Gartner predicts that by 2028, 50% of organizations will have had to adopt a zero-trust posture for data governance as a ...

Traditional model validation assumes a model can be tested in isolation, signed off, and then left unchanged. That approach ...

When governance is engineered into how data is created and used, it accelerates access, experimentation, model development ...

Absent a comprehensive federal AI framework, agencies should be guided by four governance priorities. While the federal ...

That in turn could hasten a decline in model quality and accuracy, and an increase in hallucinations and bias. In response to ...

Organisations are beginning to implement zero-trust models for data governance thanks to the proliferation of poor quality AI ...

The implications of AI for data governance and security don’t often grab the headlines, but the work of incorporating this ...

For today’s CISOs, the perimeter isn’t a firewall — it’s the data itself. Hybrid and multi-cloud architecture have created massive volumes of sensitive ...

If you’re reading this, there’s a very good chance your organization’s approach to data governance is the exact opposite of what it should be for the AI era. If you’ve read my prior articles, you know ...

Abstract: The increasing reliance on artificial intelligence (AI) and advanced analytics to gain competitive advantages has elevated the importance of robust data governance frameworks. This article ...

In today’s rapidly evolving digital landscape, the value of data cannot be overstated. Data has become the lifeblood of innovation, driving decisions, shaping industries, and transforming how we live ...

Open banking, embedded finance, and AI are changing where bank data flows. Data privacy now determines how far innovation can ...