Who this is for

Built for incidents involving model compromise, prompt injection, data poisoning, harmful outputs, bias harms, regulatory breaches, and AI vendor failures.

Every section below is included in your download, summaries only shown here, not the policy text.

• —

  Document control

  Owner, version, review cycle, and approval fields ready to customize.

• 1

  Purpose

  Why this policy exists and the outcomes it supports.

• 2

  Scope

  Who and what systems, locations, and activities are in scope.

• 3

  Definitions

  Key terms defined in a table for consistent interpretation.

• 4

  Roles and responsibilities

  Accountability for executives, owners, managers, staff, and IT.

• 5

  Policy requirements

  Numbered, audit-ready controls you can adopt or tailor.

• 6–8

  Exceptions, monitoring, enforcement

  Exception process, review cadence, and consequences of non-compliance.

• 9–10

  Regional compliance and framework mapping

  US, EU, and global obligations plus mapped control themes.

• A–C

  Appendices

  Customization notes, document history, and approval signatures.

Requirement themes addressed, not the verbatim policy language.

• Integrate AI incident types into the enterprise incident response plan with defined…
• Maintain 24/7 contact paths for reporting AI incidents affecting production or…
• Assign incident roles: commander, communications, legal, technical lead
• Execute containment playbooks (model rollback, API key rotation, feature disable)…
• Preserve logs, prompts, outputs
• Notify affected customers, regulators
• Conduct post-incident reviews with corrective actions tracked to closure.
• Test AI incident scenarios at least annually through tabletop or technical exercises.
• Coordinate with Security Incident Response and Breach Notification policies without…
• Report aggregate AI incident metrics to the AI Governance Committee quarterly.