Introduction
AI in media and journalism is now part of daily newsroom work, yet many editorial teams adopt drafting, transcription and translation tools without agreed rules, and audiences notice when AI output is published unchecked. This Core Concept course gives journalists, editors, producers and content teams hands-on practice with AI tools across the news cycle, from story discovery and subtitling to archive tagging and audience analytics, under clear editorial guidelines and disclosure rules. Participants work in labs on newsroom material and leave with a Newsroom AI Adoption Plan for their own media unit.
Course Objectives
- Map where AI tools can support newsgathering, production, distribution and archiving in a media unit, and where human editorial judgement must remain
- Use generative AI to draft, summarise, headline, translate and subtitle news content with a documented human review step
- Apply AI-assisted transcription, audio and video editing and automated tagging to speed up production and archive search
- Verify AI-generated text, images and quotes with a structured fact-checking routine before publication
- Write an editorial AI policy covering disclosure, accountability, copyright and bias, based on the Paris Charter on AI and Journalism
- Produce a Newsroom AI Adoption Plan with prioritised use cases, controls and success measures
Target Audience
- Reporters and correspondents who gather, write and file news stories
- Editors and sub-editors responsible for checking, headlining and publishing content
- Broadcast and digital producers who edit audio, video and multimedia packages
- Archive, library and media asset staff who catalogue and retrieve content
- Communications and content staff who produce news-style material for their organisation
- Audience and digital desk staff who track readership and distribute content
Course Outline
Day 1: AI Across the News Cycle
- Automated Journalism Landscape: Earnings, Sports and Weather Story Generation
- Newsroom AI Use-Case Map: Newsgathering, Production, Distribution and Archive
- Human-in-the-Loop Editorial Model and Decision Points
- Audience Attitudes to AI in News from the Reuters Institute Digital News Report
- Media Unit AI Readiness Assessment Template
Day 2: Editorial Frameworks for Responsible AI Use
- Paris Charter on AI and Journalism: Ten Principles Applied to Daily Work
- AP Stylebook Guidance on Labelling AI-Generated Material
- BBC Machine Learning Principles and Public Service Checklists
- Editorial Accountability and Byline Attribution Rules for AI-Assisted Stories
- AI Disclosure Statement Templates for Text, Audio and Video
Day 3: Generative AI Tools in Newsroom Production
- Story Drafting and Summarisation with Chat Assistants and a House Style Brief
- Headline and Standfirst Variants with Editor Review Checklist
- Machine Translation and Arabic-English Subtitling Workflow
- Speech-to-Text Transcription of Interviews and Press Conferences
- AI-Assisted Audio Clean-Up and Video Rough-Cut Editing
Day 4: Verification, Archives, Audiences and Risk
- Fact-Checking Routine for AI Output: Fabricated Quotes, Sources and Figures
- Reverse Image Search and Metadata Checks on Synthetic Images
- Automated Tagging and Semantic Search for Media Archives
- Recommendation and Personalisation Settings That Protect Information Diversity
- Copyright, Source Protection and Bias Risk Register for Newsroom AI
Day 5: Newsroom Lab and the AI Adoption Plan
- Breaking News Lab: From Press Release to Verified Bilingual Story
- Broadcast Lab: Transcribed Interview to Subtitled Video Package
- Use-Case Prioritisation Matrix: Value, Risk and Effort
- Newsroom AI Adoption Plan Drafting with Training and Success Measures
- Peer Editorial Board Review of Adoption Plans
Skills You Will Gain
- Newsroom AI Workflow Design
- AI-Assisted News Writing
- Automated Subtitling and Translation
- Synthetic Content Verification
- Media Archive Tagging
- Editorial AI Policy Drafting
- Audience Personalisation Oversight
- AI Use Disclosure
Why Attend This Course
- Return with a Newsroom AI Adoption Plan that sets out which tools your unit will use, for what, and under which controls
- Cut the time spent on transcription, subtitling and first drafts while keeping an editor accountable for every published item
- Answer audience and management questions about AI use with a written disclosure and editorial policy
- Compare newsroom practice with peers from broadcasters, publishers, agencies and corporate communications teams
Conclusion
AI tools only strengthen journalism when editors stay accountable for what is published and audiences are told how content was made. This course moves from mapping AI across the news cycle, through editorial frameworks such as the Paris Charter, to hands-on drafting, translation, subtitling, transcription and archive tagging, then to verification, personalisation and copyright risks. The final day applies these skills in newsroom labs and produces a Newsroom AI Adoption Plan that participants take back to guide tool choices, controls and training in their media unit.
