Research

Research

At Entropy Data, we're committed to advancing the field of data governance through research and innovation.

Automating Data Governance with Generative AI

This research examines how large language models can support data governance by generating warnings about data access decisions in decentralized systems. The study introduces Governance AI, an LLM-powered tool that evaluates whether data access requests comply with data contracts, company policies, and regulations like GDPR.

Rather than making final decisions, the system provides "structured warnings and suggestions for correction to guide human experts."

This approach ensures that AI augments human decision-making rather than replacing it, maintaining the necessary human oversight for contextual and legal accuracy in data governance decisions.

Publication Details

Authors:

  • Linus W. Dietz (King's College London)
  • Arif Wider (HTW Berlin)
  • Simon Harrer (Entropy Data)

Conference: AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 2025

Key Findings

  • Governance AI issued 3.6 times more warnings than human experts while catching all compliance concerns
  • 80% of AI-generated warnings were judged correct after secondary review
  • LLM-generated synthetic test cases effectively simulated real-world governance scenarios
  • Human oversight remains essential for contextual and legal accuracy

Learn More

Read More Download PDF

Impact on Our Products

The findings from this research inform the development of our products, including the AI-powered governance features in Entropy Data. By exploring how AI can support and enhance human decision-making in data governance, we aim to make data more accessible, secure, and compliant across organizations.