These industries have well-developed governance practices built largely around algorithmic, rule-based and other model technologies and regulations that predate AI models.

Read here A comprehensive data governance model Building a comprehensive, enterprise-wide, data governance model that pulls the oldest and newest data together requires buy-in at the leadership level ...

In this episode of Focus, we take you to the World Governments Summit 2025 in Dubai, where global leaders, policymakers and experts gathered to shape the future of governance. From the integration ...

In an era where AI adoption frequently outpaces regulatory readiness, Archana Pattabhi, Senior Vice President at a leading global bank, led a forward-looking transformation that redefined how ...

By treating model governance as a proactive, integral part of operations rather than a box to check after the fact, life sciences organizations can uphold compliance, better allocate their ...

Along with Informatica's announcement of its Cloud Data Governance and Catalog today, comes a suite of features aimed at extending data governance to the world of AI and machine learning models.

The industry's ability to establish effective governance hinges upon the ability to overcome the inherent challenges associated with using AI in healthcare.

* Next, the Data Governance Maturity Model is borne of the best practices from industry and solution providers, balanced against the “ideal requirements” provided by academia.

Opinion Why super’s governance model delivers for members The existing arrangements are not some quaint artefact of history – it’s the predominant model used by high-performing workplace ...