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How to govern OpenClaw

Autonomous agents that browse, click and complete tasks across your systems on your behalf.

OpenClaw · Reviewed when the vendor ships a capability change or a customer declares the tool

How OpenClaw is used

We see two common ways businesses use OpenClaw, and we govern each one on its own terms. If your team uses it differently, that is fine: you describe the use in your own words and Certrak works out the governance from what it actually does.

Autonomous task agent

Consequence to people: High

General-purpose AI agent that takes actions across your tools and systems - email, calendar, messaging, files

Personal informationMost outputs reviewedInternal use onlyChanges records in other systemsActs on its own
  • Review rhythm: Monthly check-in
  • Governance is mostly about: What it may be given; Safe everyday use; A person stays accountable

Workflow automation across systems

Consequence to people: Medium

Automating tasks across business systems - triggers, data movement, decisions in workflows

Internal informationNo human reviewInternal use onlyChanges records in other systemsActs on its own
  • Review rhythm: Monthly check-in
  • Governance is mostly about: Safe everyday use; A person stays accountable; Checking what it produces

Governing OpenClaw in practice

  1. Name one person who owns OpenClaw in your business. Governance starts with a name.
  2. Write down what OpenClaw is used for. Certrak recognises 2 common uses: Autonomous task agent and Workflow automation across systems. Yours may differ; write down yours.
  3. Decide what OpenClaw may and may not be given. Personal information is in scope for some uses; write the boundary down before it is needed.
  4. There is no human review of outputs. Decide whether that is acceptable for each use, and what would make you change it.
  5. OpenClaw can create, change, or delete records in another system without a person approving. Record which of these you allow, and who can change that.
  6. Look at this again every month, and sooner on any of these: industry incidents, vendor model updates, autonomy level changes and data classification changes.