Transforming the Unknown: Revealing AI Risks and Data Lineage Insights

As organizations rapidly embrace AI, with 96% accelerating adoption, traditional "log-based" security measures are proving inadequate. The opaque nature of AI initiatives—where input and output exist without transparency—poses significant risks for data security leaders. They face challenges such as prolonged investigations, undetected insider theft, and compliance issues due to the lack of visibility into data journeys.
Join our executive briefing to learn how data lineage can shift your security strategy from a Black Box to a Glass Box. We’ll discuss how transitioning to a dynamic "Lineage Graph" can reveal hidden threats and reduce AI-related risks, allowing your organization to protect sensitive information while fostering innovation.
Key Takeaways:

• Understand the limitations of traditional security in AI contexts.
• Discover the importance of data transparency and lineage.
• Learn how to implement a dynamic Lineage Graph.
• Identify methods to mitigate insider threats and compliance risks.
• Gain insights into balancing security with rapid innovation.