Compliance & Regulatory
AI Transparency
The ability to explain how AI systems work, what data they use, and how decisions are made.
AI transparency is the principle that organizations should be able to explain their AI systems' purpose, operation, data sources, and decision-making processes to stakeholders. For enterprises using third-party AI tools, transparency has two dimensions:
- Vendor transparency: Understanding how the tools you use work, what data they process, and how they're trained
- Organizational transparency: Being able to tell regulators, customers, and employees what AI tools are in use and how they're governed
The EU AI Act makes transparency a legal requirement for many AI systems, including obligations to inform users when they're interacting with AI and to document the purpose and limitations of AI systems used in high-risk contexts.
Why it matters
Transparency builds trust — with regulators, customers, employees, and partners. It's also a practical necessity: you can't govern AI effectively if you can't explain what AI you're using and why.