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Disclose AI when it materially shapes published content or when your publisher’s policy requires it. Say what the tool did, what part of the work it affected, and what a human actually checked. There is no single disclosure rule for every newsroom or publisher, so apply the organization’s current policy and make meaningful audience-facing contributions clear.
When should you disclose AI assistance?
Start by checking your publisher’s current policy, any applicable contract or rule, and the role AI played in the specific work. A practical threshold is whether AI output became part of the published words, image, audio, translation, analysis, or recommendation—and whether its contribution could change meaning, accuracy, framing, or an editorial decision.
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- Usually merits a content-level disclosure: generated or substantially transformed material that readers or viewers encounter, such as an AI-assisted translation that could change meaning, generated text, or synthetic audio.
- May be covered by an outlet-level policy: routine, low-impact backstage support, such as spelling assistance, when it does not materially shape the published work and policy does not require a specific note.
- Always check policy: the same task may be treated differently by different publishers, media, or jurisdictions.
This is a practical framework, not a universal industry standard. For example, the Associated Press says disclosure standards apply when generative AI plays a material role in published content, while BBC guidance calls for audience signals for certain techniques. A UK Parliament briefing reports that Impress recommends attributing AI use in content generation unless there is good reason not to.
What should an AI disclosure say?
Describe the actual contribution rather than naming a tool without context. Include the task, the material it affected, and the human review or verification that really occurred. Add relevant limitations or risks when they help readers understand the work.
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A flexible template is:
We used [tool or type of AI] to [specific task] for this piece. [Describe what material it affected.] A journalist/editor [describe the actual review and verification].
For example, if accurate: “We used an AI tool to translate this article from English into Spanish. A member of our Spanish-language staff edited the translation before publication.” This is an example of wording, not a prescribed formula.
- Do not say “fact-checked” or “reviewed by an editor” unless that work took place.
- Do not imply AI generated the entire piece if it only helped with a limited production task.
- Do not hide substantial generated material behind a vague statement such as “AI was used.”
Where should the disclosure appear?
Place a content-specific note close enough to the relevant work that readers can tell what it describes, and use plain, accessible language. An outlet-level policy can explain recurring background practices. Depending on format and policy, disclosure may be direct at the point of consumption or indirect through policy information or metadata; the UK Parliament briefing describes both approaches in its summary of BBC guidance.
How do newsroom policies differ?
Published standards illustrate why a single wording or threshold cannot be assumed across organizations. These are examples of those organizations’ policies, not rules that automatically apply to other publishers.
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Associated Press
In its newsroom standards updated July 23, 2026, AP permits listed assistive uses including early-stage research and document summarization, transcription and translation, headline and summary suggestions, grammar and spelling assistance, and search optimization. It says journalists review and edit AI output; AI does not replace reporting, sourcing, editorial judgment, or verification. AP says generative AI’s material role in published content triggers disclosure under its standards, and it continues to prohibit generative AI from creating, altering, or enhancing news photography. In a May 8, 2024 explanation, AP said it would clearly indicate AI use in English-to-Spanish translations because translation can materially change a story; its example is not a universal rule for other newsrooms. AP newsroom standards · AP explanation of its AI use
Reuters
Reuters says it embraces generative AI while retaining editorial accountability for all output and committing to transparency about its use. Its standards say generative AI must not create or enhance visual journalism imagery. The policy page does not give one disclosure formula for all text assistance. Reuters and generative AI
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BBC
BBC guidance says generative AI should not directly create news, current affairs, or factual content published or broadcast by BBC News/Nations unless AI is the subject and its use is illustrative. AI may support production or research under human editorial oversight, with output assessed before use; certain techniques should be signalled to audiences. Synthetic voices that are not of a real person must be clearly disclosed. Cloning a real person’s voice should not normally occur without consent, absent strong editorial justification and safeguards. These are BBC-specific requirements. BBC guidance on generative AI
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesImpress and UK publisher guidance
The UK Parliament House of Commons Library’s January 20, 2026 briefing summarizes an Impress best-practice note from April 2025. It says publishers should attribute AI use in content generation unless there is good reason not to, and explain the tool’s purpose and scope, potential limitations and risks, and effects on newsgathering, editorial decisions, and published content. The briefing says Impress does not prescribe exact wording. House of Commons Library briefing on AI and the news media
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How can a publisher set a consistent policy?
For recurring use, establish an outlet-level policy rather than asking each writer to improvise. The Thomson Reuters Foundation’s April 2025 guide suggests a process that can help publishers develop one:
- Inventory the AI tools in use and the tasks for which they are used.
- Identify risks to journalistic standards and define how those risks will be mitigated.
- Monitor the policy and tools over time, improving the approach as practices change.
Set clear thresholds for when routine support needs only policy-level explanation and when a particular piece needs its own note. This is a practical synthesis of the guidance, not a binding standard. Thomson Reuters Foundation guide for newsrooms
What should you verify before publishing?
A disclosure explains AI’s role; it does not make the work accurate or responsible by itself. Before publication, check the underlying work and the risks of the tool and task.
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- Accuracy: verify claims and source material independently. AI can produce fabricated or inaccurate information; BBC guidance highlights hallucination risk and calls for human oversight.
- Privacy and rights: consider whether entering material into a tool could expose private or confidential information, whether data may be shared or used for training, and whether copyright or other rights are implicated.
- Images and audio: treat synthetic or altered material as a distinct editorial issue, not ordinary reporting material. AP and Reuters prohibit generative AI imagery in their respective visual journalism standards; BBC sets specific safeguards for synthetic and cloned voices.
- Accountability: identify the person or editorial role responsible for the review and describe only checks that actually happened.
- Rules that apply to you: newsroom standards are not a substitute for checking relevant laws, publisher contracts, academic rules, or platform terms.
Does disclosure make readers trust a story more?
Do not promise that a label will increase trust. A Reuters Institute author reviewing 13 editorial AI guidelines reported that most invoke transparency but often do not define what it means in practice, and wrote that “we lack any evidence that transparency alone bolsters trust.” The article also warns that labels can affect perceived accuracy and sharing. This is an evidence limitation, not proof that disclosure harms trust.
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