What it is
An AI governance framework is the set of policies, roles and controls that decide which AI a company uses, on what data, and who answers for the results. It covers which use cases get built, how they're vetted for risk, and who owns oversight, spanning data privacy, model selection, compliance, and ethical use across every department deploying agents. Unlike individual agent policies, it operates at the organizational level.
Why it matters
Mid-market teams scaling Agentforce quickly hit compliance and risk questions without a clear owner. A governance framework prevents shadow AI sprawl and gives leadership a defensible audit trail.
Key components
- risk review board
- usage policy
- audit trail
- escalation path
How it connects
Salesforce's Trust Layer and agent-level controls handle governance inside one Agentforce deployment; a governance framework sets the company-wide rules those controls enforce, often owned by an AI Center of Excellence.
Good to know
Start small: a one-page policy on data usage and approval steps is better than no framework at all.
Related terms
Agent Governance
The policies, controls, and monitoring systems that ensure AI agents operate safely, compliantly, and within business-approved boundaries.
AI Center of Excellence
The cross-functional team that governs AI and Agentforce rollouts—setting standards, reviewing use cases, and preventing shadow AI across departments.
AI Readiness Assessment
A structured evaluation of whether your Salesforce org, data, processes, and team are prepared to deploy AI agents successfully.
Trust Layer
Salesforce's AI trust and safety framework that ensures agents operate within compliance boundaries, prevent misuse, and maintain data security.
