What is Editorial AI policy?
An editorial AI policy is the public document that defines how a newsroom uses artificial intelligence — at which stages, with which safeguards, and with which disclosure to readers — versioned and maintained as a visible editorial commitment.
In short
- Public document describing AI use in the newsroom.
- Defines safeguards (human review, fact-check, prohibited areas).
- Versioned: changes produce new versions with date and justification.
Full definition
In professional journalism, having a public editorial AI policy has shifted from good practice to near requirement (especially in markets with upcoming regulation). The document serves the reader (transparency), the team (internal clarity), and external audit (compliance).
Expected components of a serious editorial AI policy: editorial principles (editor in command, verifiability, non-replacement), description of the stages where AI operates, prohibited areas (uncontrolled hallucination, fabricated quotes, investigative journalism with confidential sources), audit trail, no-training policy with the publication's content, and relationship with regulation.
Serious publications version the policy — every change produces a new version with effective date and justification, keeping history accessible. This pattern is the same used in Terms of Use and Privacy Policy — and for similar reason: transparency requires traceability.
How it works
- Public document at a fixed URL (e.g. /editorial-ai-policy), with clear version and effective date.
- Modular section structure: principles, stages where AI operates, prohibited areas, audit trail, training, disclosure, regulation.
- Explicit versioning: each new version has a rationale ('what changed and why') published at /versions.
- Linked in the site's global footer, in the FAQ, and in onboarding for new editorial contracts.
Practical example
A news publication publishes editorial AI policy v1.0 in January 2026 with 10 sections. In May 2026, it updates to v1.1 adjusting the disclosure section after regulatory guidance. /editorial-ai-policy/versions lists both versions with effective date and what changed. External audit can reconstruct the exact history.
Editorial AI policy vs Implicit editorial principle (not published)
An implicit principle exists but has no public trail. It works internally until something goes wrong (reader complaint, lawsuit, regulation). A public policy is the opposite: written, versioned, accessible. In 2026, the second is the growing standard; the first became strategic exposure.
Frequently asked questions
Who should write the editorial AI policy?
Ideally, senior editorial + legal + technology, together. It can't be only legal (it becomes defensive); it can't be only editorial (it loses legal grounding); it can't be only technology (it loses journalistic sensibility). All three need to be in the room.
Is it mandatory to have an editorial AI policy?
In 2026, it's not legally mandatory in Brazil — but several regulations in progress converge in that direction. Serious publications are getting ahead of the curve: having a public policy ready before the regulatory requirement arrives is competitive advantage and legal protection.
See how Typedit uses editorial ai policy
The verifiable editorial AI platform applies this concept in production — at Brazilian newsrooms with 10M+ monthly readers.
Related terms
Editorial audit trail
An editorial audit trail is the complete, versioned, exportable history of decisions made on each AI-assisted story — sources consulted, claims modified, editorial overrides, and timestamps — ready for internal investigations, reader inquiries, and regulatory compliance.
AI-use disclosure
AI-use disclosure is the explicit signal to the reader that a story involved artificial intelligence in its production — it can appear in the story footer, author bio, or as a standard badge, per the publication's editorial policy.
E-E-A-T (in the AI era)
E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is the set of signals Google uses to evaluate content credibility — in the AI era, visible human authorship, verifiable sources, and AI-use disclosure have come to count more.