weaknesses?”
Moore said the tools did a good job. So the company started using AI to improve its website, and to help brainstorm names for new products. It’s also using AI to help automate some of the menial jobs real people used to have to do with its manufacturing software.
“If you think about an administrative task of a human doing 10 clicks, to just move material from here to here to here, so we know where it is in the manufacturing process — we just automated that,” Moore said.
Moore said some of that work used to take half a day. So now, his staff can use that time to focus on other stuff that requires an actual human brain.
“Developing supply chains for a new product,” Moore said. “Looking at costing, looking at even material certifications; all of these things that you have to do that are complex and require a lot of nuanced thinking.”
As a result, Moore said the company can develop more products, more quickly, at a better price.
“How much better, it totally depends on the product,” Moore said. “But, essentially, it’s going to be a better experience for our customers, and it’s going to be better for our business, because of the efficiencies we’re going to have.”
That is the definition of higher productivity: more output in less time. But while it’s easy to see AI’s impact on one firm, it’s not so easy to see
how it’s affecting the economy as a whole.