The last few years have been auspicious for artificial intelligence. Once the preserve of Silicon Valley's tech giants, AI has emerged as a tool that businesses small and large have become keen to harness for disparate use-cases in domains ranging from cybersecurity to customer service and analytics. Data scientists, tasked with creating machine learning-driven tools, are now ubiquitous in most industries. As AI's presence and influence grows across the business world, one key potential pitfall should not be overlooked: data. AI systems are generally powered by machine learning, a technique that creates smart systems through the recursive training of algorithms on vast troves of data – in the case at hand, we are talking about data that companies create and gather throughout their daily businesses.

The last few years have been auspicious for artificial intelligence. Once the preserve of Silicon Valley's tech giants, AI has emerged as a tool that businesses small and large have become keen to harness for disparate use-cases in domains ranging from cybersecurity to customer service and analytics. Data scientists, tasked with creating machine learning-driven tools, are now ubiquitous in most industries. As AI's presence and influence grows across the business world, one key potential pitfall should not be overlooked: data. AI systems are generally powered by machine learning, a technique that creates smart systems through the recursive training of algorithms on vast troves of data – in the case at hand, we are talking about data that companies create and gather throughout their daily businesses.

Nobody wants their company's core competency to be managing data in a database. We feel the same way about AI." In many ways, Hammond represents a wave of entrepreneurs who are counting on the cloud to help them make AI less exotic and more accessible.

If 2015 was the year analytics tools became ubiquitous in enterprise software, 2016 is shaping up to do much the same for machine learning. Just last week artificial-intelligence startup Nervana launched an offering that promises "deep learning on demand," and on Thursday Hewlett Packard Enterprise released a product of its own for what it calls "machine learning as a service." Dubbed Haven OnDemand, the cloud platform offers machine-learning application programming interfaces (APIs) and services designed to enable developers and businesses to build data-rich mobile and enterprise applications. Face-detection capabilities are included in Haven OnDemand. Haven OnDemand entered beta back in 2014, and at the time it had just a few APIs, said Fernando Lucini, HPE's CTO for big data.