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This article explains how different countries approach data governance, showing how the EU, U.S., and China have very different views on data ownership and use. Understanding these differences helps explain how global AI systems are developed.
Scotiabank has launched Scotia Intelligence, an integrated AI framework designed to unify data and AI operations while ensuring compliance and empowering client-facing teams.
Data quality is often neglected until issues arise, but as organizations scale, the cost of fixing inaccurate data multiplies. Proactive data governance is essential for sustainable growth.
As AI systems become more autonomous, the importance of data governance is gaining prominence. Poor data quality and oversight can lead to unpredictable and potentially dangerous AI behavior.
Learn how to create a cross-functional AI implementation framework that goes beyond just appointing a Chief AI Officer, following the 'magician' leadership approach that successful organizations use to maximize generative AI potential.
Half of agentic AI adopters cite data quality and retrieval issues as deployment barriers, according to a survey of chief data officers.
Meta is under fire for sending private AI glasses footage to Kenya for training, raising privacy concerns and potentially inviting European regulators.
