AI Foundations
Low-risk AI use cases
Start with tasks where AI can help without exposing sensitive data or making final decisions.
4 min readFoundations
Workplace example
Good first use
Summarising a public article for discussion notes is usually low risk. Drafting an unreleased merger announcement, even with names removed, is not low risk because the context itself may be confidential.
What this means
- •A low-risk AI use case does not involve confidential information, high-impact decisions, sensitive personal data, or final authority.
- •Good early uses often include brainstorming, summarising public information, drafting first-pass notes, organising ideas, or improving wording for human review.
- •Higher-risk tasks can still use AI, but they need stronger controls, approved tools, and human review.
Why it matters
- •Starting with low-risk tasks helps people learn without creating avoidable data, quality, or compliance risk.
- •It builds confidence while keeping the review burden manageable.
- •It helps teams separate productivity gains from unsafe automation.
Common mistakes
- •Using public tools with disguised but still sensitive work information.
- •Letting AI influence final recommendations before the facts are stable.
- •Assuming internal tasks are automatically low-risk.
What good judgement looks like
- •Choose tasks with public or non-sensitive information.
- •Keep human review before sharing or acting.
- •Avoid tasks involving employment, pay, compliance, customer harm, or confidential strategy unless approved controls are in place.
Try this at work
- •List five tasks you do often.
- •Label each as low risk, review required, high risk, or avoid.
- •Pick one low-risk task and define how you will review the output.
How this helps your reassessment
- •You can identify suitable first uses for AI support.
- •You can explain why some tasks need stronger controls.
- •You do not use tool convenience as the main risk test.