How is AI privacy different from privacy-protected AI?
AI privacy is the broader subject area — the general discipline of protecting personal data across an AI system's lifecycle. [Privacy-Protected AI](/glossary/privacy-protected-ai) describes a specific, achieved outcome: an organization's AI use where sensitive data consistently doesn't reach an external vendor unprotected.
Related terms
Privacy-Protected AI
The broader outcome that local redaction, masking, privacy engines, and privacy firewalls are all built to achieve — using AI tools productively while ensuring the sensitive data behind the results never reaches an external vendor in a form that exposes real people or organizations.
Sensitive Data
Any information that could cause harm, embarrassment, discrimination, or loss if exposed to an unauthorized party — a broader category than regulated data, defined by potential impact rather than by a specific legal framework.
Hallucination (AI Hallucination)
An AI model generating output that's fluent, confident, and entirely wrong — not a bug that occasionally slips through, but a structural property of how these models work, which means the real question isn't whether hallucination happens, but what catches it before someone acts on it.
HIPAA (Health Insurance Portability and Accountability Act)
The US law governing how protected health information can be used, stored, and shared — and one of the clearest examples of a regulation written decades before AI existed that now has to be applied, without modification, to AI tools its drafters never anticipated.
How does agent governance relate to an audit trail?
An audit trail is one of the concrete outputs agent governance typically requires — a record of what an agent did, when, and under what authorization, which supports both internal accountability and the kind of documented oversight regulators increasingly expect for autonomous, multi-step AI systems.
How is AI agent governance different from AI governance generally?
AI Governance covers policies and oversight across an organization's entire AI footprint. AI agent governance is a narrower, more specific discipline focused on the particular risks agents introduce — autonomous decision-making, tool use, and chained multi-step actions — that general AI policies weren't originally built to address.
See How is AI privacy different from privacy-protected AI? in practice
Questa AI anonymizes sensitive data before it reaches any AI model — across documents and live prompts, with governance and data-residency control.