Direct answer
Run an AI use-case boundary matrix by listing each task, its risk level, source requirements, customer impact, review need, allowed AI role, forbidden AI role and accountable owner. The matrix prevents teams from treating all AI tasks as equally safe or equally useful.
Why it matters
This answer keeps human accountability visible in AI-assisted work. It should help readers separate source-grounded claims, useful inferences, review thresholds, unsupported output and decisions that still need human judgement.
What to check
- Which claims are source-derived, inferred, assumed or unsupported?
- What review threshold applies?
- Who owns the final judgement before publication or client use?
Common mistake
Mistaking fluent AI output for grounded, reviewed and accountable work.
Caveats
Low caveat risk: suitable for publication from the available source pack, but still avoid pricing, guarantees, unsupported service promises or claims not visible in the linked public ecosystem.