In the rapidly evolving landscape of cybersecurity, the need for efficient and effective security remediation strategies has never been more critical. Through the use of machine learning algorithms, natural language processing, and data analytics, the approach automates the identification of vulnerable sensitive data and how to remediate the data at the group, individual or document level. We further explore the challenges associated with implementing such a system, including ownership identification, integration with existing processes, and how to prioritize actions to deliver the greatest risk reduction.

Takeaways from the talk:

• Use AI to enable existing processes to reduce security vulnerability and risk.
• Remediate at various levels of security risks to address different outcomes.
• Enable automation to increase time to value.