Depending on the industry where AI is deployed, model data drift can have alarming consequences ranging from financial to ...

While AI has been used in enterprise and consumer products for decades, only large tech organizations with sufficient resources were able to implement it at scale. In the past few years, advances in ...

Is it better to monitor for quality or detect problems? It depends. Here's how to choose between active and passive data governance. Image: Friends Stock/Adobe Stock The goal of data governance is to ...

Unverified and low-quality data generated by artificial intelligence (AI) models – often known as AI slop – is forcing more security leaders to look to zero-trust models for data governance, with 50% ...

Published in AI & Society, the study titled “Data-centric AI governance for responsible organizational value: evidence from a ...

A blended approach combines centralized policy compliance with decentralized flexibility. In association withCapital One Data governance has historically been a serious bottleneck for analytics. While ...

The COVID crisis has shown that ethical and effective uses of data and increased sharing of data can save lives and can be critical for society as a whole (by contrast to the use of data made by ...

Data governance is an umbrella term encompassing several different disciplines and practices, and the priorities often depend on who is driving the effort. Chief data officers, privacy officers, ...

In banking, data governance is about meeting both regulatory and internal requirements. Find out what's required of your data governance plans by reading this guide ...