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AI Editorial Guidelines: How to Write Your Own

AI editorial guidelines set who is accountable, what to disclose, how to fact-check and what never goes into a tool. Here is how to write yours, with examples.

AI Editorial Guidelines: How to Write Your Own

AI Editorial Guidelines: How to Write Your Own

Editor reviewing a printed policy sheet

AI editorial guidelines are a short, written set of rules that says where your team may use generative AI, who stays accountable for the result, when you tell readers, how you check the output and what data never goes into a tool. The best ones are operational: a page people actually open while they work, not a statement of values. This guide shows what newsrooms, publishers and journals put in theirs, then turns it into a template any creator, marketing team or small business can adopt.

TL;DR

  • A person, never the tool, owns every published word. Every serious policy we reviewed starts there.
  • Disclose AI use when it generates content or shapes editorial decisions. Routine spelling and grammar fixes usually do not need a label.
  • Verify every fact, quote, statistic and image before publishing, and test for bias in anything public-facing.
  • Keep confidential, unpublished and client data out of tools you have not approved.
  • Put the rules into onboarding and checklists, and review them on a schedule.

Table of Contents

What AI editorial guidelines are and why they matter

An editorial guideline has always answered one question: what will we stand behind when we publish? Generative AI adds a second one: what happened between the idea and the page? If a model drafted the outline, a person rewrote it, and a tool polished the sentences, your readers, clients and editors deserve a consistent answer about how that process works.

An analysis of guidelines published by news organizations found that oversight is the most common theme: meaningful human involvement, extra editing and fact-checking before publication, and a rejection of the idea that machines replace the people deciding what goes out. Academic publishers say the same thing in different words, and so do professional bodies for journalists.

You do not need to be a newsroom to need this. A marketing team publishing 40 pieces a month, a freelancer with five clients, an ecommerce seller generating product copy and a student submitting coursework all face the same three risks: an unchecked claim goes live, a confidential file ends up in the wrong tool, or a reader feels misled about who made what.

What the ranking policies agree on

Policies from the BBC, Springer Nature, Sage, Taylor & Francis and others differ in detail, but a handful of principles repeat. Here is what the checked sources say.

Human accountability cannot be delegated

The Canadian Association of Journalists says in its March 2026 AI guardrails that AI can assist with repetitive tasks, research and production, while journalists should review or edit outputs, humans should monitor systems, and editorial leadership should set standards and stay accountable. The same document describes layers of oversight: a human in the loop on individual outputs, a human on the loop watching the system, and editorial governance above both.

Three layers of human editorial oversight

The SDEWES Centre’s generative AI policy is blunt: AI must not replace independent editorial judgment, reviewer assessment or final decision-making, and a human editor remains responsible for every decision. IREX makes the same point for newsrooms in its June 2025 guidance note: AI should complement human judgment, with oversight at every stage.

AI is a tool, not an author

The STM Association’s 2023 generative AI paper recommends that AI never be credited as an author, because a tool cannot fulfill the role of an author or be held accountable for content. The BBC’s editorial guidance on AI takes a different angle on the same idea: any AI use in creating, presenting or distributing content must stay consistent with its editorial values, including accuracy, impartiality, fairness and privacy. Your AI rules are not a separate rulebook. They sit under the standards you already have.

Policies differ by context

STM also notes that authors should consult the specific journal’s guide before submitting, because policies differ by publisher and journal. Some go further than disclosure. Inter-Research prohibits AI-generated images and videos for publication because of copyright concerns, and requires authors to disclose generative AI support, including the tool and the reason.

Context Typical stance What it means for your guideline
Newsrooms Humans decide and verify; AI assists with research and production Name who signs off on every piece
Academic publishing No AI authorship; disclosure of substantive use; strict on images Follow the target journal’s own policy first
Marketing and business content Rules set by the company, plus advertising and consumer law Write your own policy and tie it to brand and legal review

Marketing teams have the most freedom and the least external structure, which is exactly why a written policy matters more for them than for a journal with one already in place.

Disclosure: when to tell readers and what to say

The test most policies use is substance. Impress, a UK press regulator, advises in its April 2025 best practice note that AI use should be disclosed when it generates content, assists reporting or influences editorial decisions, that disclosure should be proportionate, and that public statements should explain the tools’ purpose and scope. Labels can take several forms, such as a logo, an AI-assisted byline or a specific note, scaled to the AI’s impact on the content.

New Zealand’s public broadcaster draws the lower line clearly. RNZ’s 2026 AI principles ask for precise disclosure explaining how and why AI was used, while noting that mundane assistive tasks such as basic spelling and grammar correction generally need no disclosure unless they change the meaning.

A draft 2026 policy from the IJREL journal says substantive use of generative AI in writing, analysis, translation, coding, image generation or data processing must be disclosed. Editorial Tecnológica de Costa Rica asks for a note naming the tool, its purpose and its specific contribution, in its 2026 guidelines.

A workable disclosure line for a business blog might read: “This article was outlined with an AI assistant and edited, fact-checked and approved by [name].” Three parts, one sentence: the tool’s role, the human’s role, the accountable person.

Disclosure is not only a courtesy in the US. The FTC’s rule banning fake and AI-generated consumer reviews and testimonials was announced in August 2024, so your guideline should forbid generating customer reviews or testimonials outright. For labels on images, audio and video, our companion piece on AI content policy for creators covers EU rules and C2PA content credentials.

Disclosure: when to tell readers and what to say

Accuracy, bias and unsupported claims

Generative models write fluent text whether or not it is true. A guideline has to say who checks what, and how.

Impress advises publishers to fact-check information intended for publication when AI was used for research, and to apply human editorial review to ensure accuracy and prevent discriminatory content. Its Standards Code requires human review of all AI uses that lead to publishing journalistic content, under clause 1.1.6©. One academic analysis reports that The New York Times requires AI use to begin with facts verified by journalists and to be checked by editors.

On bias, the CAJ recommends ongoing bias testing of any authorized tool, especially when it generates public-facing content. PMParrot, a Nigerian media outlet, requires staff to review AI outputs for systemic, gender, ethnic, religious or political bias and to adapt content to local cultural and legal realities.

A verification checklist you can paste

  1. Claims. Every number, date, quote and named study is traced to a primary page, and the link is kept in the draft.
  2. Names and products. People, companies, prices and features are confirmed against the owner’s own page.
  3. Invented sources. Any citation the model supplied is opened and read. If it cannot be found, it is deleted.
  4. Bias pass. Someone other than the drafter reads for stereotypes, missing perspectives and local fit.
  5. Voice. The piece sounds like your brand and not like generic model prose.
  6. Sign-off. A named human approves it.

Detector scores are not a substitute for step 1. A tool that says “98% human” tells you nothing about whether the claims are true, which is the argument in our piece on checking claims before you trust detector scores.

This section prevents the most expensive mistakes. Impress says publishers should avoid sharing confidential, sensitive, unpublished, copyrighted or proprietary information with AI tools unless they use secure in-house models with strict data-protection measures. It also advises considering creators’ rights and labeling AI-generated images. SDEWES requires editors and staff to protect unpublished materials and to keep confidential content out of external generative AI systems unless a tool is expressly approved and safeguards exist.

For a business, translate that into a short list of data classes:

  • Never enter: client contracts, unreleased financials, customer personal data, passwords, embargoed announcements.
  • Enter only in approved tools: internal strategy notes, unpublished drafts, brand guidelines.
  • Free to use: public information, your own published copy, generic briefs.

On copyright, decide in advance whether you allow AI-generated images in published work, who confirms licensing terms for the tool you use, and how you credit and label visuals. If you sell products online, add a line about product copy and photos; our guide to scaling AI product descriptions safely covers the ecommerce side.

How to build and maintain your own guideline

The CAJ recommends defining core principles, updating guidelines regularly, keeping human accountability, testing tools for bias and training staff continuously. A publisher governance playbook from April 2026 argues the best internal policies are operational guides built into onboarding and checklists, not aspirational documents. PMParrot adds that policies fail without capacity building, including training on prompting, spotting hallucinations and fact-checking.

Here is a sequence that works for a team of two or twenty.

  1. List your content types. Blog posts, social captions, product pages, press releases, video scripts, client reports. Each gets its own risk level.
  2. Set allowed, restricted and prohibited uses. For example: allowed for outlines and first drafts; restricted for statistics and quotes; prohibited for testimonials and anything under embargo.
  3. Name the accountable human. One editor or owner per piece, written into the workflow.
  4. Write the disclosure rule. Use the substance test above, and attach a standard sentence.
  5. Add the checklist. Paste the verification list into your content brief template so it travels with every draft.
  6. Approve tools. Keep a short list of tools the team may use and what data each may receive.
  7. Train and test. Run a one-hour session with real examples of errors the team has caught.
  8. Review on a schedule. Every quarter, or whenever your tools, laws or clients change.

Keep the whole document to two pages. If it is longer, nobody will open it at 4 p.m. on a deadline.

Fit the rules to your workflow

The guideline should describe the real path content takes, from keyword research to publishing. An AI-assisted content workflow saves time on research and planning, but each stage still needs a named human check. If you publish press materials, see our workflow for AI press release writing, and for marketing teams with brand and legal review, our AI brand compliance guide goes deeper.

Our perspective

We built AmmarAI around one conviction: speed is only worth having if the output is still yours. A guideline is how you keep it yours.

Most teams we talk to do not have an AI problem, they have a stack problem. Drafts come from one tool, images from another, voiceovers from a third, and nobody can say which model produced what or which version of the brand voice was applied. You cannot disclose, audit or correct what you cannot trace. That is why we put chat, writing, image, video and voice in one workspace, with one history, one brand voice and one bill. Our design aim is that your rules live in one place instead of five.

We also think a guideline should be easy to follow, which is why shared workspaces matter. When the whole team works from the same brand voice and the same asset library, the policy stops being a PDF and becomes how the work is done. Our position is simple: the tool drafts, a person decides, and your process shows it.

Ahmed

Put your guideline to work in one workspace

If you are writing a policy because your team uses several AI tools at once, consolidating makes the policy easier to enforce. AmmarAI brings writing, image, video, voice and code tools into one workspace with a saved brand voice and a single history of what was generated. Plans start with a free tier at $0 per month, then Starter at $9.99, Professional at $29.99 and Ultimate at $59.99 per month. See what each includes on the pricing page.

Ammarai

Teams that need shared assets and consistent output can look at team workspaces, and our multi-model approach lets you choose the right model for each task and keep a record of which one you used.

Template: a one-page AI editorial guideline

Copy this, replace the brackets and trim anything that does not fit your work.

Purpose. We use AI to work faster on [research, outlines, drafts, edits]. We do not use it to replace our judgment.

Accountability. Every piece has a named editor, [role], who approves it before publishing. AI is never listed as an author.

Allowed. Brainstorming, outlines, first drafts, rewriting for clarity, translation drafts, summaries of public material.

Restricted (human verification required). Statistics, quotes, legal or medical statements, comparisons, anything about named people or companies.

Prohibited. Fake reviews or testimonials, invented quotes or sources, uploading confidential or personal data to unapproved tools, passing off generated images as photographs.

Disclosure. When AI generated substantial content or shaped an editorial decision, we add: “[standard line].” Routine spelling and grammar help needs no label.

Verification. The checklist above is attached to every brief.

Tools. Approved tools: [list]. Data allowed in each: [list].

Review. [Owner] reviews this document every [quarter] and after any incident.

Common mistakes to avoid

  • Copying a newsroom policy wholesale. A newsroom’s rules assume reporters, editors and a standards desk. Adapt them to the people you have.
  • Banning everything. Blanket bans push use underground, where nobody checks it. Define safe uses instead.
  • Disclosing everything. Labeling a spellcheck dilutes the labels that matter.
  • Treating detectors as proof. They guess, and they cannot confirm a fact.
  • Writing it once. Tools and laws change. A dated, owned document survives; an orphaned one does not.

If your team produces video, the same rules apply to scripts, voiceovers and synthetic footage. Resources on AI-driven video production for marketers show where AI fits in a production pipeline, and each of those stages needs an owner under your guideline.

FAQ

Do I need AI editorial guidelines if I am a solo creator?

Yes, in a short form. A half-page covering what you will not enter into tools, how you verify facts and what you disclose to clients and audiences is enough. It also gives you a clear answer when a client asks how you use AI.

Should I disclose every use of AI?

No. Policies such as RNZ’s treat basic spelling and grammar correction as generally not needing disclosure unless it changes meaning. Disclose when AI generated substantial content, assisted reporting or research, or influenced editorial decisions, and keep the note proportionate.

Can AI be listed as an author?

Major publishing bodies say no. The STM Association recommends that AI not be credited as an author because a tool cannot be accountable for content. Credit the human who reviewed and approved the work, and describe the tool’s role in a disclosure note.

How often should we update our guidelines?

Review them at least quarterly and after any incident, new tool or legal change. The CAJ specifically recommends regular updates and ongoing staff training, so schedule both.

Sources

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