He adds: “In many cases, there’s data estates [that] look like a large, dusty closet with things shoved in a bunch of different drawers. You can’t take that and then have a clean, precise analysis based on data that you can trust.”
Artificial intelligence (AI) has moved beyond the experimentation phase and is now seen as a key tool in enterprises. This year’s global survey report by Cloudera, titled The Evolution of AI: The State of Enterprise AI and Data Architecture, reflects this. Of the 1,500 IT leaders polled, 96% of them reported that AI is at least “somewhat integrated” into their core business processes, up from 88% of the 600 leaders surveyed last year.
As the adoption of AI grows, the biggest challenge to quality AI is having quality data, says Cloudera CEO Charles Sansbury. “[In the] early stages, when companies bought pre-trained models and then tried to fine-tune them on their own data, they got incredibly varied results. So we’ve heard that we’re in the early stages of this evolution. But still, most customers will tell you that their biggest challenge to quality AI is quality data.”
