Extract from Tim Rollins article, “Unifying Data Risk Management: A 4-Step Operational Framework.”
Learn how legal and security leaders are transitioning to defensible, goal-driven AI automation to streamline complex, high-stakes workflows today.
Author’s Note: This is the sixth article in our multi-part series exploring how legal, privacy, and security leaders can transition from standard Generative AI to defensible, goal-driven automation. This series is based on insights from our thought leadership white paper, The Shift to Autonomous, Defensible AI.
On the surface, a 72-hour cybersecurity breach notification, a complex civil subpoena, and a Data Subject Access Request (DSAR) seem like entirely different operational problems. They originate from different departments, involve different regulatory bodies, and carry distinct deadlines.
However, when you look beneath the surface, these workflows share a common procedural DNA. Responding to any high-stakes data risk event demands a similar set of core capabilities:
- Navigating massive data volumes
- Isolating sensitive information
- Applying context-specific legal or privacy rules
- Maintaining an immutable audit log under strict time pressure.
Traditional, manual data processing stumbles when attempting to execute these tasks at enterprise scale.
