Who this is for

Built for rules engines, ML classifiers, robotic process automation with decision logic, and generative AI used to approve, deny, or rank individuals or transactions.

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.

• Maintain a register of ADM use cases with legal basis, data categories
• Prohibit ADM where banned by law unless explicit consent or contractual necessity…
• Implement human-in-the-loop or human-on-the-loop controls proportional to decision…
• Provide pre-decision notices and post-decision explanations commensurate with…
• Enable data subjects to contest decisions and request human reconsideration within…
• Ensure ADM logic is tested for accuracy, fairness
• Separate development and production ADM environments
• Log ADM inputs, outputs, model/rule version
• Conduct periodic ADM audits with internal audit or compliance participation.
• Update ADM documentation when laws, models