How Newsrooms Are Building with AI

The conversation around AI in journalism has shifted from speculation to implementation. Across newsrooms of every size, from major broadcasters to independent newsletters, AI tools are being integrated into daily workflows. But the gap between hype and practical adoption remains wide. Most journalists know AI exists. Far fewer know how to use it effectively without compromising the editorial standards their audiences depend on.

Research and Discovery

The most immediate and widely adopted use of AI in newsrooms is research acceleration. Tools like Perplexity, ChatGPT and Claude can synthesise background information, surface related stories and identify patterns across large datasets in seconds. Investigative journalists are using AI to process thousands of public documents, court records and financial filings that would previously take weeks to review manually.

The key principle is verification. AI-generated research summaries are a starting point, never a source. Every claim must be cross-referenced against primary documents. Newsrooms that have adopted this approach report significant time savings at the research stage without any reduction in accuracy.

Production and Repurposing

Content repurposing is where AI delivers the clearest return on investment for resource-constrained newsrooms. A single long-form article can be transformed into social media threads, newsletter summaries, audio scripts and video caption overlays using AI workflows. Transcription tools like Otter.ai and Descript have become standard in podcast and broadcast production, cutting post-production time by more than half.

At Other Labs, our AI workshops teach creators to build custom repurposing pipelines that maintain editorial voice across formats. The goal is not to automate writing but to eliminate the repetitive reformatting work that consumes hours each week.

Audience Intelligence and Distribution

AI-powered analytics are giving newsrooms new visibility into audience behaviour. Beyond basic pageviews, machine learning models can predict which stories will drive subscriptions, identify audience segments most likely to churn and recommend optimal publishing times. This data informs editorial strategy without dictating it.

Distribution is also evolving. AI tools can A/B test headlines, generate metadata for SEO and personalise newsletter content based on reader preferences. The newsrooms seeing the best results treat AI as an editorial assistant rather than a replacement for human judgment.

Building an AI-Ready Newsroom

Successful AI adoption requires more than subscribing to tools. It requires a cultural shift toward experimentation. Start with low-risk, high-reward workflows like transcription and social repurposing. Build internal guidelines around transparency and attribution. Train your team on prompt engineering fundamentals. The newsrooms that invest in AI literacy now will have a significant competitive advantage over those that wait.