The media industry is consumed right now with anxiety about the “zero-click” future. AI chatbots and search engines absorb content, interpret it, and deliver summaries directly to users, with the predictable result that fewer people actually visit publisher sites. This isn’t speculation. Data from Chartbeat, the analytics firm serving media companies, shows global publisher traffic from Google fell by a third last year, with smaller publications taking the biggest hit. AI clearly substitutes for content, but not uniformly.

A recent study by Define Media Group examined how Google AI Overviews have influenced traffic across content categories over the past year. Overall, organic search traffic has declined 42%, but clicks on breaking news stories have actually surged by 103%.

The reason: Google doesn’t display AI Overviews for breaking news queries. That tracks, since breaking stories involve rapidly changing and inconsistent information as reporters across multiple publications sort out what really happened from the noise of rumors, exaggerations, and outright misinformation that swirls around a news event. When a user searches for a breaking news event on Google, they typically see a Top Stories carousel instead of an Overview, a feature that’s existed for a long time.

The real reason breaking news traffic is climbing

Looking closer at the data reveals that Google Discover—the built-in news feed on most Android phones—is the primary driver of the big jump in news traffic. Google has also recently tweaked Discover in ways that apparently pushed even more news from publishers into feeds. But even setting Discover aside and examining only web traffic, news clicks are essentially flat. Clearly, breaking news is the content type most resistant to AI substitution.

This doesn’t mean publishers should pursue news alone, though. The category has other challenges, and competing on breaking news is expensive, requiring continual monitoring and staffing. Also, news without context loses its power. News publishers need to explain to their readers why the news is important to them, even if that explanation is at risk of being summarized by AI.

Furthermore, when AI summarizes content, it doesn’t necessarily mean you’ve “lost”—it shifts the competition to another arena: citation. As I’ve explored before, competition for presence in AI summaries is a battle worth fighting, even if the rewards shift considerably from the click-based advertising business model that is still important to the majority of media companies. Sites that are consistently cited in summaries will ultimately be the ones that define consensus, and data suggests that the share of the audience that does click through to sources, while smaller, is more intentional, meaning there’s more opportunity to turn them into loyal readers.

But the citation game is crowded. Publishers aren’t just competing with each other. They’re not even the preferred sources in many cases. A report from Semrush, the search-analytics firm, ranked the top sources most often cited in AI answers: Reddit, LinkedIn, and Wikipedia. The first publisher on the list is Forbes at No. 11, and I suspect it has a lot to do with its extensive contributor program.

That ranking isn’t the complete picture—other studies, like this one from Muck Rack, do show that AI search engines favor journalistic content over brand-created or social content. At the same time, AI draws answers from a wide range of sites it considers authoritative, not solely from news publishers.

How publishers can build a strategy from these signals

From these data points—news is a moat, AI favors journalism but casts a wider net, and explanatory content is the battleground—a strategy starts to take shape.

The Semrush study found that AI heavily favors citing LinkedIn content. The reason, per the study’s authors: LinkedIn content, especially the longer articles native to the platform, tends to be clearly framed, structurally obvious, and substantial in length (between 500 and 2,000 words).

If AI rewards structured explanatory writing on LinkedIn, those same qualities likely boost explanatory journalism published elsewhere. The Muck Rack data says journalism makes up about a quarter of AI citations, but it also shows that more than half of citations are from the last 12 months and that the highest citation rate is in the first seven days. Define, meanwhile, says breaking news is up while evergreen content has taken a 35% hit.

Together, that evidence points to a specific kind of publisher explainer: not static archive content, but fresh, tightly structured explanatory journalism that accompanies the news.

Now the outline of an AI-resilient news operation comes into focus. Publishers should still invest in breaking news because it remains defensible and difficult for AI to compress into a zero-click summary. But they should pair that with explainers that are updated quickly, tied closely to live topics, and written in a format that is easy for both humans and machines to parse. What’s most exposed is the generic evergreen article that works neither as essential live reporting nor as especially useful source material for AI answers.

AI, then, hasn’t made journalism irrelevant. It’s made its value more precise. Breaking news still commands attention because platforms are cautious about compressing fast-moving events into a single summary. And when the news settles, the publishers that still matter are the ones that can turn their reporting into clear, timely explanations and analysis. That’s where the next fight for authority will be fought.

A version of this column appears in Fast Company.

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The evidence that AI is fundamentally reshaping the media landscape keeps mounting. A recent report from Growtika, a self-described SEO and AI search agency, analyzed data from the search analytics platform Ahrefs and found that traffic to many tech media sites has dropped considerably over the past couple of years.

The numbers are striking. Digital Trends fell 97%, ZDNet 90%, and The Verge 85%. Even publications that appeared more durable took significant hits—Mashable was down 30% and CNET 47% (both Ziff-Davis properties). Some of these reductions are no doubt exaggerated—Growtika compared each publication’s peak month with traffic in January 2026, which doesn’t account for seasonal reductions—yet no one’s disputing the overall trend, or who’s to blame: AI.

On the surface, those numbers paint a grim picture of the floor collapsing under the media industry as a whole. But that’s overly simplistic, and it fails to take into account that publishers have seen this trend for years, and many have been adapting around it. Consider The Verge as an example: Not only did it sound the alarm early about AI’s potential to make website content irrelevant, but it also introduced a paywall in late 2024, part of a larger, four-point strategy. Traffic decline, in other words, doesn’t have to mean business decline.

The authority moat

What The Verge illustrates goes beyond traffic resilience. In the AI era, having a strong brand with a loyal audience is a genuine strategic asset. The publication has been synonymous with tech news, commentary, and analysis since its debut in 2011. Many tech brands choose to break their news there. That credibility has influence in what appears in AI answers, which tend to favor journalistic content above other types—something a recent Gartner report on the communications industry made clear.

AI is easy to cast as a traffic destroyer, but there’s another way to read it: as an audience filter. The people who find your brand through an AI summary are clearly deeply engaged. That makes them probably the most willing to pay for your content, and The Verge has given them that opportunity.

But The Verge has had a strong brand for 15 years. The audience is clear and already engaged. Other publications aren’t so fortunate, and the Growtika data should push them to take a harder look at their brand, their audience, and the actual business they’re running. With AI now fully in the picture as the ultimate information synthesizer, publishers have to understand what they’re layering on top of that information that only they—specifically, the humans that work for them—can provide.

Journalism has always been a storytelling act, and audiences are the listeners. They will seek out publications and writers with voices that resonate with them, AI or no AI. Content with lower storytelling potential, by contrast, has less value and is easily substituted by AI. The practical implication: lean into analysis, opinion, and scoops. Aggregated news (i.e. stuff broken elsewhere, or broad announcements) is less valuable, though with a caveat: A publication that skips “big” stories on its beat risks looking lightweight. But for that to be worthwhile, there are two requirements: a clear sense of what the beat actually is, and the discipline to make every piece of coverage a showcase for that publication’s unique value.

Going narrow

That dynamic tilts the playing field toward smaller publications and independent voices, and the evidence is already visible. Substack reached 5 million paid subscriptions last year, and competitor Beehiiv—where many journalists from places like The Verge and CNN have landed—is on track to double its revenue this year to $50 million.

Still, the Growtika data isn’t entirely a story of small beating large. Some numbers in the report suggest that larger organizations with strong internet domains still have resilience. Mashable and CNET are both Ziff publications, and having spent time at the company twice, I’d say Ziff has a legitimate edge when it comes to SEO. Larger outlets also have resources to quickly spin up formats that audiences are gravitating towards, such as vertical videos.

But those resources won’t hold if the underlying audience work hasn’t been done. For many publications, especially those that built their identity in the 2010s, that means narrowing focus. It also means adapting or even pivoting toward a new model. The rise of media events is telling: research from Vendelux, an event intelligence company, reported that 23% of publishers received a “large or very large portion” of revenue from events in Q1 2025, up from 8% in Q1 2024.

Chasing the wrong metrics

So the real lesson of the great traffic drop of 2026 isn’t that AI is consuming the media industry. It’s that traffic is losing its relevance as a success metric. Brands that have built businesses around things that aren’t just “articles”—such as subscriptions, newsletters, podcasts, and events—can still succeed, though with a somewhat altered definition of success. In almost all cases, the audience is smaller but more engaged in a way that’s measurable and monetizable.

For those that haven’t had that reckoning, however, the runway is getting shorter by the day. When all of the metrics around how you measure the success of your media business are falling, that’s a strong indicator you’re in the wrong business. There’s no more time to put off the hard questions about your audience, the value you bring, and how to connect those two in ways that can grow.

In other words, it’s time to panic.

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For years, publishers have lived between two business models: subscriptions and advertising. Now AI is putting pressure on both. In this episode of The Media Copilot podcast, Pete Pachal speaks with Colin Jeavons, founder and chairman of Nomix Group, to unpack what happens to the business of media when answer engines, agents, and AI-powered discovery tools begin to sit between audiences and publishers.

Listen or watch:

• YouTube
• Spotify
• Apple Podcasts

Drawing on decades of experience across publishing, search, and commerce technology, Jeavons argues that the biggest disruption is not simply AI summarization. It is the accelerating collapse of the old CPM-based advertising economy. As content explodes across social platforms, creator ecosystems, and AI-generated media, the supply of content keeps rising while the pool of ad dollars does not. That imbalance, he says, is forcing a reset.

At the same time, Jeavons sees a countertrend emerging: trust is becoming more valuable, not less. As audiences face a growing flood of low quality or machine generated information, publishers with expertise, authority, and niche value may find new strength in paid models, premium journalism, and smarter commerce strategies. The conversation explores what that means for newsrooms, review sites, AI discovery, shopping behavior, and the broader future of digital publishing.

Why this matters

AI is no longer just a tool layered onto the internet. It is increasingly becoming the interface through which people search, shop, compare, and decide. That has major implications for publishers whose businesses were built around traffic, clicks, and ad impressions. If AI answers reduce referrals and reshape consumer behavior, media companies may need to rethink not only distribution, but the economics behind their work.

This conversation looks past the hype cycle and gets into the harder question: what actually replaces the business models that no longer hold. Jeavons makes the case that quality journalism, expert reviews, and trusted vertical content are not disappearing. But the publishers that survive will likely be the ones that adapt quickly, invest in trust, and stop relying on scale for scale’s sake. It is a timely conversation for anyone thinking seriously about media, commerce, and the future of the open web.

What we cover

• Why Colin Jeavons believes 2026 is a turning point for media and AI

• The long shift from print and early web publishing to answer engines and agents

• Why the ad supported model is under more pressure than ever

• How AI generated content and user generated content are flooding the digital economy

• Why trust may become one of the most valuable products publishers can sell

• The future of review sites, affiliate commerce, and consumer buying behavior

• Why Jeavons believes premium journalism can regain value

• The case for micropayments and why publishers may have been too early with paywalls

• Why Google may resist making AI mode the default

• What AI shopping engines could mean for discovery, conversion, and revenue

• The broader societal risks and opportunities AI creates beyond publishing

About the show

To explore more conversations like this and see what’s new, visit the freshly updated 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.

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.

Frequently Asked Questions

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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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Patch.com’s readers expect their local site to be first on big stories, whether it’s a highway closure, a neighborhood fire or a fast-moving storm. But with one reporter often covering an entire town, and editors responsible for clusters of markets, the company needed a way to see beyond a single police scanner or a handful of Facebook groups.

Dataminr, a real-time breaking news detection platform, has become one of Patch’s central tools for doing that work at scale. By scanning thousands of public sources and flagging potential news events, the system gives editors minutes—or sometimes hours—of advance warning they would otherwise struggle to get.

The gist

Dataminr acts as a digital scanner for Patch’s distributed newsroom.

• AI-driven alerts flag breaking events across more than 1,900 communities
• Geographic and severity filters keep the volume manageable for small teams
• Editors treat alerts as tips, not facts, and verify before publishing

How they use it

Patch’s editors have built Dataminr into their daily and overnight routines.

• Geographic filters: Coverage areas are defined by city clusters and regions, ensuring alerts match Patch’s footprint.
• Alert tiers: Editors rely primarily on Urgent-level alerts for serious local events such as crimes, accidents and severe weather.
• Multi-channel delivery: Alerts arrive via email for searchability and through a web dashboard for real-time monitoring during shifts.
• Backup coverage: Breaking news editors use alerts to step into unstaffed markets, posting initial briefs and then coordinating with local reporters.

Key numbers

Dataminr and Patch do not publish specific performance metrics, but the platform’s documentation notes:

• Coverage scale: Patch operates in more than 1,900 U.S. communities
• Setup time: Initial configuration typically takes 1–2 hours; full customization and training 1–2 weeks
• Detection advantage: Alerts can surface events 5 minutes to several hours before traditional discovery methods

What to watch for

Patch’s experience with Dataminr underscores the need for guardrails.

• Verification burden: Alerts based on social media or scanner traffic require confirmation before publication.
• Information overload: Even with filtering, smaller teams can be overwhelmed without clear protocols.
• Fit by newsroom size: Dataminr’s own guidance suggests that very small outlets may struggle to justify the subscription cost.
• Workflow dependence: The platform delivers value only when someone is actively monitoring and empowered to act.

For Patch, Dataminr has not replaced reporters’ local relationships. It has, however, given editors a broader view of where trouble is starting—and a better chance of staying ahead of it.

Newsrooms can contact [email protected] for demos and tailored pricing.

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Google says it’s “exploring” giving publishers the ability to opt out of having their content appear in AI-generated search features like AI Overviews. The move, first reported by Reuters, comes as the UK’s Competition and Markets Authority opened a formal consultation on new conduct requirements for the search giant.

The announcement marks a notable reversal. As recently as May 2025, internal Google documents revealed the company had deliberately decided against giving publishers granular control over AI search features. Now, facing regulatory pressure, Google’s Ron Eden wrote in a company blog post that the goal is “to protect the helpfulness of Search for people who want information quickly, while also giving websites the right tools to manage their content.”

Why this matters for newsrooms

News websites and other publishers have seen click-through rates drop sharply as users rely on AI-generated overviews instead of clicking through to original articles. Google, which controls more than 90 percent of search queries in Britain, uses content harvested by its search crawler to build AI Overviews and AI Mode, as well as standalone products like its Gemini assistant.

The CMA’s proposal addresses this directly: it wants publishers to be able to opt out of Google’s AI features without affecting their position in general search results. That’s the critical distinction. Currently, blocking AI features means blocking search visibility entirely—an unacceptable tradeoff for most publishers.

“These targeted and proportionate actions would give UK businesses and consumers more choice and control,” said CMA chief executive Sarah Cardell. “They would also provide a fairer deal for content publishers, particularly news organisations, over how their content is used in Google’s AI Overviews.”

The fine print

Google’s response suggests this won’t be a simple on/off switch. Eden emphasized that “any new controls need to avoid breaking Search in a way that leads to a fragmented or confusing experience for people.” Translation: Google won’t implement controls that significantly reduce AI Overview coverage.

The CMA is also proposing changes to make search result rankings “fair and transparent” and to make it easier for users to choose alternative search engines—broader competition measures that go beyond the publisher opt-out question.

The consultation runs through February 25, 2026. Publishers can submit comments through the CMA’s dedicated portal.

What to do now

News organizations should consider:

• Submitting comments to the CMA consultation before the February 25 deadline
• Auditing current robots.txt and Google-Extended settings to understand your existing posture
• Monitoring referral traffic from AI Overviews specifically (available in Search Console)
• Coordinating with industry groups like the News Media Alliance or INMA on collective responses

This won’t be the last word. Google’s hedged language—”exploring,” not “implementing”—leaves room to water down eventual controls. But the CMA’s specific demand that opt-outs not affect general search rankings puts real teeth behind the proposal.

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ChatGPT made its debut when I was Chief of Staff at CoinDesk, and I ended up leading the publication’s approach to AI. Our internal AI committee quickly ran into an argument that felt simple on the surface but was surprisingly thorny underneath: Should we let AI systems index our articles, or shut the door?

The early consensus leaned toward “block them.” Even before the current wave of copyright fury, the logic was obvious: why hand over original reporting to AI companies that could summarize it, monetize the attention, and send us nothing but vibes in return? If compensation was the only language anyone understood, then withholding content felt like leverage.

But one person made the counterargument: If AI becomes the default way people retrieve information, he said, opting out doesn’t protect your work—it removes it from the record that AI users will actually see. Your reporting still exists, but it’s absent from the synthesized “answer” that becomes the starting point for everyone else. And if your stories aren’t in that amalgam, your competitors’ framing will be. The loss wouldn’t just be referrals (which, even then, we assumed would be minimal). It would be authority.

The cost of silence

At the time, the debate felt like a forward-looking thought experiment. Nearly three years later, it’s become the centerpiece of the media’s AI conversation. Presence inside AI summaries—whether you’re a publisher, a brand, or a PR team—is suddenly both urgent and poorly understood. Publishers are still fighting over copyright and compensation, and they should. But whatever the courts decide, a large and growing audience now encounters journalism through an interpreter. There’s a reason traffic to publisher sites dropped by a third in 2025: To many, AI is the new front door of the internet.

Back then, we didn’t have a label for the “let them in” strategy. Now we do: generative engine optimization or GEO (and yes, sometimes the first word gets swapped for “answer,” or AEO). When I’ve written about GEO before, it’s been framed as a pragmatic question: why participate in a system that summarizes your work and keeps people from clicking through?

But that question is backwards. The more useful one is harsher: what’s the price of refusing? And the answer is influence—specifically, your influence over what becomes consensus inside your domain.

The risk isn’t the loss in traffic—that will ebb away no matter what. Audiences are turning to AI as their information guides no matter what publishers do. What’s on the line is who gets to be the interpreter when the audience shows up somewhere else. For decades, journalism has set the baseline by reporting facts, validating claims, and establishing what’s known. That doesn’t just inform readers; it gives everyone else something solid to respond to. If those inputs aren’t present in the AI layer, the machine will still produce a picture of reality—just not a very good one.

And here’s the uncomfortable part: even if you opt out of AI summarization, your information won’t. Someone will re-report it. Someone will rewrite it. Someone will publish their own version, and some of them won’t block crawlers.

A foundational concept of copyright law is that, although works are copyrightable, the underlying facts and ideas aren’t. Except now those facts travel through someone else’s lens first. That lens becomes the “first draft” the machines reuse. Will it be incomplete? Probably. Will it still harden into the default answer as AI use expands? Also probably.

This is why the “block or die” framing misses what’s actually happening. Blocking AI from indexing your content means blocking yourself from having a say in what a rapidly expanding portion of the world counts as truth. GEO, in that sense, isn’t a growth hack. It’s a recognition that the old scoreboard—traffic, time on site, even subscriptions as a direct outcome of a single session—doesn’t capture the new fight. The battleground is the summary. The trophy is citation, narrative presence, and the long-tail compounding of trust.

Shaping truth at scale

None of that is an argument for surrender. Publishers shouldn’t shrug and let AI companies crawl anything they want for free. If anything, proving that your reporting is driving the consensus inside AI answers is the most concrete evidence of value you could ask for. The legal fights tend to focus on consent, copyright, and compensation. Fair enough. But GEO makes the deeper contest obvious: Who gets to shape meaning at scale?

Right now, it’s difficult to show—cleanly, repeatably—how specific pieces of content echo through AI-generated answers. That’s changing fast. Marketers, PR agencies, and brands are already pushing to measure GEO, refine it, and turn it into a playbook that blends content strategy, technical signals, and deliberate communication. Like SEO, it will always be more art than science. But by this time next year, I’d bet GEO won’t feel nearly so embryonic.

And AI itself will be an even bigger informational gatekeeper than it is today. Compensation matters, and the media shouldn’t stop demanding it. But litigation can’t be the only plan. Publishers also have to compete to be present inside the new crucible where truth is forged—because that crucible isn’t going away.

Journalists may no longer control the interfaces where people get information. But they still control the facts. The job now is to make sure those facts survive translation—and that the story that gets told at scale still has your fingerprints on it. Fighting for a better system doesn’t mean opting out of the one people are already using.

A version of the column first appeared in Fast Company.

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