Newsroom Robots

How do you bring AI into a newsroom as big and globally distributed as the BBC, an editorial network that stretches across 42 languages and more than 5,000 journalists?This week on Newsroom Robots, host Nikita Roy talks to Olle Zachrison, Head of News AI at BBC News, where he leads the BBC’s efforts to advance AI use and strengthen its journalism and audience experiences. Previously, the Head of AI at Swedish Radio, Olle has spent the past few years implementing practical newsroom AI workflows while upholding public-service values.In this conversation, Olle breaks down BBC’s four-part AI strategy, covering large-scale translation and transcription, content reformatting, investigative tools, and early experiments with synthetic audio and conversational news. He shares what’s working inside one of the world’s largest news organizations, what routinely stalls AI projects, and why the most challenging part of AI transformation isn’t the technology but the collaboration required across editorial, product, and engineering. Olle also reflects on what it means to innovate as a public broadcaster in an AI-driven ecosystem, and why archives, credibility, and direct audience relationships will determine which journalism remains indispensable in the years ahead.This episode covers:03:39 – The BBC’s four-part AI strategy: Boosting productivity, reformatting content, augmenting journalism, and innovating user experience as the core themes05:10 – Using AI for large-scale transcription, tagging, live pages, alt text, newsletter production, and translation to save time and make content more searchable.08:17 – Reformatting content across platforms and formats20:59 – Innovating user experiences with synthetic audio and conversational formats31:59 – How the BBC uses strategic themes, clear metrics, and fast pilots to decide what’s worth building and scaling46:59 – Inside the BBC’s fine-tuned LLM and Style Assist52:01 – What it means to be a public broadcaster in an AI-driven ecosystem01:02:58 – Olle’s personal AI stackSign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.

How does a 182-year-old global magazine stay ahead in the age of generative AI? This week on Newsroom Robots, host Nikita Roy is joined by Ludwig Siegele, Senior Editor for AI Initiatives at The Economist. After more than 25 years reporting from San Francisco, Berlin, and London, Siegele now leads the publication’s AI strategy. He discusses how The Economist launched its AI Lab—a startup-style group within the organization with the freedom to test bold ideas and move quickly. The lab is charged with looking years ahead, preparing for a future where much of journalism’s supply chain may be automated, and ensuring The Economist maintains its identity in an AI-driven media ecosystem.From practical newsroom wins like AI-powered translation and research pipelines to more experimental projects such as TikTok video dubbing and the SCOTUS bot, Siegele explains how The Economist is testing, iterating, and learning in real time. He also reflects on what hasn’t worked, the challenges of newsroom adoption, and why the next phase of journalism may require redefining the role of the journalist itself.In this episode:00:00 – Introducing Ludwig Siegele & The Economist’s AI journey01:31 – How AI experimentation began at The Economist03:26 – Overcoming newsroom fear of ChatGPT04:53 – Building AI infrastructure and upskilling staff07:10 – The tools and vendor partnerships powering experiments08:29 – Why adoption is harder than building tools12:10 – Translation, research, and NotebookLM as newsroom game changers16:06 – How automation could reshape the journalist’s role18:41 – Launching The Economist AI Lab24:11 – Audience-facing AI experiments (TikTok dubbing, Espresso app, SCOTUS bot)26:05 – Partnering with Google NotebookLM while protecting the brand30:02 – Scraping, monetization, and the future of publisher revenue33:41 – Measuring ROI on AI initiatives37:40 – The biggest barriers to newsroom AI adoption39:14 – How Ludwig uses AI personally in art and culture40:40 – Closing reflectionsSign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.

As a new academic year begins, journalism schools face a defining challenge: how to prepare students for a profession being reshaped by AI.At Stanford University, Djordje Padejski is leading the way. A veteran investigative journalist and now associate director of the John S. Knight Journalism Fellowships at Stanford, he created one of the earliest AI-focused journalism courses at Arizona State University before bringing it to Stanford last year. His classroom is less lecture hall and more lab, where students test AI tools and also learn to examine them.On Newsroom Robots, Djordje shared how he structures his course and what journalism schools must do to prepare the next generation of journalists.Key topics include:Why journalism education must move beyond teaching AI as just a tool and instead frame it as a socio-technical phenomenon.How to embed AI literacy in classrooms by separating hype from reality, contextualizing the history of AI, and examining its cultural and ethical limits.Practical strategies Djordje uses to structure his Stanford course, from lab-style experimentation to peer-led discussions that uncover both opportunities and pitfalls of tools like ChatGPT, Perplexity, and NotebookLM.The importance of teaching students not just how to use AI but how to critically assess its strengths, biases, and limitations.What a future journalism curriculum or degree built around AI might look like, and how educators across disciplines can prepare the next generation of reporters.Sign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.

What if the future of journalism isn’t locked behind the paywalls of big tech companies, but freely available to every newsroom willing to embrace it?Too often, the conversation around AI in newsrooms centers on big tech, like OpenAI’s ChatGPT or Google’s Gemini. These are powerful tools, no doubt but they come with caveats: mainly cost, limited transparency, and little to no control over where your data ends up.But there’s another world of AI rapidly evolving in parallel and it might be journalism’s best path forward: open-source AI.In this episode of Newsroom Robots, host Nikita Roy reconnects with returning guest Florent Daudens, now the Press Lead at Hugging Face, one of the leading platforms powering open source AI. Formerly a newsroom leader driving AI integration at Canada’s Radio-Canada, Florent now sits at the heart of the open source AI movement.Key topics include:Why open source AI matters for journalism and how it compares to proprietary modelsThe rise of AI agents and what they mean for editorial control and user experienceHow compressed, privacy-first models running on laptops and phones could change the gameThe environmental cost of AI and how newsrooms can make more sustainable tech choicesWhat news apps might look like in an agent-powered futureHow newsrooms can start experimenting with open source AI (no dev team required)Plus, Florent shares 20 must-know open source AI tools for journalists, explains how writing is building in the age of AI, and discusses why owning the experience, not just the content, will be key to journalism’s survivalSign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.

In this live episode, host Nikita Roy sits down with Gina Chua, Executive Editor of Semafor, recorded at an event at New York University hosted in collaboration with the AI networking group, Humans in the Loop. Gina brings a uniquely expansive lens to the AI conversation, grounded in her leadership across global newsrooms—from Reuters and The Wall Street Journal to the South China Morning Post. Now at Semafor, she continues to be a leading voice rethinking the information ecosystem for an AI-driven world.In this wide-ranging and candid conversation, Gina explores how generative AI is reshaping the fundamental architecture of journalism—from editorial workflows and business models to the core definition of a story. She discusses her team’s experiments with building custom AI tools like Miso, a multilingual aggregation system powering Semafor’s Signals format. Key topics include:How Semafor is using AI for multilingual search, editorial summarization, and style guide enforcement built directly into Google Suite workflows using App Scripts and Claude.The challenges of building durable AI products in newsrooms including unstable models, integration hurdles, and evolving use cases.Rethinking the role of journalists in an AI world: where value lies in asking the right questions, building audience understanding, and creating narratives only humans can shape.The importance of reframing journalism’s mission not as saving “journalists” or “journalism,” but as delivering information in the public interest.Behind-the-scenes on JESS (Journalist Expert Safety Support), a chatbot Gina prototyped and co-developed to democratize access to field safety guidance for reporters worldwide.Why the future of news depends on tight, authentic relationships with audiences and how startups like Semafor are designing for trust, voice, and community from the ground up.The episode closes with reflections on Gina’s personal coding journey with AI including her work building an assistive tool for a friend with ALS.Sign up for the Newsroom Robots newsletter for episode insights and updates from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.

When officials in Santa Clara County (home to Silicon Valley) publicly proclaimed they were not sharing data with U.S. Immigration and Customs Enforcement, they likely did not expect to be caught in a contradiction. Yet behind the scenes, those same officials had recently signed new contracts with the federal agency — a fact that might have remained hidden if not for a new generation of AI tools developed at Stanford University.This breakthrough was made possible by Big Local News, a Stanford-based initiative using AI to help local journalists uncover stories hidden deep within public records. As local newsrooms grapple with shrinking resources and overwhelming amounts of data, tools like these are helping restore investigative capacity where it’s needed most.In this episode of Newsroom Robots, Cheryl Phillips, founder and co-director of Big Local News at Stanford University, joins host Nikita Roy to share how her team is building AI-powered tools that support watchdog journalism and make complex data more accessible to reporters across the country.Key topics include:Agenda Watch, a tool that scrapes and indexes public meeting agendas to surface early signals of newsworthy developments across thousands of local agencies.DataTalk, an AI assistant that turns natural language questions into campaign finance data queries, simplifying analysis for journalists without coding expertise.The use of generative AI and large-scale scraping systems to analyze police misconduct records and create public-facing accountability databases.How Big Local News uses Slack-integrated bots to deliver real-time alerts on layoffs and problematic fiscal audits to local newsrooms across the U.S.Sign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.

Imagine a newsroom where AI agents assist with reporting, actively surface leads, analyze government data, and help journalists navigate complex investigations in real time. Norway’s iTromsø is laying the groundwork for exactly that.In the second part of this episode with Rune Ytreberg, head of data journalism at iTromsø, and Lars Adrian Giske, head of AI join host Nikita Roy to share how their small but ambitious newsroom is systematically building an infrastructure for AI-powered journalism. This isn’t just about isolated tools—it’s about creating a cohesive ecosystem where AI enhances reporting at every level.Rather than simply bolting AI onto existing workflows, iTromsø is focused on building a structured data infrastructure that supports AI agents across multiple newsroom functions.Their vision includes:A centralized AI-powered data interface that allows journalists to filter, analyze, and cross-reference government records, public documents, and municipal archives.Automated news alerts that notify reporters when AI detects important patterns or anomalies in the data.A structured repository of historical data, ensuring journalists have context-rich information at their fingertips, allowing for deeper investigative work.This structured approach isn’t just about efficiency—it’s about creating a foundation where AI can play an active role in surfacing critical stories.iTromsø is designing an AI-ready newsroom—one where structured data, automated insights, and AI-assisted research come together to elevate investigative journalism.Sign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy. Hosted on Acast. See acast.com/privacy for more information.