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2025 wasn’t just another year of AI experimentation in the media industry. It forced the industry to confront a bigger question: what happens when AI stops being just a newsroom tool and becomes the layer audiences experience journalism through? That is the core question heading into 2026.
This week on Newsroom Robots, host Nikita Roy sits down with Francesco Marconi and Scott Austin for an end of year recap roundtable on what actually changed in AI and media in 2025 and what newsroom leaders need to prepare for heading into 2026.
Francesco is the co-founder and CEO of AppliedXL. He previously led R&D at The Wall Street Journal and built some of the earliest AI and newsroom automation systems at The Associated Press.
Scott leads business development at Symbolic.ai, an AI assisted publishing tool. He is also a journalist and digital media veteran who spent years at The Wall Street Journal as a reporter and award winning editor, and later led content partnerships at Dow Jones across major platforms.
This episode covers:
03:10 — Why 2025 was journalism’s operational reckoning year
08:55 — The shift from search to answers and why it breaks old business models
14:40 — Proactive AI and what ChatGPT Pulse reveals about the next distribution layer
20:30 — Journalism’s hidden work and why persistence, source building, and human judgment still matter
23:30 — Why news orgs must move upstream from content to structured knowledge
36:10 — AI agents: what they actually are, what they are not, and why transparency matters
41:20 — The overlooked shift: Model Context Protocol (MCP) and why it is a major newsroom disruption
51:05 — Predictions for 2026
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The Philadelphia Inquirer never had an AI engineer on staff until the Lenfest AI Collaborative & Fellowship program changed that.
The collaborative is a $5 million partnership between the Lenfest Institute, OpenAI, and Microsoft that placed 10 AI fellows in American newsrooms for two years. These engineers work within the organizations, building tools that solve real newsroom problems.
This week on Newsroom Robots, host Nikita Roy sits down with Jim Friedlich, CEO and Executive Director of the Lenfest Institute, David Chivers, lead advisor to the Lenfest AI Collaborative and Matt Boggie, CTO of The Philadelphia Inquirer, to walk through how the program works and what the Inquirer has built as a result.
The Inquirer came to the collaborative with an idea to build a full-archive search tool that would let reporters query decades of journalism. They expected it to take 24 months. Within two weeks of a Microsoft hackathon, they had working code. The tool, now called Dewey, searches everything the Inquirer has published since 1978.
This episode covers:
03:02 — How the Lenfest AI Collaborative got started
05:34 — Can newsrooms trust big tech partners?
08:33 — How the fellowship works day to day
14:52– Inside the Microsoft hackathon that built Dewey in two weeks
21:37 — Training journalists to understand LLM limitations
24:07 — How AI literacy has changed newsroom culture
29:45 – How small newsrooms can get started with AI
35:14 — AI answers, search decline, and the future of audience traffic
38:15 — Rethinking journalism’s role in an AI-mediated world
41:23 — Closing reflections and personal AI use
This episode of Newsroom Robots is supported by the Lenfest Institute for Journalism.
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This week on Newsroom Robots, host Nikita Roy is joined by Tav Klitgaard, the CEO of the Danish newsroom Zetland, to unpack the origin story of GoodTape — an AI transcription tool that began as an internal newsroom solution and evolved into a profitable, global product used far beyond journalism.
Zetland is an audio-first newsroom in Denmark. But GoodTape wasn’t born from an AI strategy or a product roadmap. It emerged from a familiar newsroom pain point of journalists spending hours transcribing interviews, with existing tools falling short, especially in non-English languages like Danish.
In this conversation, Tav breaks down how GoodTape went from an internal experiment to a standalone, subscription-based product that quickly became profitable, generated millions in revenue and was eventually divested. He also shares what building GoodTape taught Zetland about AI adoption, organizational learning, and where newsrooms should, and shouldn’t, use generative AI.
This episode covers:
05:50 – How a prototype using OpenAI’s Whisper sparked GoodTape
08:36 – The moment Zetland realized GoodTape could be a real product
12:34 – How journalism’s trust and privacy standards became a product advantage
13:59 – What actually improves transcription quality beyond the model itself
15:27 – How GoodTape became profitable and contributed to Zetland’s revenue
16:29 – Why Zetland eventually divested GoodTape instead of scaling it internally
17:36 – What building an AI product taught Zetland about newsroom AI adoption
19:08 – Why Zetland uses AI for productivity, not editorial output
28:14 – A real-world example of AI use that forced Zetland to rethink its own guidelines
30:34 – Why principles matter more than rigid AI rules in newsrooms
🎧 Listen to the full conversation with Tav Klitgaard on Apple Podcasts, Spotify, or your favorite podcast platform.
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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 our 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.
In this episode, we cover:
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:
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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:
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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:
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:
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:
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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In this live episode, host Nikita Roy sits down with Zach Seward, Editorial Director of AI Initiatives at The New York Times, recorded at the ONA x Newsroom Robots AI Leadership Summit in Detroit. With a background that spans journalism, product, and executive leadership, Zach brings a rare blend of newsroom insight and entrepreneurial thinking to the challenges of this AI era. Before joining the Times, he co-founded Quartz, where he served as editor-in-chief, CEO, and chief product officer, helping to pioneer digital-native journalism.
Now at The Times, he’s built a new editorial AI team from the ground up, experimenting with tooling, guiding newsroom adoption, and thinking through what comes next in how journalism is produced, distributed, and consumed.
Key topics include:
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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:
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When it comes to AI adoption, experimentation is easy—scaling is hard. So, what is the difference between AI projects that fade out and those that transform newsrooms? A strong infrastructure.
In this episode of Newsroom Robots, Kasper Lindskow, the head of AI at JP/Politikens Media Group joins host Nikita Roy. Kasper shares how as one of Denmark's largest media groups they are building a scalable AI infrastructure across multiple news brands, balancing technical innovation with editorial values.
Key topics include:
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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:
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.
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Translating a journalist's gut instinct into code—is it possible? In Norway, iTromsø—a long-standing regional newspaper known for its investigative journalism and deep local coverage—has found a way.
Their AI system, DJINN (Data Journalism Interface for News Gathering and Notification), acts like an experienced beat reporter, scanning hundreds of municipal documents and surfacing the most newsworthy leads. The impact? In their first week using DJINN, summer interns fresh out of journalism school produced five front-page stories—on a beat that usually takes years to master.
In this episode of Newsroom Robots, Rune Ytreberg and Lars Adrian Giske join host Nikita Roy to talk about iTromsø’s structured approach to AI-driven reporting and how they built tools that strengthen their local journalism.
Rune leads iTromsø’s data journalism lab, where he has been developing AI-driven editorial solutions for 70 local newspapers within the Polaris Media Group since 2020. And Lars is the Head of AI at iTromsø and led the development of DJINN. Since its launch in 2023, 36 newspapers across Norway have adopted DJINN, sourcing documents from nearly half of all Norwegian municipalities.
Key topics include:
•How a small newsroom built AI tools to strengthen investigative journalism
•Why their AI systems are designed for specific beats like urban planning and fisheries, reducing hallucinations and increasing precision.
•Embedding editorial expertise in AI development
•How their fisheries database flagged irregularities and how their urban planning system transformed local accountability coverage.
This is just Part 1 of our deep dive into how iTromsø is using AI to power investigative reporting. In Part 2, Rune and Lars will discuss their latest project: AI-powered research assistants that will proactively surface investigative leads for their journalists.
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Neil Brown, president of The Poynter Institute and former chair of the Pulitzer Prizes, joins host Nikita Roy to discuss the Pulitzer Board's decision to require AI disclosure in prize submissions. In 2024, two Pulitzer Prize winners disclosed using AI in their work - City Bureau and Invisible Institute used machine learning to analyze police misconduct files for "Missing in Chicago," while The New York Times' visual investigations desk employed AI to identify bomb craters in Gaza. Of the 45 finalists that year, five had disclosed using AI in their submissions.
In this episode, Brown discusses how the Pulitzer Board approached AI disclosure requirements and shares his perspective on technology's evolving role in journalism.
Key topics include:
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Upasna Gautam, Senior Platform Product Manger at CNN and Chair of the Board of Directors at the News Product Alliance, joins host Nikita Roy to discuss her framework for AI integration in newsrooms.
In this episode, Gautam breaks down her three-question approach to AI implementation and shares insights from building CNN's content management platform Stellar. Through practical examples from CNN's journey and her work with newsrooms globally, Gautam offers a systematic framework for evaluating which AI opportunities are worth pursuing.
Key topics include:
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