There’s much more to a successful AI project than installing a Hadoop cluster and hoping for the best. According to one Gartner forecast, “60 percent of big data projects will fail to go beyond piloting and experimentation, and will be abandoned.” Others estimate AI project failure rates as high as 85%!
Yet, to remain competitive over the next few years, organizations will increasingly need to have not just one AI project success but will need to apply AI across the entire enterprise, transforming themselves to become AI-driven.
“If you wish to become an AI-driven organization, you’ll need to do things at scale. For that, you will need expertise [...], speed, [...] and finally, you need trust.”
— Colin Priest, Sr. Director of Product Marketing, DataRobot
These are three obstacles that businesses face on their journey to become AI-driven organizations. In this AI Simplified video, Colin defines each obstacle with examples and shares how businesses can overcome them with automated machine learning.
Watch Colin’s video for more insights on how to overcome the three barriers to becoming an AI-driven enterprise:
Hear more from Colin about the importance of trusting AI in his blog series, How to Understand a DataRobot Model.