Newsroom Robots

Chicago Public Media operates two distinct news brands: WBEZ, the public radio station, and the Chicago Sun-Times, the legacy newspaper. With audio and print journalism, both membership and advertising revenue, and decades of archives in multiple formats, they're a unique case study for AI in local news.

When CEO Melissa Bell joined the organization, there was interest in AI but no dedicated resources for experimentation. Through the Lenfest AI Collaborative, they brought in their first AI engineer. A year later, Spanish translations that used to take days are now published the same day. Forty years of WBEZ audio, previously unsearchable, are being transcribed and made searchable for journalists.

In this week's episode, host Nikita Roy speaks with Chicago Public Media leaders Melissa Bell (CEO) and Aron Pilhofer (Chief Product and Membership Officer), along with Mark Chonowsky (AI Fellow) and David Chivers (lead AI advisor for the Lenfest AI Collaborative).

A note on this week's episode
David Chivers, who listeners will hear in this episode, passed away on January 1, 2026. He was the lead advisor for the Lenfest AI Collaborative and this episode was recorded the previous month. David was deeply committed to building capability in newsrooms. He was generous with his time, sharp in his insights, and always had one of those big smiles that would light up a room. He will be missed.

The conversation covers how Chicago Public Media is thinking about AI as part of a larger membership strategy, how they decide what to build versus buy with limited resources, and what it looks like to lead through a public AI failure.

In this episode:
02:55 — Where Chicago Public Media started with AI a year ago
08:08 — What AI use looks like inside the newsroom
15:42 — How product development is evolving with AI tools
27:28 — Collaboration with OpenAI and Microsoft
28:26 — How AI fits into Chicago Public Media's membership strategy
36:05 — Build vs. buy with limited resources
37:44 — The Chicago Sun-Times AI-generated book list incident
42:18 — Advice for leaders navigating AI mistakes publicly

This episode of Newsroom Robots is supported by the Lenfest Institute for 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.

By 2026, most leading newsrooms have moved past the question of whether AI belongs in their organization. Now the key question is: what does a sustainable AI product strategy look like when you’re building for a subscription-based business and a high-trust brand?

This week on Newsroom Robots, host, Nikita Roy sits down with Alessandro Alviani, Lead for Generative AI, and Fabian Heckenberger, Managing Editor for AI, at Germany’s Süddeutsche Zeitung to discuss how they’re using AI to build the next generation of news products.
This conversation looks at what happens when AI becomes a permanent layer in a newsroom’s product stack.

Alessandro and Fabian walk through how they’re designing AI experiences that fit naturally with reader behavior and how they’re developing new distribution and accessibility formats that would have been impossible to sustain manually.

This episode also goes deep on a topic that’s becoming a defining competency which is operational trust. What do you monitor once an AI product is live? How do you categorize failures? And how do you respond quickly when something goes wrong, without panic and without eroding your brand?

This episode, we cover:

02:52 — How editorial and product roles complement each other in AI strategy

13:13 — Addressing skepticism and fear around AI in the newsroom

25:17 — Inside building the German election chatbot

31:10 — The design framework that signals AI content without eroding trust

35:30 — Real-time risk management and monitoring for live AI tools

48:50 — The two questions every newsroom should ask before greenlighting an AI project

54:55 — Closing reflections and personal AI use

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.

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

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.

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.

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.

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

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.