Data is the cornerstone of today’s economy, powering nearly every corporate system. Ethical businesses want to gather and use relevant insights from data to advance their business goals, but they also ...

A phased guide to AI governance in cloud-native systems, aligning ISO 42001:2023 and NIST AI-RMF with lifecycle controls, ...

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

AI governance cannot live solely within IT. It requires cross-functional oversight. Many institutions are creating AI ...

Data Governance (DG) is the systematic approach to managing, organizing, and securing an organization’s data assets. For a long time, large organizations were the ones mainly concerned with this topic ...

Responsible organizations understand that privacy governance is essential for the systematic and compliant management of personal data and for maintaining customer and stakeholder trust. In a world ...

1. The "quarantine" pattern is mandatory: In many modern data organizations, engineers favor the "ELT" approach. They dump raw data into a lake and clean it up later. For AI Agents, this is ...

India's AI framework proposes a layered, lifecycle approach. But how will it work in practice, and what challenges does it ...