By The Copilot & Michele Musso

For many journalists and publishers, artificial intelligence feels like the next existential threat…a technology capable of flooding the internet with cheap content, eroding trust, disrupting search, and making it even harder for real journalism to survive.

But what if AI could also be part of the solution?

On this episode of The Media Copilot, host Pete Pachal sits down with Paul Gewuerz, host of Small Press, Big Ideas and founder of LocalPod, to explore what is actually happening on the front lines of local media.

After more than 120 conversations with publishers, editors, entrepreneurs, and local news operators, Paul has seen firsthand how deeply challenged the industry remains. But he has also discovered something that rarely makes the headlines: new ideas are taking root.

From local newspapers transforming themselves into cafés and community gathering spaces to publishers building new revenue streams, launching podcasts, embracing events, and using AI to accomplish work that once required entire teams, local journalism is being reinvented in unexpected ways.

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Pete and Paul discuss why trust may become even more valuable in an internet overwhelmed by AI-generated content, how small newsrooms are already using tools like ChatGPT and Otter.ai, and why AI could give independent publishers the ability to launch products and businesses that simply weren’t possible before.

They also confront the darker side of this transformation, including AI slop, fake local news sites, politically funded “pink slime” operations, and the growing challenge of knowing what information…and which sources…can actually be trusted.

In this episode:

• Why local journalism remains vital to healthy communities and democracy
• How innovative publishers are reinventing the local news business model
• Why trust could become journalism’s greatest advantage in the age of AI
• How small newsrooms are actually using AI today
• The opportunities AI creates for new products, revenue streams, and branded content
• Why AI-generated local news and “pink slime” sites pose a growing threat
• How podcasts can help local publishers grow audiences and deepen community relationships
• Why Paul believes AI represents a new industrial revolution
• The uncomfortable reality of building with AI: if you can create something faster, so can everyone else

Why this matters

For Paul, the promise of AI is personal. After spending more than two years building a software platform with limited progress, he used AI-assisted coding tools to complete it in just two months.

“I’ve been working on a software platform for my company for two and a half years, had about 10% done. I have finished it in the last two months. It is operational. People are on the platform.”

His experience raises one of the biggest questions facing media today:

What happens when suddenly anyone can build almost anything?

About the 👤 Guest

Paul Gewuerz on LinkedIn: Paul Gewuerz

LocalPod website: LocalPod.co

Small Press, Big Ideas on LinkedIn: Small Press, Big Ideas

About the show:

To explore more conversations like this and see what’s new, visit the Media Copilot website at mediacopilot.ai. You’ll find new episodes, expanded resources, and tools designed for journalists, communicators, and media leaders navigating the fast-changing world of AI. It’s the home base for everything Media Copilot and it’s just getting started.

Enjoyed this episode?

Subscribe to The Media Copilot on Substack, Apple Podcasts, Spotify, or your favorite app. On YouTube? Tap the Like button and Subscribe to the YouTube channel. For more AI tools and resources built for media professionals, visit mediacopilot.ai.

Produced by Pete Pachal and Executive Producer Michele Musso
Edited by the Musso Media Team 

Music: “Favorite” by Alexander Nakarada, licensed under CC BY 4.0

All rights reserved. © AnyWho Media 2026

Episode Transcript

This transcript has been lightly edited for clarity and readability.

Introduction

Pete Pachal (00:34)

Hi, welcome to The Media Copilot. It’s a podcast about how AI is changing media, news, and communication. I’m your host, Pete Pachal. I covered tech for a long time as a journalist, and now I have deep conversations with the media people, the builders, and the creators who are all answering the question: How will we get information in the future? And how will that transform journalism and the business of media?

My guest today is Paul Gewuerz, host of Small Press, Big Ideas. That’s a podcast about local news in the United States and the people trying to make it work. Paul talks to publishers, editors, entrepreneurs, and local news operators about what’s working, what isn’t, and the future of community journalism.

I was recently a guest on Paul’s show, and we had a lively conversation about AI and local news and search and trust and all the things. So I wanted to flip the microphone this time and get his view from the front lines of local media.

Local news really is where a lot of the AI debate gets very real. These organizations are usually understaffed and underfunded, but they’re deeply tied to their communities. AI could potentially help them cover more ground, build more products, reach new audiences, and save time. But it could also flood the zone with cheap content and make trust even harder.

So we’re going to talk about what Paul’s hearing from small publishers and how local newsrooms are actually using AI. Where’s the risk? Where’s the opportunity? And what does community journalism look like if AI becomes part of the basic infrastructure of media?

Before we get into it, please take a second to rate or review the show. It really would help a lot. If you’re listening on Apple or Spotify, that might mean leaving a five-star review and maybe a nice comment. And if you’re watching on YouTube, please like the video and subscribe to the channel. Those things really do help people find the show.

All right. Housekeeping over. Paul, welcome to The Media Copilot.

Paul Gewuerz (02:46)

Pete, thanks, man. Thanks for having me on. Good to talk to you again. It’s been a few months, or a few lifetimes in the AI world and media world. So yeah, good to be here.

Pete Pachal (02:49)

Yeah, likewise, man. Totally. I think it’s like 500 Claude versions ago.

Before we get into AI and all the stuff around community journalism and local news that I just talked about, let’s talk a little bit about you. I’d love to hear more about your history, your background, and what brought you to covering local media in this way.

From Audiobooks to Local Journalism

Paul Gewuerz (03:20)

Yeah, I’d love to. I’ve said it a million times on my podcast: I’m not a journalist. I don’t come from a journalism background. I’ve always had an interest in it. In high school, I was really attracted to more gonzo journalism. I was a big fan of Hunter S. Thompson.

I went to school for journalism for a few years and graduated in 2008, so not a great time for the job market. I went into an entirely different field. I actually worked for a beer distributor for about a decade.

Pete Pachal (03:58)

Okay. I feel like that would have been great in 2008, with everyone wanting to drink their sorrows away.

Paul Gewuerz (04:18)

It was great. The beer industry does good in a good economy and better in a bad one. That’s kind of the internal line, anyway.

I worked there at a big corporation, a household name, for a long time and eventually got frustrated with the large corporate structures.

I’ve been told that I have a good voice, so I actually got into narrating audiobooks. I did that freelance for a few years, left my corporate gig, and eventually got out of that freelance, feast-or-famine mindset.

I’m a big audio guy, so I started producing podcasts for clients, social media influencers, content creators, etc.

A few years back, I was approached by a local news outlet in the Seattle area to produce a podcast for them, and it reignited that interest in journalism, specifically local journalism. We put together a podcast for them, and I got really interested in it. I wanted to work more in the space, started reaching out to more publishers, launched my own podcast, Small Press, Big Ideas, and I’ve just tumbled down a rabbit hole of media and specifically local journalism.

I’ve had a crash course in it over the last few years. I went into it initially as a business interest. I thought, “This is an interesting niche to target.” Then, after talking to people, I realized how vital it is to democracy and a community.

There are studies showing that when a local news source disappears in an area, creating what’s referred to as a news desert, corruption and financial misdealings at the city and county level skyrocket because there’s no accountability.

So besides the need for good-quality local news and information, it’s a vital thing for our society. I didn’t expect to tumble down that rabbit hole, but that’s where I’m at.

Today, I host the Small Press, Big Ideas podcast, and I have a company called LocalPod.co, where we specialize in producing podcasts for mostly all-digital publishers. But specifically, my heart is with local media operators and helping them grow audience and revenue from there.

That’s pretty much the story in a nutshell, I’d say.

The Untold Stories of Local Media

Pete Pachal (06:15)

I feel like with local media, there are obviously networks and groups that cover certain regions and that sort of thing. But generally, I don’t know if there’s a lot of communication outside of those things.

I feel like your podcast really provides a good service by creating conversation around that layer of media.

Everyone talks about local media almost at arm’s length, in the third person. “Wouldn’t it be nice if we had more?” But I feel like the actual newspapers are rarely part of that discussion. It’s usually just people opining on them, or whatever they are, not necessarily newspapers.

I think you’re providing a valuable service by giving folks an outlet. Also, people love to talk about their communities and themselves, and as you’ve found, I’m sure there are tons of unique stories out there in terms of success in journalism.

Paul Gewuerz (07:20)

Yeah, it’s a bigger topic than I realized. When I started the podcast, I thought maybe I could get 10 people I’d researched to come on. I’m 120 episodes deep now and still have people lined up. There are a lot of interesting stories out there.

I had Steven Waldman on the podcast early on from Rebuild Local News, an advocacy group out of Washington focused on strengthening local news. I think he’s the one who put it best in terms of local media sustainability.

He said it’s like there’s a forest fire. The last 20 years of Google and Meta and everything else have decimated the local media industry. But there are all these little green shoots and sprouts coming up. You wouldn’t know it from looking at the side of a mountain, but if you look closely, they’re there.

That’s what the podcast has shown me. There are a lot of cool stories and innovations happening. It’s just not necessarily at the scale we need yet.

Pete Pachal (08:16)

I’d love to hear about some of those. Are you thinking about anything specific when you think about the promising things being seeded right now?

Paul Gewuerz (08:22)

I’ve had a lot of people on the show, and every organization is different. Every community is different, and this is a huge country. The podcast is mostly based in the U.S., although we’ve had a couple of people from the U.K. and Canada.

I’ve had nonprofits on. I had somebody from South Carolina who left the legacy newspaper in town and started basically a glorified Substack. Three or four years later, they’re a nonprofit that works mostly on sponsorships, and I think they have a newsroom of four or five, maybe five or six, full-time people now. It’s become this vital thing to the community.

For a Canadian example, The Green Line up in Toronto is really interesting. It was founded by Anita Li, who was also on the podcast. I really like the design. They’ve built The Green Line to be very social media-native. Everything is visually appealing. Even the functionality of the website is different from what you think of when you imagine a newspaper site.

They create in-depth guides on things like housing and the job market, and they’re very practical. It’s not just an article you’d read. It’s a different format, and they’re crushing it.

Those two come to mind, but I could go on and on. There are a lot of examples.

The Hard Reality of Running Local News

Pete Pachal (10:04)

I’m glad you brought up Anita Li’s operation. I actually used to work with her at Mashable. She’s great.

We’ve talked about some specific examples, but let’s zoom out a bit. What’s your broader perspective on local media now that you’ve talked to more than 120 people and heard so many stories? What do you understand about local news now that you didn’t when you started the show?

Paul Gewuerz (10:36)

You hit the nail on the head when you said everybody holds it at arm’s length and says, “Yeah, we need more good local journalism.” And almost everybody who says that also says, “Well, I’m not going to pay for it.”

That’s a reality.

I think it was a mistake made by the news media industry early on in the internet era to put everything up for free. People got used to that, and it’s very hard to walk it back.

Pete Pachal (10:57)

And we’re reaping the winds of that with AI now that you think about it. But anyway, go on.

Paul Gewuerz (11:05)

Not that anybody knew that at the time. I don’t want to discredit anybody.

But what I’ve seen is that it’s a hard business to operate, especially where it’s needed most in rural America. I’m in western Colorado, in a town of 20,000, which is the biggest city anywhere around my region. I think a lot of folks on the coasts forget just how huge the country is.

It’s a very difficult business to operate on a smaller scale where it’s needed. If we’re using jiu-jitsu belt levels, it’s closer to the black belt level of business operations compared with something that has higher margins.

Combine that with the fact that many of the people who get into smaller outlets are mission-driven journalists. They want to serve the community. They’re not necessarily businesspeople.

You came up in media. There used to be a firewall between the business side and the editorial side. A lot of that needs to be dissolved, and people on either side need to think more like the other side.

Business operators sometimes come in and don’t know how to do good journalism. On the other hand, there are people whose organizations have fallen apart around them, and maybe they’re the last person left, a one-man or one-woman operation running the whole thing. They have to report on everything and get revenue coming in the door.

It’s a challenge. It’s a very, very complicated challenge. I think about it a lot every day, and I don’t have any great answers. But there are also amazing people doing amazing things out there.

Why Local Media Must Reinvent Itself

Pete Pachal (12:50)

For sure. The smaller the organization, the more everyone has to be mindful of how the business is doing and how you’re actually succeeding.

Neither of us means to disparage the spirit of the church-state separation, which has good roots in preventing business interests from affecting journalism. We both believe in that.

But at the same time, there has to be a strategy for running the business. If you’re News Corp, you might have strategists and executives making broader strategic decisions. But if you’re a team of three, four, or five people, everything is strategic to some extent.

I’m not at all endorsing commercial interests affecting the actual journalism, but when it comes to the broader directions you take, everyone is going to have a voice. Especially today, almost every decision seems a bit existential.

Paul Gewuerz (14:25)

Yes, very much.

The way I think about it sometimes is that the local news industry has gone the way of the music industry.

The big record companies in the ’60s, ’70s, and ’80s were absolutely printing money with records, cassettes, and CDs. Then the internet came along and democratized everything. Napster and LimeWire arrived, disrupted the business model, and now it’s a very different, much smaller business that’s much more spread out.

I think the same thing has happened with news.

Newspapers had this amazing business model throughout the 1900s. They had classified ads and were the primary source of advertising revenue. Then the internet came along, along with Google and Craigslist, and upended that.

It’s never going back to the way it was. Things evolve. They’re constantly in flux. It’s going to change, and it’s a matter of learning how to deal with that and adapt to the new realities and the new environment.

Pete Pachal (15:58)

The music analogy is interesting because the music industry was forced to figure out that selling songs for 99 cents, at least in the 2000s, was kind of the future. Then they had to adapt to this new business model, and it’s interesting that it was forced upon them by tech.

There are a lot of parallels here. I wonder about the media and strategic planning back then. Classified revenue was substantial, and then it went to zero. If they had planned around that, could it have made a difference?

Because in today’s media, specifically with AI, there’s a lot of strategic planning around Google Zero. It hasn’t happened yet. Obviously, Google isn’t dead as a search engine, and the 10 blue links still exist, at least for a while. But people have been planning around Google Zero for a while.

If people had started planning around classified zero in 2000, would there have been quite the apocalypse there was? I don’t know.

At this point in 2026, media has learned so many hard lessons over the last couple of decades that we’ve got this ingrained survival instinct now.

Are you seeing evidence of that at the local level? How are they surviving?

Trust, Community, and New Business Models

Paul Gewuerz (17:30)

To be honest, there are a lot of organizations that, in my opinion, have not changed enough. They’re still relying on advertising and sponsors, scraping by, and doing what they’ve always done.

But the ones that are thriving are doing something unique. They’re building a local brand.

You came on my podcast and talked about how you think it’s going to be a huge boon for PR firms over the next couple of years. Anybody who can generate trust and reliability in an age when anyone can produce anything with AI has an opportunity.

If you can build a brand, get people excited, and generate that trust in a community, those are the organizations doing a really good job.

I thought of a few more examples. There’s the Big Bend Sentinel in Marfa, Texas.

Max Kabat, who came on the podcast, and his wife moved to Marfa. There was an elderly couple running the Big Bend Sentinel, the local newspaper and print shop, and they wanted to retire. Max and his wife purchased it from them.

There was a huge print shop in downtown Marfa, but they didn’t need that much space anymore because most everything is digital now, even though they still have a print product.

They basically cut the space in half. They turned half of this old, really cool print shop into a café, community space, event center, and arts center, with the profits feeding into the journalism.

It’s become an absolute hub. Marfa is a town of about 2,000 people, and I think the combined café, event space, and newspaper employ around eight or 10 full-time people now.

There’s a similar example up in Maine. They have a café and were featured on CBS Sunday Morning. There’s also a bed-and-breakfast tied to it, and upstairs is basically the newspaper.

It all feeds into this idea of a community center. People who want to air their grievances about the city council can come down, have pancakes, and talk to journalists.

There are cool things like that happening.

Pete Pachal (20:18)

Is that an opportunity for sponsorships and things like that? Having an event space…events are the future for media broadly. Obviously, it’s one of many business models, but it’s a growing one.

It sounds like this could be a doorway to that at the local level. You could have a sponsored night and do something related to your publication.

Paul Gewuerz (20:45)

Yeah. My friend Paul Myers is in California’s Central Valley, and they do what I think are called “Brews and News” nights every month or quarter.

They basically rent out the local microbrewery, and you get one free pint of beer. The price is your email address for their newsletter list.

It’s not necessarily a sponsored thing, but it’s about subscribers and growing the audience. I think it’s a cool idea.

How Local Newsrooms Are Actually Using AI

Pete Pachal (21:18)

That’s really cool.

So, Paul, we’re about 20 minutes in and we haven’t talked about AI yet. I feel like I’m getting someone in my ear insisting that I get to the machines.

You talked about some success stories. How much AI is actually being used at the local level, and what are some of the most interesting use cases you’ve come across?

Paul Gewuerz (21:57)

There are a couple of things that almost everyone who comes on the podcast mentions.

The specific tool that seemingly every journalist and entrepreneur running a local news operation mentions is Otter.ai, which is a transcription service. It seems simple and obvious, but everyone swears by Otter for transcribing meeting notes, interviews, city council meetings, etc.

Another trend I’ve seen is normal old ChatGPT being used for ideas. Almost nobody, I should say, is using it to actually write content, at least not unchecked. But using it to generate headline or title ideas seems to be very popular.

I’m an optimist. I’m a fan of AI. I think it can be used as a tool.

A lot of local news publishers are scarred from the rise of Google, the internet, Craigslist, and everything else we’ve talked about. These big tech companies came in and basically hollowed them out over the last 20 years.

I think a lot of them view AI as an extension of that: “This is going to be the final blow. This is it. This is going to do us in.”

I fundamentally disagree with that.

As opposed to The Empire Strikes Back, I think AI tools are Return of the Jedi. I think they’re going to enable so much more time for these organizations.

There are boring back-end business use cases and tasks nobody wants to do but that need to get done. AI can reduce newsroom time spent on those things and enable more good reporting to get done.

I also think there are business models that local media operators have tried in the past that are going to become more possible now. For instance, the idea of operating as a local news outlet and also as a marketing firm for local businesses.

Some people have had success doing marketing for local companies. But that’s almost like adding a whole other business to your newsroom.

Pete Pachal (24:37)

Can you double-click on the marketing part of that? Are you talking about a publication with a team that might also do branded work?

Paul Gewuerz (24:46)

Yes. It’s something that’s been floated around in the space for probably the last 10 years, with some success. But once again, it’s a hard business to run, and that adds another layer of complexity on top of everything else.

Pete Pachal (25:02)

That speaks to what I was saying earlier about the church-state separation. At a major publication, obviously you’re going to have different teams and completely different operations.

At the local level, you’re going to have to put on different hats and figure it out. That’s just the reality.

Paul Gewuerz (25:17)

Yeah. For example, I’m mostly a one-man show for my business, and I need to get a new landing page up for a segment of LocalPod.co.

A year or two ago, that would have taken three days or, if I’m being honest, a week of my time to get polished. I can do that in half a day now with some of these AI tools.

It’s hard to overstate how much more efficient AI has made me at operating my business. I think that’s going to translate to local media operators.

For the marketing example, I think they’ll be able to do their reporting and still have enough time to take on clients, like the real estate brokerage in town that wants branded work done, while also getting a spot in the newspaper that week.

I think it’s going to create more options. We don’t know exactly what it’s going to enable, but I’m seeing it in my own business and my own tinkering with these tools.

There are all kinds of things possible now that I simply didn’t have the time or bandwidth to take on before.

What Can We Do Now That We Couldn’t Do Before?

Pete Pachal (26:26)

I like that. It’s making good on the promise that AI isn’t just about efficiencies. It’s not just making you a little faster, or even a lot faster, and hopefully getting time back.

It’s also about asking: What can we do now that we simply couldn’t do before?

Branded content isn’t reinventing the wheel, but for these publications where, as I said, everything is existential, that’s a big move. Now they don’t necessarily need to hire a completely different team and buy a whole different set of software to do it.

That feels like progress to me.

What also resonated with me is that a lot of the distrust of AI stems from its effect on distribution. AI is obviously vastly affecting distribution and digital discovery. That’s indisputable. But its use as a tool is also indisputable.

You can acknowledge how good it is at making certain things better in your workflows while also acknowledging that, yes, it’s doing something strange to audiences as people get AI summaries and stop there.

Broadly, it’s a “don’t throw the baby out with the bathwater” argument. But I feel like that’s where journalists often end up for some reason.

Are you seeing that change as AI becomes more embedded? On my end, over the last five or six months, I’m seeing more of a resignation among skeptics that this is happening.

Paul Gewuerz (28:23)

I’ve felt the exact same way.

A year ago, if I’d seen some AI headline in the local news industry about somebody using it for something, there would have been a ton of backlash, shaming, and people piling on.

But over the last five or six months, I’ve seen a marked shift in the mood of the industry.

Whether people are resigning themselves to it or just getting more familiar with AI, realizing what it can and can’t do, and becoming more aware of it, the mood has changed.

The vibe has shifted, Pete, from what I can tell.

Could AI Actually Strengthen Local News?

Pete Pachal (29:01)

Yeah. Not completely to, “Hey, it’s awesome,” but more to, “Okay, this is getting embedded.”

Let’s talk about AI disintermediation and distribution. Do you have a sense of the unique factors affecting local media?

Intuitively, I would think local media might be a little less affected because you’re more invested in your own community and what’s happening there. You’d want to go directly to the source.

What are you hearing about how badly Google Zero or the traffic apocalypse is affecting local media?

Paul Gewuerz (29:50)

I think in terms of trust, it’s actually a really good thing for local news.

People are inundated with content coming at them now. If there is a trusted local voice, I think people are going to turn to that more and more. There’s that human connection, a human byline they can actually read.

That being said, local media operators still need to pull that off. It goes back to what I was talking about before: brand building and trust building.

Not everybody has that down.

A lot of people I talk to honestly think they can keep doing what they’ve always done. “We’ve got our website up. We’ve had our masthead for 50 years. People trust that.”

It’s just not the case anymore.

You still need to be on social. You need to be everywhere at the same time.

It’s a dance between the people who don’t want to change and the people who are changing. The people who get it and recognize the opportunity realize that I think it’s going to be a good thing.

Because the AI slop out there is ridiculous.

AI Slop, Fake Local News, and “Pink Slime”

Pete Pachal (31:08)

Let’s talk about slop specifically for local media.

Every few months, it feels like there’s some kind of story about someone trying to game the system with local news.

There was a guy who was eventually hired by 6AM City. That wasn’t necessarily malicious. I think there was a mix of people trying things out who aren’t really journalists and are just throwing locally oriented content out there.

Then there’s this more recent thing in Florida involving a sort of fake site, which sounds a little shadier, and they were apparently running a whole bunch of other sites.

I feel like this keeps happening in local media. Maybe it’s because people think they can do something with local sites and stay under the radar, as opposed to trying to create some fake national site that probably wouldn’t get very far.

Is that basically what’s happening, or is there some unique perfect storm of circumstances fueling this?

Paul Gewuerz (32:31)

I think that’s definitely a thing. You see those headlines pop up.

I think it’s two different things.

One is more malicious, like the story in Florida. It’s referred to as “pink slime.”

Pink slime sites are basically websites that look like legitimate news operations but are funded by some kind of organization with a specific goal, usually political operatives or something like that.

They’re playing themselves off as reliable local journalism and then slandering one political party or the other party’s candidates.

So that’s happening, often with strange funding that nobody can really trace.

At the same time, there’s been a huge trend I’ve seen on YouTube and some podcasts of people getting really interested in local newsletters specifically.

There have been some huge success stories where people say, “I run this local newsletter, and now I make $400,000 a year.”

That has happened, and there’s been a lot of interest and content popping up around it.

With the rise of AI tools making things easier, there are also a lot of people in their basements throwing spaghetti at the wall. Someone can spin up 15 local newsletters with almost nothing, ripping off actual local news outlets, copying their work, and putting it out there.

I think those are the two main culprits.

But there are also legitimate people creating local curated events newsletters. It’s not as simple as good and bad. There are quality people doing this work.

My friend TJ Larkin is in that space, and he puts out a really quality product and teaches other people how to do it.

Podcasting as a Growth Strategy for Local News

Pete Pachal (34:29)

Absolutely. Let’s switch gears as we wrap up here because we’re both podcasters, and you’ve obviously talked and written about podcasting and its relevance to local media.

Where does podcasting factor into a local news strategy? Obviously, people like podcasts, but they’re harder to scale. Is that less true now?

What’s a good podcast growth strategy for local news in 2026?

Paul Gewuerz (35:02)

That’s one of the reasons I zoned in on this a few years ago.

Podcasts are notoriously hard to reliably grow. And when they do grow, it’s almost hard to figure out why unless there’s some kind of viral moment.

If you start a podcast about World War II in the Pacific Theater, for example, it’s hard to find audiences. It’s hard to find first-party data.

The difference I’ve seen with local podcasts in particular, although this does take a little bit of a budget, is a site I use called AudioGO.

It’s an advertising platform that allows you to create 15- and 30-second audio ads and place them on top podcast networks, Pandora, and a few other platforms.

The key is that you can geotarget them by ZIP code.

I’ve seen some success with this, and it’s particularly useful for local podcasts.

If you can communicate your message well in a 30-second spot, something like, “Hey, this is the Montrose Daily Press podcast covering the news and events in your town,” you can geotarget that to people listening to The Daily or top true crime podcasts in your local area.

I haven’t seen anything else work as well as that kind of strategy for general podcasting.

Your podcast and my podcast don’t work like that. You’re covering AI, I’m covering local media, but we’re both speaking to the whole country. It’s harder to target those people.

That’s the edge I’ve seen. Any local operators listening should feel free to use that. That’s kind of the secret sauce we’ve been using.

What Keeps Paul Up at Night About AI?

Pete Pachal (37:00)

I’m sure everyone’s got their notebooks out right now.

I try to end these conversations with a similar question because we see divergent futures ahead of us with AI involved. There’s going to be bad, and there’s going to be good.

What is something that might keep you up at night with regard to AI and media? And what’s something you’re hopeful about?

Paul Gewuerz (37:29)

Something that keeps me up at night is the relentless pace of change.

It’s really hard for me to see what anything is going to look like in two or three years, let alone six months from now.

I’ve been over the moon with some of the capabilities I have now, like with Claude Code. I’ve been working on a software platform for my company for two and a half years and had about 10% done.

I finished it in the last two months.

It’s operational. People are on the platform.

Pete Pachal (38:00)

Nice. What’s the platform? Tell me about it.

Paul Gewuerz (38:03)

It’s my LocalPod Studio. It’s basically a dashboard studio where you can turn written content into an AI-narrated podcast that’s fully distributed in a couple of clicks.

Anybody who wants to check that out can go to LocalPod.co or message me.

But the thing that keeps me up at night is that I built this…

Pete Pachal (38:18)

Nice. Beautiful.

Paul Gewuerz (38:28)

It’s pretty incredible.

I have a little bit of coding ability, but not much. Minor league. And I’ve been able to build this crazy thing, and I have all these other ideas I can build.

But at the same time, I’m thinking: That means anybody can build this.

I think it’s a great equalizer and a great democratizing force. I’m excited and optimistic that I can build things and do things for my business.

The competition is going to come with that. I think it’s still early.

Combine all that with the fact that I don’t know what the whole economy is going to look like in a couple of years because you can’t map what that growth is going to look like.

I’m sorry, what was the second part of the question?

Pete Pachal (39:08)

You kind of almost mixed it in there, but it was also: What are you hopeful about?

Paul Gewuerz (39:25)

It’s really kind of the same thing.

There are doomers. There’s a lot of doomerism around AI. I don’t think AI is sentient. I don’t think it’s going to get there.

When you actually dig in and see how it works, it’s a very powerful tool. I don’t think it’s going to murder all of us. I just don’t see it in the cards. Or there’s a very small chance, at least.

Pete Pachal (39:36)

Yeah, people can tell it to do bad things, but it doesn’t have any ideas of its own.

Paul Gewuerz (39:39)

Yes. There’s no ghost in the machine, is my take on it.

I think this is a new industrial revolution. I don’t think that’s underselling it at all.

People are worried about all the jobs disappearing. But every time people have said that in recorded history, if you go back and read about it, new things emerge that people couldn’t even imagine becoming jobs.

I graduated high school in 2003. I’m 41 years old.

My job titles today include podcast producer and SaaS platform owner. My wife and I also operate an Airbnb upstairs.

None of that existed when I graduated high school in 2003.

If I’d said I was an Airbnb host and podcast producer, I would have been locked up, basically. And that was only a little over two decades ago.

Things change.

I think there’s a future of abundance, and I think AI is going to help us unlock that. There are some issues with it, but I think they’re going to get sorted out because it’s worth it to sort them out.

Pete Pachal (40:50)

That’s awesome. We’ll leave it there.

Paul, thank you so much for dropping by The Media Copilot and sharing your thoughts.

Paul Gewuerz (40:55)

Yeah, this was fun, Pete. I always enjoy these talks. It gets me fired up. Thanks for having me. I appreciate it.

Pete Pachal (41:01)

Cool. We’ll do it again soon.

The post AI didn’t kill Local News. Could it actually save it? appeared first on The Media Copilot.

The tools used to monitor journalists — once confined to intelligence agencies — are now commercially available, widely deployed, and capable of accessing a phone without the target ever clicking a link. On World Press Freedom Day, May 3, the International Federation of Journalists put that reality at the center of its annual assessment of global press conditions, publishing findings that describe not a gradual erosion of media freedom but an accelerating one.

The IFJ, which represents more than 600,000 media professionals across 148 countries, called the global state of press freedom “deplorable.” UNESCO’s latest World Trends Report on Freedom of Expression and Media Development adds the statistical frame: press freedom has fallen 10% since 2012, a decline the IFJ said is comparable to some of the most unstable periods of the 20th century.

128 deaths, and counting

The human cost in 2025 was 128 journalists killed. The IFJ said additional deaths have already been recorded in 2026. Reporters working in conflict zones face the sharpest risks — in Ukraine, Palestine, Lebanon, and Sudan, journalists have been arrested, displaced, or killed while carrying out their work. Individuals identified as press are increasingly becoming deliberate targets rather than incidental casualties.

IFJ General Secretary Anthony Bellanger described each attack as an act with consequences beyond the individual.

“Every attack on a media professional is an attack aimed at silencing a story intended to inform citizens,” Bellanger said, adding that restrictions on journalism ultimately prevent the public from making informed decisions.

Spyware without borders

In a study published April 28 — “Global Surveillance of Journalists: A Technical Mapping of Tools, Tactics and Threats” — the IFJ documented what it describes as a convergence of state intelligence capabilities, private-sector tools, and weak regulatory frameworks.

The report, which draws on cybersecurity expert interviews and technical investigations conducted between 2021 and 2025, identifies commercial spyware systems including Pegasus, Predator, and Graphite as now widely available beyond their original government-intelligence markets. All three are capable of “zero-click” intrusions — accessing a target’s device with no interaction required from the user.

The IFJ found these technologies are frequently deployed with limited oversight, leaving journalists monitored without accountability and with few legal avenues for redress.

AI as force multiplier

The IFJ study also raises concerns about artificial intelligence extending the reach of existing surveillance infrastructure. Data gathered through digital monitoring — communications, location history, online activity — can be fed into AI systems that analyze it at scale. In conflict environments, the report said, such systems can combine telecommunications data with drone feeds, enabling the identification and tracking of journalists in the field.

Beyond targeted surveillance, the IFJ warned of AI-driven disinformation, identity theft, and automated content systems that bypass editorial standards entirely.

Lead study author Samar Al Halal said the effects compound in ways that damage journalism even when no direct harm occurs.

“When journalists are watched, sources disappear, investigations stop, and self-censorship becomes normal,” Al Halal said. “The public doesn’t just lose information, it loses the ability to hold power accountable.”

What the IFJ is demanding

The organization is calling on governments to enact laws protecting press freedom and regulating surveillance technologies, restrict the export and use of commercial spyware, and strengthen legal safeguards for journalists’ sources. The surveillance report specifically recommends increased investment in digital security training and stronger protections for encryption and anonymity.

The broader context makes those demands urgent. A 10% global decline in press freedom over 13 years, 128 journalists dead in a single year, and surveillance tools that require no mistake from their targets — the infrastructure for silencing reporters has rarely been more capable or more available.

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A single unreleased AI model has triggered emergency regulatory mobilization on both sides of the Atlantic. UK financial regulators are holding urgent talks with the government’s cybersecurity agency and major banks to assess risks posed by Anthropic’s Claude Mythos Preview — days after US Treasury Secretary Scott Bessent and Federal Reserve Chair Jerome Powell convened an emergency meeting with Wall Street’s top CEOs over the same concerns.

In the UK, officials from the Bank of England, Financial Conduct Authority, and Treasury are in talks with the National Cyber Security Centre. Representatives from major British banks, insurers, and exchanges are expected to be briefed on cybersecurity risks at a meeting with regulators within the next two weeks, according to Reuters. The BoE, FCA, and NCSC all declined to comment.

The US response was more public. White House national economic adviser Kevin Hassett confirmed on Fox News that Bessent and Powell had convened bank chiefs — including the CEOs of Citigroup, Morgan Stanley, Bank of America, Wells Fargo, and Goldman Sachs — to warn of cyber risks from the model. JPMorgan CEO Jamie Dimon was unable to attend. The urgency of the meeting reflected the capabilities Mythos Preview has demonstrated in controlled testing: the ability to identify and exploit weaknesses across every major operating system and every major web browser.

Anthropic has stopped short of a broad release, citing concerns the model could expose previously unknown cybersecurity vulnerabilities at scale. The company has been navigating an increasingly complex relationship with the broader tech and media ecosystem as its models grow more capable.

What Mythos Preview is — and who can use it

Despite not being publicly available, Claude Mythos Preview is already in active use — under strict controls. Under a program Anthropic calls Project Glasswing, select organizations have been granted access to the model for defensive cybersecurity work. Partners include Amazon, Microsoft, Apple, Google, Nvidia, CrowdStrike, and Palo Alto Networks. Access has since been extended to approximately 40 additional organizations responsible for critical software infrastructure.

Anthropic says Mythos Preview has already found “thousands” of major vulnerabilities in operating systems, web browsers, and other software. The company has committed up to $100 million in usage credits and $4 million in donations to open-source security groups as part of the program.

The framing is defensive. But the same capability that finds vulnerabilities can, by definition, be turned toward exploiting them — which is precisely what regulators appear to be stress-testing.

Why regulators are moving fast

The simultaneous and independent responses from UK and US financial regulators signal that Mythos Preview represents a qualitatively different kind of AI risk than those regulators have previously had to assess. Prior AI regulatory concerns have centered on bias, misinformation, and systemic market risks — as seen in ongoing debates around AI copyright policy and AI use certification. A model with demonstrated offensive capability against critical software infrastructure — in active use, even in a restricted form — is a different category of problem.

It is also a compressed timeline problem. The model exists. It is being used. The regulatory frameworks to manage it are still being assembled.

All three UK agencies — the BoE, FCA, and NCSC — declined to comment on the talks. Anthropic had not responded to a request for comment at the time of the Reuters report.

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The Associated Press, founded in the mid-1800s to help New York newspapers share reporting costs, is offering buyouts to an unspecified number of U.S.-based journalists — the latest move in a long-running transformation from wire service to technology data company.

The News Media Guild, which represents AP journalists, said more than 120 staff members received buyout offers on Monday. AP executive editor and senior vice president Julie Pace said the goal is to reduce global headcount by less than 5%, though she acknowledged the cut among U.S. staff would likely exceed that figure depending on how many people accept.

“We’re not a newspaper company and we haven’t been for quite some time,” Pace said.

The numbers back her up. Over the past four years, AP’s newspaper revenue has fallen 25%. Big newspaper publishers, once the organization’s financial foundation, now account for just 10% of income. Gannett and McClatchy both dropped AP in 2024. Lee Enterprises — publisher of The Buffalo News, the St. Louis Post-Dispatch, and the Richmond Times-Dispatch — is now seeking an early exit from a contract due to expire at the end of 2026.

Where the growth is coming from

While the newspaper business contracts, AP’s technology revenue has grown 200% over the same four-year period. Kristin Heitmann, senior vice president and chief revenue officer, put it plainly: “If you can think of a large technology company, they are a customer of ours.”

AP was among the first news organizations to move aggressively into AI deals, agreeing in 2023 to lease part of its text archive to OpenAI. It has since launched on Snowflake Marketplace to license data directly to enterprises, stood up AP Intelligence to sell data to financial and advertising sectors, and last year secured a deal with Google to deliver news through the Gemini chatbot — Google’s first content deal with a news publisher.

Elections data is another growth vector. AP saw a 30% increase in election data customers between the 2020 and 2024 cycles, and last month agreed to sell U.S. elections data to Kalshi, the world’s largest predictions market. ABC, CBS, NBC, and CNN all signed on to the AP elections service last year.

What the restructuring looks like

Beyond the headcount reduction, AP is doubling down on video — it has already doubled the number of U.S. video journalists since 2022 — and deploying rapid-response teams that contribute to major stories regardless of geographic base. The organization says it will maintain a presence in all 50 states.

The union is pushing back. In a statement, the News Media Guild said AP “refuses to offer [staff] appropriate training and tools” and is “flirting with artificial intelligence — ignoring the opportunity to differentiate AP news stories as ones that are and always will be created by human journalists.” The union also said AP declined a request last week to bargain over AI use.

AP did not immediately comment on either claim.

Pace framed the restructuring as a strategic choice made from stability, not distress. “The AP is not in trouble,” she said. “We’re making these changes from a position of strength.”

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Tubi is bringing its 300,000-title library directly into ChatGPT — and betting that the future of entertainment discovery looks a lot like asking a chatbot for recommendations.

The free streaming service, owned by Fox Corporation, announced Tuesday that it has launched a native app inside ChatGPT, becoming what it claims is the first major streamer to integrate directly into OpenAI’s conversational interface. Users can type “@Tubi” in any ChatGPT thread and describe what they’re in the mood for. “A movie that feels like a fever dream but isn’t horror,” for example, and receive curated results pulled from Tubi’s catalog, complete with a direct “Watch on Tubi” link that jumps straight to playback on web or mobile.

The move reflects a broader shift in how platforms are thinking about content discovery. Rather than scrolling through interfaces or searching by title, viewers are increasingly describing intent in natural language and platforms want to be present at that moment of decision. Mike Bidgoli, Tubi’s chief product and technology officer, framed it as a natural extension of how AI agents are becoming a primary way people navigate the internet. “Streaming should feel effortless,” he said. “At the core of Tubi is a deeply scaled personalization and discovery system, trained on more than 1 billion monthly hours of viewing from over 100 million active users.”

The timing aligns with Tubi’s release of its annual Stream 2026 study, which found that 80% of respondents said they would rather watch TV or movies than scroll social media — a signal that audiences are becoming more selective about how they allocate attention, and that discovery friction matters more than ever. For a free, ad-supported service like Tubi, reducing the distance between “I’m bored” and “I’m watching something” is a direct path to more impressions. For publishers broadly, the question of who gets paid as AI reshapes discovery is becoming increasingly urgent.

The ChatGPT integration is also a reminder that streaming platforms are no longer competing just with each other — they’re competing with every interface where a recommendation can surface and a viewing session can begin. The broader battle over how AI accesses and pays for content is playing out across the industry, with the open web losing ground as AI-driven answers reduce the need to click through to original sources.

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The Internet is undergoing a fundamental shift — and two of its largest infrastructure companies want to be the ones who set the rules for it.

Cloudflare and GoDaddy announced a strategic partnership Tuesday designed to give creators and small businesses more visibility and control over how AI agents access their content. The centerpiece: GoDaddy is integrating Cloudflare’s AI Crawl Control directly into its website hosting platform, letting site owners allow, block, or signal that payment is required before any AI crawler touches their content. The companies are also supporting open standards — specifically GoDaddy’s own Agent Name Service (ANS) and Cloudflare’s Web Bot Auth — that would give AI agents a cryptographically verified identity rather than operating anonymously across the web.

The problem they’re solving is real and growing. AI agents are increasingly browsing, summarizing, and retrieving content on behalf of users — but most operate without identifying themselves, leaving site owners with no record of who scraped what and no mechanism to negotiate terms. “There needs to be a way to ensure that businesses and creators have the tools to easily identify, manage, and trust AI traffic,” the companies said in a joint statement.

ANS, which GoDaddy introduced as a global open standard, uses DNS and public key infrastructure to assign verifiable identities to AI agents — a layer of trust that lets site owners distinguish legitimate agents from impersonators. Cloudflare, which introduced Web Bot Auth in 2025 along with a Signature Agent Card developers can use to share their agent’s stated purpose, is supporting the standard alongside its own tools. The broader goal is a permission-based model for the agentic web — and a technical foundation for a fair value exchange in what both companies call the Answer Engine era. It’s a dynamic that mirrors broader tensions: as AI companies negotiate directly with publishers over content access, the underlying question of who controls and monetizes AI’s use of the web is far from settled.

“The Internet is evolving into a high-velocity, AI-driven ecosystem, and that requires a new kind of transparent infrastructure,” said Stephanie Cohen, Chief Strategy Officer at Cloudflare. “By putting tools like AI Crawl Control and open standards into the hands of website owners, we are providing essential underpinnings for a new Internet business model.”

For publishers and creators watching their search traffic erode as AI answers replace clicks, the partnership is a concrete — if early — signal that the infrastructure layer is beginning to take shape. Whether it scales to the full open web remains an open question. Cloudflare has already been converting web pages to markdown for AI agents, and the battle over how AI crawlers pay for content is accelerating.

“We move at the speed of the Internet,” said GoDaddy Chief Strategy Officer Jared Sine, “and we’re working with the broader industry to ensure the agentic open web does too.”

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Artificial intelligence was the single largest reason U.S. employers cited for layoffs in March 2026, responsible for 15,341 of the 60,620 job cuts announced during the month — roughly one in four.

The numbers come from the latest monthly report by outplacement firm Challenger, Gray & Christmas. Overall job cut announcements rose 25% from February, though they remained 78% below March 2025, when the Department of Government Efficiency drove a massive spike in federal workforce reductions. Closings (13,931), restructuring (8,726), and market and economic conditions (6,597) rounded out the month’s other major drivers.

“Companies are shifting budgets toward AI investments at the expense of jobs,” Andy Challenger, chief revenue officer at the firm, said in the report. “The actual replacing of roles can be seen in technology companies, where AI can replace coding functions. Other industries are testing the limits of this new technology, and while it can’t replace jobs completely, it is costing jobs.”

The tech sector led all industries with 18,720 job cuts in March, bringing its first-quarter 2026 total to 52,050 — up 40% from a year earlier and the sector’s highest first quarter since 2023, when the industry recorded 102,391 cuts.

Dell confirmed in a 10-K filing that its headcount fell to 97,000 as of January 30, down from 108,000 a year earlier, citing “ongoing business modernization initiatives.” Oracle has reportedly begun its own round of cuts, and Meta is reducing its Reality Labs workforce as it increases AI spending, the Challenger report noted.

The numbers offer a concrete data point for what has largely been an anecdotal debate about AI’s impact on employment. While headline AI investments continue to draw investor attention — and job postings for AI-related roles remain elevated — the Challenger data suggests the technology is quietly displacing existing positions, particularly in software engineering and technical operations. Year-to-date, AI ranks fifth among all reasons cited for layoffs at 27,645 cuts, or about 13% of total planned reductions — but March’s surge to 25% suggests it is accelerating.

Not all signals point downward. Hiring plans surged in March to 32,826, up 157% from February and 149% year-over-year, though year-to-date hiring remains slightly below 2025 levels. Overall, Q1 2026’s total of 217,362 cuts represents the lowest first-quarter total since 2022.

Still, “More layoffs are likely to come from technology companies in 2026,” the Challenger report warned — a prediction that aligns with what’s already happening across the journalism industry, where AI-driven restructuring is accelerating job losses across both digital and legacy outlets.

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Anthropic accidentally published the source code for Claude Code this morning — 512,000 lines of TypeScript, exposed for hours before anyone pulled it.

Source maps can reconstruct the full, readable source from compiled code. By 4:23 am ET, a developer at Solayer Labs had spotted it, posted a direct download link on X, and the codebase was being mirrored to GitHub and analyzed by thousands of developers across the industry.

Anthropic confirmed the incident to VentureBeat: “Earlier today, a Claude Code release included some internal source code. No sensitive customer data or credentials were involved or exposed. This was a release packaging issue caused by human error, not a security breach. We’re rolling out measures to prevent this from happening again.”

That framing — human error, not a breach — is accurate but undersells the competitive exposure. Claude Code is reportedly generating $2.5 billion in annualized recurring revenue, has more than doubled since the start of the year, and competes directly with Cursor, GitHub Copilot, and a fast-moving field of agentic coding tools. The leaked code gave competitors a detailed look at exactly how Anthropic solved some of the hardest engineering problems in that space.

Among the details developers surfaced: a three-layer memory architecture that keeps AI agents coherent across long coding sessions by maintaining a lightweight index of pointers rather than storing everything; an “autoDream” background process that consolidates the agent’s memory while the user is idle; 44 hidden feature flags; and internal model codenames including Capybara (a Claude 4.6 variant), Fennec (Opus 4.6), and an unreleased model called Numbat. The code also showed internal performance metrics: version 8 of Capybara had a 29-30% false claims rate, a regression from version 4’s 16.7%.

The most discussed detail was what developers called “Undercover Mode” — a system that lets Claude Code contribute to public open-source repositories without disclosing that the commits came from an AI. The leak is the second high-profile setback for Anthropic in recent weeks, following its lawsuit against the Pentagon over the company’s AI safety limits.

The underlying story here isn’t the leak itself — packaging errors happen. It’s that one slip exposed enough proprietary engineering detail that competitors now have a working map of how one of the most commercially successful AI coding tools actually functions. For a company that’s staked its position on responsible AI development and technical differentiation, that’s the real cost.

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Of the 440 applications Texas Tribune chief product officer Darla Cameron received for an AI engineering role, 90% were junk — many apparently written using the very tools candidates were supposed to understand. One application literally read: “Here’s a short response that’ll work for this.”

That anecdote, from Hacks/Hackers and Poynter’s AIxJournalism Day at SXSW, captures the split-screen reality of AI in newsrooms right now: genuinely useful when deployed against real problems, already producing absurd side effects when cargo-culted. Poynter’s Alex Mahadevan spent the day listening to newsroom builders — not theorists — and distilled five lessons worth reading carefully.

Start with a specific pain point. Every AI tool actually being used in newsrooms started with a complaint, not a mandate. Pew Research Center’s audience team was spending 95% of its time writing formulaic social posts and 5% engaging with audiences. A WordPress plugin now drafts the formulaic posts automatically; the team reviews options and moves on. That freed time goes to reading comments and responding to what readers actually ask. “Where is the mundane bullshit work that you’re sick of doing?” said Upasna Gautam of the News Product Alliance. “That is a great pathway.”

Draw the line between AI for thinking and AI for writing. Nebraska Public Media’s chief innovation officer Chad Davis stopped using AI for writing entirely — not good enough. But he uses it constantly as a “curiosity partner” for research and brainstorming. His labs team uses AI for concept art and music prototyping: instead of pitching an idea in a meeting, they show a working prototype. Most newsrooms haven’t drawn that line clearly. If you don’t decide, your staff will make their own inconsistent rules.

Be specific about where the human sits. KQED tested AI to identify notable clips from their hourlong radio show Forum. “I’m not ready to say the AI can choose the four most notable moments,” said editor-in-chief Ethan Toven-Lindsey. “But if you put a producer in the loop to make sure those are the right moments, that felt doable.” SWR, a German public broadcaster, has community managers review AI-flagged comments before anything gets acted on. “Human in the loop” is too vague — the newsrooms getting results name exactly where.

Use AI to get closer to audiences, not further away. The Texas Tribune trained a chatbot on its school voucher coverage. When readers asked questions the Tribune’s reporting hadn’t addressed, reporters got story ideas. Pew studied what creators do differently from traditional newsrooms and found a feedback loop: they read comments, answer questions, and build new content from what audiences ask. Any AI strategy that doesn’t free up staff time for that kind of direct audience engagement is probably solving the wrong problem.

Learn to build things yourself. This is the one that cuts across every other lesson. Mahadevan — not a software engineer — built a fact-checking research tool prototype for PolitiFact on vacation using AI coding assistants. Agentic coding tools like Claude Code have lowered the floor dramatically. Trei Brundrett of New_Public said it reminds him of the early web, when gatekeeping vanished and anyone could just build. “The newsroom people who pick up that skill are going to have an outsized advantage,” Mahadevan writes. The ones waiting for someone else to build it for them will be waiting a long time.

The post Five lessons from newsrooms that stopped talking about AI and started building with it appeared first on The Media Copilot.

The numbers are in, and they’re bad. A new analysis of web traffic to 10 major tech and media outlets finds that Google search referrals have collapsed since the company rolled out AI Overviews — the summaries that now appear above traditional search results and answer user queries without requiring a click.

SEO firm Growtika tracked Ahrefs data from early 2024 to January 2026. At their peak, the ten outlets combined received 112 million monthly visits from US Google users. By January of this year, that number had fallen to just under 50 million — a drop of more than 55 percent industry-wide.

For some outlets, the decline is nothing short of catastrophic.

Digital Trends went from 8.5 million clicks per month in March 2024 to 264,861 in January 2026 — a 97 percent collapse. The Verge, HowToGeek, and ZDNet each lost more than 85 percent of their Google-referred traffic over the same period. Wired lost 62 percent. Even Mashable, the analysis’s best performer, shed 30 percent of its traffic.

Growtika’s analysis notes that the four worst-hit publications now receive less combined monthly web traffic than the r/ChatGPT subreddit.

What’s driving it

The firm identifies three compounding factors: the rollout of Google AI Overviews beginning in mid-2024; algorithm changes that boosted Reddit in search rankings; and the growing number of users who skip Google entirely in favor of AI chatbots like ChatGPT and Perplexity.

The steepest declines came in mid-2025, when Google significantly expanded the range of queries that trigger an automatic AI summary. By July of last year, roughly 25 percent of all Google searches generated an AI Overview — meaning a quarter of all searches were being answered without a click.

Google pushed back on the analysis in a statement to Futurism, calling it “fundamentally flawed” for examining too small a sample and failing to account for seasonal traffic variation. The company also cited shifting audience preferences toward podcasts and forums. That defense will ring hollow for publishers whose traffic data tells a different story.

What it means for newsrooms

For journalists and editors focused on AI’s impact on journalism, the traffic story is often framed as a future threat. This data suggests it is a present reality.

Publishers built audience development strategies around search-optimized evergreen content — explainers, how-tos, reference pieces — that now trigger AI Overviews instead of clicks. That content, which represented a reliable traffic baseline for many outlets, has been effectively nationalized by Google’s summary layer.

The outlets hit hardest are tech-focused publications — the same ones most likely to have invested heavily in SEO-optimized evergreen content. News organizations with strong breaking news operations may have more protection, since real-time journalism still generates “Top Stories” placement that AI summaries can’t fully replicate.

But the broader lesson is stark: the deal that sustained digital media for a decade — produce content, get traffic from Google, sell ads against that traffic — is deteriorating faster than most newsroom business models have adapted to account for it.

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