Glossary · 5 · Content lifecycle and AI
Content risk classification
Also known as: Content criticality classification, Risk-based content classification
In technical communication, content risk classification is the division of content into classes by the consequence of an error — for example safety-related and legally required information, operating information and marketing text — so that the depth of review, the qualification of the reviewer and the strength of the release follow the risk.
- Content lifecycle
- AI
- Technical documentation
In one sentence
Content risk classification sorts content by the consequence of an error so that review depth and release follow the risk.
Example
Warnings and maintenance intervals are class A and need a review by a qualified engineer and a named release; product descriptions are class C and need an editorial check.
How it applies
- Classes: Typical criteria are the possible harm (safety-related information, warnings, limit values), legal requirements (information that law or standards require for the product) and reach (content published to many users or reused in many places).
- Review depth: Higher classes need more qualified reviewers, a second reviewer or a technical check against the product; lower classes may need only an editorial check.
- AI functions: The class decides where AI support is allowed and how its output is checked. A company may, for example, allow AI drafts for product descriptions but require that safety-related information is taken over only from released sources and reviewed in full.
- Limits: The classification decides how content is reviewed. It does not replace the risk assessment of the product, which determines what safety information is needed in the first place, and a low class never allows required information to be left out.
Content risk classification vs. risk assessment
The risk assessment analyzes the hazards of a product and leads to protective measures, including information for use. Content risk classification analyzes the consequences of errors in content and leads to review and release rules. The first determines what must be said; the second how carefully it is checked.