In data we trust. But should we?

Emerging technology is becoming an essential component of any organization that hopes to accelerate and compete on a national or global level. Advancements in technology, such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA), hold untapped potential for businesses and consumers alike; they have the potential to disrupt and strengthen industries, reinvent operations, and push the boundaries of what’s possible by leveraging data in new ways, providing deeper insights, and operating at higher speeds.
Emerging technology is getting more powerful, more affordable and will be embedded within the organizations operations and decision making moving forward. But it is not foolproof. The common denominator, whether AI, ML or RPA, is data. The limits of what it can achieve is bound by the quality of the data the technology employs.

We are pleased to launch the latest whitepaper in our three-part series, titled “In Data we trust. But should we?”, which serves as a guide for business and technology leaders. By considering potential risks in data that’s consumed by emerging tech applications, it provides a framework that can help ensure the data assets – and real time, business critical decisions based on this data – are sufficiently trustworthy and reliable.