This domain is 15% of the CCAO-F exam. Use Claude safely: data, accuracy, bias, policy and accountability.
Know what you are putting in
Before pasting anything into an AI tool, classify it: public, internal, confidential, or personal data. Your company's policy should say what may be used with which tool and plan. In Malaysia, personal data is also covered by the PDPA, so customer details need care. See our guide to AI governance and PDPA.
Main risks to manage
- Data leakage — confidential or personal information shared where it should not be.
- Inaccuracy — confident but wrong output used without checking.
- Bias — outputs that treat groups unfairly, especially in hiring, lending or customer decisions.
- Over-reliance — people stop checking, or skills erode.
- Intellectual property and confidentiality — what you may generate, share or train on.
Policy and accountability
Good governance is plain: an approved-tools list, rules on data classes, a requirement to review output before external use, a place to report problems, and a named owner. A person — not the model — remains accountable for any decision or deliverable.
Responsible use in practice
- Be transparent when AI contributed to work, where that matters to the recipient.
- Keep a human in the loop for consequential decisions affecting people.
- Choose the minimum data needed for the task.
Common exam angles
- The best response to a scenario where someone shared sensitive data.
- Which tasks need human review for fairness or accuracy.
- What a reasonable company AI-use policy should include.
All seven domains
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Study notes, not official material. This guide is written by Agmo Academy to help you prepare. It is not affiliated with or endorsed by Anthropic — always confirm details against Anthropic's current exam guide before you sit the exam.