Who this is for

Built for all datasets—structured, unstructured, synthetic, or scraped—used in AI lifecycle activities under your organization control or contracted processors.

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.

• Document provenance, lawful basis
• Prohibit use of datasets obtained through unauthorized access, deceptive collection
• Apply data minimization: collect and retain only fields necessary for the stated AI…
• Implement quality controls for labeling accuracy, class balance
• Remove or anonymize personal data from training sets unless processing is lawful and…
• Version datasets and link each model release to specific dataset snapshots in the…
• Restrict access to training data on a need-to-know basis with encryption at rest and…
• Define retention and secure disposal schedules for training artifacts aligned with…
• Assess bias and sensitive attribute inclusion before training
• Respond to data subject requests affecting data used in models per Data Subject…