The Cyber Security Review | Monday, August 05, 2024
Safeguarding sensitive generative AI data becomes crucial; the convergence of a unified data security and governance approach, as well as global momentum in AI regulation and data residency, are some of the important AI data security governance trends that businesses should consider.
FREMONT, CA: As more businesses use the power of generative AI, data security governance (DSG) has never been more important. The influence of generative AI is growing, pushing organizations to reconsider their data security, privacy, and governance strategies for generative AI applications.
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Here are the trends that organizations should be aware of as the AI landscape evolves:
Protecting sensitive generative AI data is crucial: As generative AI advances, businesses will increasingly use sensitive data to train AI models, Large Language Models (LLMs), and their associated embeddings in vector databases. While this opens up new opportunities, it raises concerns about sensitive data leaks. Data that would have previously been stored in silos can now be used in generative AI use cases. While the business value is obvious, generative AI may endanger an enterprise by exposing sensitive data if not properly managed and safeguarded. Unlike safeguarding data in traditional databases, securing data inputs and outputs from generative AI applications will necessitate organizations adapting existing data security and governance frameworks to accommodate the new architecture.
Integration of a unified data security and governance strategy: As organizations become more reliant on various platforms, the need for a consistent approach to DSG has never been higher. Data security in modern data and AI demands an end-to-end lifecycle approach that begins with identifying, categorizing, and tagging sensitive material in one's data estate. Then, organizations must fully safeguard data access while regularly auditing and monitoring their data security posture. Instead of including data governance and security in each tool, a unified approach ensures that security and governance policies are uniformly enforced throughout the data estate, regardless of an organization's size or data. This strategy allows for the flexibility to manage increasing compliance and security requirements by identifying sensitive data, implementing strong data controls, and assuring access transparency at scale.
Global trends in data residency and AI regulation: Privacy, data security, and compliance are becoming increasingly important due to new rules like the EU AI Act and current obligations like GDPR. The effect of AI and data transcends borders, making global compliance a crucial responsibility. Organizations must stay ahead of regulatory developments to guarantee that their data and AI processes are secure and compliant globally. Implementing control systems to automate safeguards rather than simply training individuals and improving trust and security in a consistent, automated, and worldwide manner is crucial.
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