30,000 examples of how Ikea works with AI

“It’s a good sign,” he adds. “It means people want to get involved and invest in their development, and that’s important.” Training in-house is a strategy that Marzoni clearly believes in since expecting people who are experts in a certain area to step in and make things work with the company’s processes right away isn’t realistic at the level they need. Also, AI in particular is a discipline that works in a very specific way. 

“To build AI capabilities that can help employees in a certain processes can be as important as a data scientist or a machine learning engineer being the expert and building the solution,” he says. “AI is very much about data, and data is largely in people’s heads, so we must invest in developing the people — the experts — who become important actors when it comes to how we build solutions.”

Order of data

Having your data in order is the cornerstone to moving forward with AI. “The ecosystem is constantly producing more data, so it’s impossible for everything to be in perfect order all the time; it’s something you have to constantly work at. And it’s important to have your data in order even if you don’t know what you’re going to use it for. It’s very easy to do relevant things with AI if you have a handle on your data. So far, Ikea has come a long way with its data management concerning supply chain and warehousing, but when it comes to customer experience, however, there’s more to do, says Marzoni. “We can improve how we collect data about the customer process,” he says.