Of the services that Sparkbox.ai, an AI-centric retail planning platform, offers to customers, one seeing demand is for placing quick in-season reorders of products that are performing well.

But one yet to find users is its AI-powered demand forecasting, which predicts a product’s performance weeks into the future.

Brands are still sceptical about the validity of AI forecasts, Sparkbox co-founder Lindsay Fisher said, and to make decisions with AI about their initial buys, they need to have clear, quantifiable assumptions to base their models on. Many, however, still rely on gut feeling.

“With the initial-buy planning, there’s a lot more opinion involved, so maybe AI isn’t as useful in that respect,” said Alex Ure, head of merchandising for Jaded London, which scored a hit earlier in the year when Hailey Bieber wore a pair of its parachute pants at Coachella. “There’s always going to be that element of trend and [creative] strength that I don’t think an application would harness.”

Ure herself has sometimes pushed back on the wilder initial buys the creative team advocated for and turned out to be wrong, she said.

One of the technology’s great promises is to let retailers make far more accurate forecasts about how much to produce, down to the level of size and colour. But knowing what consumers will want months in advance isn’t so simple.

https://www.businessoffashion.com/articles/technology/can-ai-predict-what-shoppers-will-buy/?utm_source=linkedin&utm_medium=post&utm_campaign=technology