Artificial intelligence's emergence into the mainstream of enterprise computing raises significant issues -- strategic, cultural, and operational -- for businesses everywhere. What's clear is that enterprises have crossed a tipping point in their adoption of AI. A recent O'Reilly survey shows that AI is well on the road to ubiquity in businesses throughout the world. The key finding from the study was that there are now more AI-using enterprises -- in other words, those that have AI in production, revenue-generating apps -- than organizations that are simply evaluating AI. Taken together, organizations that have AI in production or in evaluation constitute 85% of companies surveyed. This represents a significant uptick in AI adoption from the prior year's O'Reilly survey, which found that just 27% of organizations were in the in-production adoption phase while twice as many -- 54% -- were still evaluating AI.

Some recent surveys and predictions show that an increasing number of enterprises are making investments in all forms of AI and there is a growing interest in experimenting with deep learning. I spoke with O'Reilly Media's chief data scientist, Ben Lorica on the state of deep learning in the enterprise to get further insights. "It's a bit early to judge AI," says Ben who believes that many enterprises that have data science and machine learning groups will extend their experimentation and explore deep learning. Deep learning lies at the intersection of big data, big model, and big compute. It requires a large volume of training data and knowledge of how to configure deep learning algorithms.