Why do 87% of data science projects never make it into production?
“If your competitors are applying AI, and they’re finding insight that allow them to accelerate, they’re going to peel away really, really quickly,” Deborah Leff, CTO for data science and AI at IBM, said on stage at Transform 2019.
On their panel, “What the heck does it even mean to ‘Do AI’? Leff and Chris Chapo, SVP of data and analytics at Gap, dug deep into the reason so many companies are still either kicking their heels or simply failing to get AI strategies off the ground, despite the fact that the inherent advantage large companies had over small companies is gone now, and the paradigm has changed completely. With AI, the fast companies are outperforming the slow companies, regardless of their size. And tiny, no-name companies are actually stealing market share from the giants.
But if this is a universal understanding, that AI empirically provides a competitive edge, why do only 13% of data science projects, or just one out of every 10, actually make it into production?
