EmergingMedia, journalism, entertainment and gaming AI

Journalism AI Workflow Editor

Also called AI News Editor

A Journalism AI Workflow Editor designs and runs the editorial process around AI assistance, so reporting stays accurate and accountable. They protect trust, which is the thing a news product cannot afford to lose.

What they do

They map where AI touches reporting, from research and transcription to drafting and summarising. Then they set the checks around each step. They write verification rules, decide what needs a named human sign-off, and test model output against sources. They check provenance on images, audio and video. They keep records of what was verified, by whom, and how errors were corrected. They work with reporters, product teams and legal on licensing and rights. They also review failures and change the workflow when something slips through.

What a strong hire delivers

In the first months, a strong hire delivers a clear map of where AI is used in editorial work and where it should not be. They put in place a working verification process with named owners and a correction log. They set up a way to measure source accuracy and serious editorial errors. Staff know what is allowed, what needs review, and how to report a problem.

How you can tell they are good

Ask them to walk through a workflow they built or changed. Look for specific checkpoints, not general principles. Ask for a real error, how it was found, and what changed afterwards. Give them an AI-assisted draft with planted mistakes and watch how they check it. Strong people talk about sources first and tools second.

Why it is hard to fill

The title barely exists yet. The work is usually done by a standards editor, a product editor or a producer who took it on because nobody else would. Few people combine newsroom verification discipline with hands-on model evaluation. Candidates often have one half and need to show the other. Titles vary widely, so searching by title misses most of them.

Where to find them

Look at newsroom standards and verification desks, fact-checking teams, and audience or product editors who have shipped AI features. Others come from media production, game development and creative technology, where they handled generative media and rights questions. Publishers, broadcasters, news start-ups and studios are the usual homes. Open-source investigation and trust and safety teams also produce good candidates.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Journalism AI Workflow Editor

  1. Describe an editorial workflow you built or changed to include AI assistance. What checks did you add and why?

    A strong answer names specific steps, owners and sign-offs, and explains the risk each one covers. Worry if they describe a tool rollout, a policy document with no checks, or give no example of something that changed.

  2. Tell us about a consequential error that reached publication or nearly did. How was it found and what changed?

    Look for honesty, a clear account of cause, and a concrete fix such as a new check or record. Worry if they blame the tool, cannot recall a real case, or claim errors never happened.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are looking for an editor to shape how AI supports our reporting and production. You will set the checks, keep the records and make sure what we publish stays accurate and accountable. The work sits between editorial, product and legal teams.

What you will do

  • Map where AI is used across editorial and production work
  • Design verification steps and sign-off rules for AI-assisted content
  • Test model output against sources and record the results
  • Check provenance and rights on generated and third-party media
  • Maintain verification and correction records
  • Track source accuracy and serious editorial errors, and act on what they show
  • Train editorial staff on approved use and escalation

What you will bring

  • Demonstrated experience verifying information in a newsroom or similar setting
  • Examples of workflows you have designed or improved
  • Practical experience evaluating AI model output
  • Working knowledge of copyright, licensing and attribution
  • Clear writing and the ability to explain risk to non-specialists
  • Comfort working with reporters, engineers and lawyers

Nice to have

  • Experience with retrieval systems or agent frameworks
  • Background in game development or media production
  • Experience with provenance and authenticity checking

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Generative mediaAdvancedProduce controllable visual, sound or spatial outputs
  • Intellectual property and licensingAdvancedAssess rights in training inputs and generated outputs
  • Information integrityWorkingAssess manipulated content and evidential authenticity
  • Model evaluationWorkingMeasure capability and failure modes credibly

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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