In this interview with Help Net Security, Apoorv Agarwal, CEO at Text IQ, talks about the risk of unstructured data for organizations and the opportunity to leverage AI and automation to identify sensitive data at scale. Ideally, organizations should have a handle on where sensitive information is sitting in their data. In general, companies end up retaining the information they collect for a long time, even when they have no real use for this information. I think the problem boils down to a broader issue of data governance. It's impossible to have strong data governance without some level of automation; for instance, the volume of data generated by enterprises is rising exponentially and relying on humans to take stock of all the sensitive information that's laying buried in their database--undetected, and more often than not, in an unstructured format--simply does not work at scale.

A 2019 report from the World Economic Forum shows similar high growth for transportation and storage, manufacturing, and wholesale and retail trade. There's no doubt that Artificial Intelligence (AI) and automation are benefiting many industries. But going from a vision to a full implementation that is producing value is fraught with pitfalls. In this article, we'll look at what it takes to leverage AI and automation for productivity and growth. Being bold means taking advantage of opportunities that can have a great payoff. However, that should be balanced with risk tolerance.