There is no reliable style-only test established by the sources here for deciding whether an unlabeled news story was written by AI. To judge an article, look instead for a specific AI-use disclosure, an identifiable human responsible for verification, traceable evidence, and a clear corrections process. Those clues help you assess how the story was produced and who stands behind it; they do not prove who wrote each sentence.
What “AI-written” can mean
AI use in a newsroom ranges from support work to AI generating most of an article. Those are materially different processes, so a generic “AI was used” label may not tell readers what they need to know.
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- Support tasks: transcription, translation, spelling and grammar editing, or summarizing documents.
- Substantial production: AI drafting article text, generating images, or otherwise making a material contribution to published content.
- Human-led work with AI assistance: a journalist directs the reporting and remains responsible for checking the tool’s output.
- AI-led work with human oversight: AI produces most of the content, with a person reviewing it before publication.
The distinction matters to audiences. A Reuters Institute survey reported in 2024 found that 47% wanted disclosure when AI wrote article text, compared with 32% when AI edited spelling and grammar. Those figures reflect the surveyed respondents’ expectations, not a universal rule for every reader or newsroom. Reuters Institute, Digital News Report 2024.
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1. Look for a specific disclosure
A useful disclosure says what AI did: drafted text, summarized documents, translated or transcribed material, edited copy, or generated an image. A broad label alone may leave the extent of AI’s contribution unclear.
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The Associated Press’s updated newsroom standards, announced July 23, 2026, offer one example of a policy that separates support tasks from material AI contributions. AP says journalists review and edit AI-generated output for its listed assistance uses, including early-stage research, document summarization, transcription, translation, headline and summary suggestions, grammar, spelling, and search optimization. Its policy requires disclosure when generative AI plays a material role in published content. This is AP’s policy, not a universal industry standard. Associated Press, updated newsroom standards.
2. Find the human responsibility
Check whether a reporter or editor is named and whether the outlet explains who verified the material. AP says: “Editorial judgment, verification and accountability remain the responsibility of AP journalists.” That statement describes AP’s policy; it does not establish that every newsroom follows the same approach or that a particular article was checked adequately.
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3. Follow the evidence behind consequential claims
Look for links to original documents, data, named sources, or other evidence that lets you check important claims. A visible sourcing trail can make a story easier to evaluate whether or not AI assisted with it. It does not, by itself, identify the story’s authorship.
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4. Check how images are described
Ask whether an image is documentary evidence, an illustration, or generated or altered material. AP’s policy prohibits generative AI from creating, altering, or enhancing news photography. It also says generated or manipulated material used in AP journalism must be identified and contextualized. Other outlets may have different policies, so check the explanation attached to the image and the outlet’s own standards.
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5. Look for a policy and a corrections route
An accessible AI policy can explain which tasks an outlet permits and how it checks output. A clear way to report an error—and a record of corrections—helps show how the outlet handles mistakes. These are accountability signals, not guarantees that an article is accurate or error-free.
What audience surveys say about AI in news
The Reuters Institute’s 2025 report surveyed people in Argentina, Denmark, France, Japan, the United Kingdom, and the United States. In those six markets, 12% said they were comfortable with fully AI-generated news, compared with 62% for entirely human-made content. Respondents were generally more comfortable when human journalists led and AI assisted, though comfort varied by country and task. These results describe the surveyed markets, not readers everywhere. Reuters Institute, Digital News Report 2025.
In that same report, 33% of respondents believed journalists always or often check AI output before publication. This is what respondents thought, not an audit of newsroom review practices. The report also found that 19% said they saw newsroom AI labels daily and 28% weekly, while 77% said they consumed news daily; those label figures are self-reported survey answers, not a count of labeled articles.
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A separate Reuters Institute report from 2024 found that people were generally less uncomfortable with AI assisting journalists—for example, with transcription or research summaries—than with content produced mostly by AI under some human oversight. It also reported differences by country and age. Reuters Institute, Digital News Report 2024.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why prose style cannot settle authorship
The sources cited here do not establish a reliable way for readers to identify AI authorship from the wording or style of an unlabeled article. A story that feels polished, repetitive, or generic is not proof that AI wrote it; a natural-sounding passage is not proof that a human wrote it. Treat style-based guesses and AI-detector results as unverified for this purpose unless they are supported by separate evidence.
Survey findings can describe what audiences prefer or believe, but they do not rank individual outlets or establish the quality or authorship of a particular story. For an individual article, disclosures, named responsibility, and checkable evidence provide more useful grounds for evaluating its process and accountability than a guess based on prose.
A quick comparison checklist
When comparing two stories or outlets, ask the same questions of each:
Quick Recap
- Who led production? Did a journalist lead with AI assistance, or did AI generate most of the text under human oversight?
- What did AI do? Was it a support task, substantial drafting, image generation or alteration, or another material contribution?
- What is disclosed? Does the note identify the task, or only say that AI was involved?
- Who is accountable? Is a journalist or editor identified, and does the outlet explain review and corrections?
- Can you check the claims? Does the story link to primary documents, sources, or data?
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