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In AI governance, transparency means being open about how an AI system works, what data it uses, what it can and cannot do, and when it is being used. Transparency operates at multiple levels: system transparency (how the AI works, disclosed to regulators and auditors), interaction transparency (users are told when they are interacting with AI), and output transparency (AI-generated content is labeled as such). The EU AI Act and multiple US state laws impose transparency requirements. Internally, transparency means your team understands what AI tools are in use and what decisions they influence.
Why this matters for your team
Transparency is both a legal obligation and a trust advantage. Users who know they're interacting with AI — and understand its limitations — are more forgiving when it makes mistakes than users who didn't know AI was involved. Disclose proactively rather than waiting for regulation to force it.