AI Glossary

AI Governance

The policies, controls, and operating practices used to manage AI usage safely at scale.

TL;DR

—The policies, controls, and operating practices used to manage AI usage safely at scale.
—AI Governance shapes how organizations design controls, ownership, and operating discipline around AI.
—Use the related terms and explanation below to connect the definition to real enterprise rollout decisions.

In Depth

AI governance is the comprehensive framework of rules, technical controls, and business processes that an organization implements to ensure generative AI is used responsibly, securely, and cost-effectively. While many people confuse governance with simple 'compliance' or a static set of rules written in a PDF, true enterprise AI governance is an active, operational discipline. It shifts the organization from merely observing AI usage to actively directing it.

At its core, AI governance addresses three primary pillars: Security & Data Privacy (ensuring sensitive information like PII or trade secrets do not leak into public models), Financial Operations (AI FinOps, ensuring the organization does not overspend on expensive API calls), and Workflow Standardization (ensuring employees use AI consistently to produce reliable, high-quality results). Without governance, AI adoption rapidly degrades into 'Shadow AI,' where employees bypass IT to use unsanctioned models, creating massive legal and financial liabilities.

Implementing AI governance requires a platform capable of actively enforcing policies inline. Rather than relying on employees to remember an 'Acceptable Use Policy,' a governed system intercepts prompts in real-time, masking sensitive data, enforcing departmental budgets, and maintaining a tamper-proof audit log of all interactions.

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The 1-Page AI Safety Sheet

Print this, pin it next to every screen. 10 rules your team should follow every time they use AI at work.

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A printable 1-page PDF with 10 clear do's and don'ts for AI use.

Related Terms

Policy Guardrails

Control checks that evaluate AI inputs and outputs against organization policy.

Audit Trails

Traceable records of AI activity, governance actions, and control events.

Role-Based Access Control

An access model that grants permissions according to organizational role and responsibility.

AI FinOps

Operational cost governance for AI usage, including budgeting, tracking, and optimization.

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Get a Draft AI Policy in 5 Minutes

Answer 6 questions about your company. Get a real AI usage policy you can hand to legal this week.

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A ready-to-review AI policy document customized to your company.

Knowledge Hub

Glossary FAQs

AI governance is typically a cross-functional effort. The <a href='/use-cases/ciso'>CISO</a> handles the security and data privacy policies, IT Operations manages the deployment and identity access (<a href='/features/role-access-control'><a href='/features/role-access-control'>RBAC</a></a>), and line-of-business leaders manage the specific prompts, budgets, and workflows for their departments.

AI Security is a subset of governance focused specifically on threat vectors like prompt injections or data exfiltration. Governance is much broader, encompassing security, financial cost control (<a href='/features/department-budgets'><a href='/features/department-budgets'>FinOps</a></a>), workflow standardization, and compliance reporting.

Remova acts as the central operating system for AI governance. It provides the technical enforcement layer—actively masking PII, enforcing budgets, and routing models—so organizations can scale AI adoption without relying entirely on manual oversight or employee training.

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