How do you redesign a newsroom’s entire workflow when AI is no longer a single tool, but a collection of agents, voice interfaces, and ambient intelligence changing how journalism gets produced?

This week on Newsroom Robots, host Nikita Roy is joined by Markus Franz, Chief Technology Officer at Ippen Digital, one of Germany’s largest digital media networks with more than 80 online news and media portals. This episode was recorded live at the Digital Growth Summit in Stuttgart, where Markus shared how his team is building some of the most forward-looking AI experiments in European media.

Markus leads Ippen Digital’s Incubator Lab, an innovation unit focused on reimagining how publishing and AI-driven experiences will evolve. With 16 years inside the company, Markus has been central to Ippen’s digital transformation and now leads efforts around multi-agent architectures and building adaptive workflows for the newsroom.

In this conversation, Markus breaks down how his lab is experimenting with multi-agent “virtual teams,” voice-first newsroom interfaces, multimodal content production and an ambient AI-powered newsroom where intelligent systems support journalists in real time. He shares what his team has learned from early prototypes, why the biggest challenges are cultural rather than technical, and how news organizations should think about guardrails, platform dependency, and the rise of self-evolving models.

This episode covers:

02:22 – Why Ippen Digital built an Incubator Lab and how it’s structured as a future-focused R&D unit

04:49 – What multi-agent systems look like inside a newsroom

9:42 – The case for voice as the next major interface for both journalists and audiences

14:41 – The shift from human-in-the-loop to human-on-the-loop workflows

17:40 – Guardrails for agent systems: grounding, bounding, editorial policies

19:33 – The vision for an ambient newsroom powered by AI companions and real-time intelligence

27:31 – Why vendor lock-in and self-evolving LLMs pose new strategic risks

30:08 – Multimodal personalization and rethinking how news is experienced

34:27 – Why most AI pilots fail and what experimentation looks like in practice

49:19 – Markus’s personal AI stack and how he uses these tools day-to-day

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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 themes

05:10 – 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 formats

20:59 – Innovating user experiences with synthetic audio and conversational formats

31:59 – How the BBC uses strategic themes, clear metrics, and fast pilots to decide what’s worth building and scaling

46:59 – Inside the BBC’s fine-tuned LLM and Style Assist

52:01 – What it means to be a public broadcaster in an AI-driven ecosystem

01:02:58 – Olle’s personal AI stack

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This week on Newsroom Robots, host Nikita Roy sits down with Vilas Dhar, President of the Patrick J. McGovern Foundation, one of the world's foremost philanthropies advancing AI for public good. Dhar leads a $1.5 billion endowment that has committed over $500 million to projects spanning climate action, public health, education, and democratic governance. He has served on the UN Secretary-General's High-Level Advisory Body on AI, is the U.S. government's nominated expert to the Global Partnership on AI, and was named a World Economic Forum Young Global Leader in 2022.

Across philanthropy, policy, and technology, Dhar carries one central conviction: technology may accelerate, but the future of journalism and society must remain human-centered. Dhar introduces a three-part framework for ethical AI deployment (responsible data, clear boundaries, and transparency) and explains how to translate abstract principles into concrete newsroom decisions. He unpacks his LISA framework (Listen, Involve, Share, Assess) for audience-centered AI design, and tackles the hardest questions facing newsroom leaders: Should we buy or build AI tools? How do we balance innovation with environmental sustainability? What happens to human creativity when machines can create?

But perhaps most powerfully, Dhar challenges a deeply held belief in journalism: that media organizations can remain ‘just’ media companies in an AI-driven world. There is no way to be a media organization today without also being a technology organization, he argues, and that shift requires not just new tools, but a fundamental reckoning with organizational identity and purpose.

This epiosde covers:

00:31 – Introducing Vilas Dhar and his human-centered AI vision: Why technology should serve dignity, equity, and democracy—not just profit

02:17 – The three-part framework for ethical AI: Responsible data, clear boundaries, and transparency as actionable principles

07:08 – Questions leaders must ask before deploying AI: Who's involved? Who's accountable? Who has editorial control over AI use?

10:16 – The LISA framework: Listen, Involve, Share, Assess to turn AI experimentation into behind-the-scenes reporting that builds public trust

13:30 – Navigating ethical dilemmas around AI-generated content

13:51 – The three phases of newsroom AI adoption

18:54 – Why "we're not a tech company" no longer works

23:12 – Organizational reckoning in an 18-month transformation cycle

25:23 – Why smaller, targeted models and collective action matter more than massive systems

29:14 – Fighting misinformation with AI

34:13 – What journalism is missing compared to other industries

37:01 – The evolving role of human creativity and agency

39:33 – The McGovern Foundation's North Star

44:23 – How Vilas uses AI personally

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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 journey

01:31 – How AI experimentation began at The Economist

03:26 – Overcoming newsroom fear of ChatGPT

04:53 – Building AI infrastructure and upskilling staff

07:10 – The tools and vendor partnerships powering experiments

08:29 – Why adoption is harder than building tools

12:10 – Translation, research, and NotebookLM as newsroom game changers

16:06 – How automation could reshape the journalist’s role

18:41 – Launching The Economist AI Lab

24:11 – Audience-facing AI experiments (TikTok dubbing, Espresso app, SCOTUS bot)

26:05 – Partnering with Google NotebookLM while protecting the brand

30:02 – Scraping, monetization, and the future of publisher revenue

33:41 – Measuring ROI on AI initiatives

37:40 – The biggest barriers to newsroom AI adoption

39:14 – How Ludwig uses AI personally in art and culture

40:40 – Closing reflections

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In Estonia, Delfi Meedia has built one of the strongest foundations for AI in journalism. With one of the highest digital subscription rates in the world, Delfi has moved beyond the buzz around AI to put it into everyday practice, supporting both its journalism and business.

In this episode, host Nikita Roy is joined by Ivar Krustok, Chief AI & Innovation Officer at Delfi Meedia. Ivar breaks down how a small-market publisher is shipping AI that actually helps journalists: from live cross-language translation and newsroom bots to an in-house “company ChatGPT” toolkit wired into 25 years of archives and public records.

Key topics include:

•Delfi’s three-bucket AI strategy: everyday newsroom tools, experimental long-term projects, and company-wide literacy.

•Why Delfi built its own “company ChatGPT” toolkit to search 25 years of archives.

•How bots and agents are transforming dashboards into conversational tools for subscriptions, ads, and editorial performance.

•Lessons from AI experiments, from court-case monitoring that surfaces hidden stories to audience-facing image generators.

•The ongoing challenge of scaling AI literacy across hundreds of staff while keeping adoption practical and trust-centered.

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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.

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In this episode, host Nikita Roy  is joined by Sara Beykpour, co-founder and CEO of Particle News — the AI-powered news aggregator. Launched in November 2024, Particle blends multi-perspective coverage, concise AI-generated summaries, and a bias meter that makes framing visible, giving readers both speed and trust in the same experience.

Key topics include:

• How Particle’s “Reality Check” process works using multi-source input and verification passes to minimize hallucinations and produce more accurate summaries.
• Strategies Particle uses to maintain reader trust in an era when AI-generated summaries can quickly erode it.
• How Particle surfaces bias with a meter that shows how coverage leans left, right, or center and updates as stories develop.
• The role of topic-based personalization in avoiding filter bubbles while still giving readers tailored news feeds.

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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 models
• The rise of AI agents and what they mean for editorial control and user experience
• How compressed, privacy-first models running on laptops and phones could change the game
• The environmental cost of AI and how newsrooms can make more sustainable tech choices
• What news apps might look like in an agent-powered future
• How 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 survival

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In this live episode of Newsroom Robots, host Nikita Roy moderates a panel discussion recorded at the Nordic AI and Media Summit in Copenhagen. The conversation features Gard Steiro (Editor-in-Chief and CEO of VG in Norway), Fabian Heckenberger (Managing Editor and Senior Editor for AI at Süddeutsche Zeitung in Germany), and Naja Nielsen (Media Director at SVT in Sweden and former Digital Director at BBC News).

They discuss how news organizations are approaching the complexities of integrating AI into editorial workflows, organizational strategy, and audience experiences. The conversation focuses on the tensions, trade-offs, and open questions that newsroom leaders are wrestling with.

Key topics include:

• How AI is shifting from isolated projects to infrastructure across newsroom operations, and the implications for leadership and cross-functional teams.
• Why VG uses a fixed one-year runway model to evaluate AI experiments, and what happens when projects don’t deliver measurable outcomes.
• The role of transparency and relevance in building trust with audiences, particularly for younger and emerging user groups.
• SVT’s approach to organizational learning, including how leadership can empower experimentation without centralizing all decision-making.
• What interdisciplinary teams look like in practice—drawing on SZ’s experience embedding editorial staff into product and tech teams.
• Challenges with prioritization: choosing between maintaining legacy systems, launching new GenAI tools, or refining user experience.
• Why personalization can’t rely on a human-in-the-loop model, and how AI agents may soon take on quality assurance roles within content pipelines.
• Emerging revenue considerations: from small-scale funding streams and philanthropic support to fundamental questions about what people are actually willing to pay for.

The episode wraps with a candid exchange about whether the article format has outlived its usefulness in an era of personalized, multimodal news delivery and what that means for the future of storytelling and journalistic impact.

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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.

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