• The Verge | Former FCC staffers agree: Brendan Carr needs to be stopped (5 min read)
• Adexchanger | Streaming Platforms Are Embracing Vertical Video. But At This Point, Is It Worth It? (7 min read)
• The Financial Times | Streaming services give TV adverts a new lease of life (9 min read)
• Pew Research Center | A growing share of Americans say they mostly get news because they happen to come across it, not because they’re actively seeking it out. (6 min read)
• Poynter | Why can’t newsroom leaders just be normal about AI? (7 min read)
• Axios | Audio’s old guard looks to consolidate (4 min read)
• The New Yorker | Inside the World-Conquering Rise of the Micro-Drama (26 min read)

The post DCN’s media industry must reads: week of April 30, 2026 appeared first on Digital Content Next.

The implicit deal publishers had with search – make good content, earn rankings, convert traffic – no longer holds. The publishers in the best position today recognized early that this wasn’t a temporary dip and started planning for referrals to keep declining.

Search was always a rented audience

Search was always someone else’s distribution channel. Google’s incentives lined up with publishers for a 15-year stretch, and most of the industry built acquisition strategies on that alignment. The alignment is over.

It’s a familiar pattern. Social played out the same way. Facebook referral traffic peaked around 2016 and has fallen unevenly since. Any publisher whose acquisition engine depended on organic social reach has already been through a version of what’s happening with search now.

Owned channels are what’s left. The publishers who built them early are ahead and everyone else is catching up.

From traffic intelligence to relationship intelligence

According to Parse.ly data, across the publisher network it works with (more than 400 sites with 15B+ pageviews a month) the pattern is consistent. The publishers whose audience base has held up are the ones that started investing in direct and newsletter channels years before the search decline forced the issue. The ones that didn’t are trying to build that muscle now, during the decline, which is a much harder job.

Most publisher analytics, including ours, grew up in an era when the publisher’s job was to understand what search traffic did once it arrived. Which articles held attention. Which converted. Which didn’t. That’s content intelligence, and it was the right problem to solve when traffic was abundant and external.

The new problem is different. How does a reader move from a first visit to a repeat visit to a loyal relationship? What content earns the second visit? Which acquisition sources produce readers who stay? When should the newsletter signup appear, and to whom?

That’s a different type of analysis – one that we call relationship intelligence.

Three diagnostic questions

The starting point is a traffic-mix audit. This is not to confirm assumptions, but to see where things actively stand. Most publishers are surprised by what they find. Three questions cut to the picture quickly:

1. What percentage of your traffic is direct or newsletter-driven today, compared to 12 and 24 months ago? If that figure is flat or shrinking while search declines, owned audience isn’t developing fast enough to offset the loss.
2. Which pieces of content drive newsletter signups or repeat direct visits, as opposed to the ones that get the highest raw pageviews? These are often different articles, and the conversion-first bias tends to be under-examined in editorial reviews.
3. Where did your most loyal subscribers originally come from, and what was the first piece of yours they engaged with? The acquisition path that produces a long-term subscriber is probably the most underused signal in publisher analytics.

What owned relationships produce

Direct traffic converts to paid subscriptions at a higher rate than search-referred traffic. A reader typing in your URL or clicking through from your newsletter already has a relationship with your site. A search visitor often doesn’t.

Newsletters are the most concrete example. Publishers sent 28 billion emails in 2025 to over 255 million readers, with average open rates above 41%. There’s no intermediary algorithm between the publisher and the inbox, which is the whole point. The Financial Times now gets more than 70% of its subscriber traffic through its mobile app. That traffic doesn’t move if Google changes a ranking signal next quarter.

What’s missing: the audience connection

What’s missing in most publisher analytics today isn’t more pageview data – it’s relationship intelligence. The acquisition path that produces a long-term subscriber. The content that earns a second visit. The newsletter signup that started a ten-year reader relationship.

A reader who found you through a newsletter, opens your app a few times a week, and subscribed because they trust your coverage on a specific beat is not a reader Google or an AI assistant can reassign. That’s a different audience than the one search was providing for most of the last decade. It’s a much more valuable audience. And relationship intelligence is how you build it.

About the author

Bob Ralian is Head of Unified Analytics at Automattic, including Parse.ly, the content analytics platform for enterprise publishers. His team works with publishers to make sense of their audience data, what’s working, what isn’t, and what to do about it.

The post How publishers rebuild audience ties as search falls appeared first on Digital Content Next.

Ofcom’s Adults’ Media Use and Attitudes Report shows how this caution plays out. Audiences are spending more time online yet feel less positive about the experience, with only 59% saying the benefits outweigh the risks, down from 72% last year. At the same time, 89% feel confident online, suggesting they are comfortable navigating and using digital platforms. But that confidence does not always match their ability to distinguish reliable information from misleading content. These patterns point to broader shifts in how audiences engage with media, evaluate information, and build trust online. 

AI use becomes routine, but trust lags  

AI is moving into the mainstream quickly, with 54% of adults now reporting use, up from 31% last year. At the same time, 75% encounter AI-generated summaries in search. Adoption is not the issue. Trust is. 

Many users, 57%, say they trust AI-generated news less than human-written content. Widespread use does not translate into confidence. Even as AI becomes part of everyday experiences, skepticism remains high. AI may change how content gets surfaced, but it does not replace the need for visible authorship, sourcing, and editorial judgment. The gap between use and trust is not unique to AI. It reflects a broader shift in how audiences evaluate all media. 

Trust shifts while confidence holds 

Most viewers (85%) report using mainstream media, such as the BBC and The Guardian for news. But only 19% say they always trust it, while 21% say they always question it. This is not just a divide between those who trust and those who do not. It signals a deeper shift in how people evaluate information. 

Audiences now validate information socially. About 41% look at comments and reactions to judge credibility. In practice, a story’s reception can matter as much as its origin. Authority still matters, but it now competes with visible social context. Publishers no longer control how their content is interpreted once it enters digital environments. 

At the same time, confidence remains high. About 82% say they can spot scams, and 81% say they can recognize advertising. The results look different when tested, with only 52% correctly identifying paid search results. This gap highlights a difference between perceived ability and actual performance. 

Engagement is receding 

After years of expanding social media activity, behavior is starting to tighten, with posting declining from 61% to 49% this year. Only 14% of users say they explore new websites regularly. People are not leaving the internet, but they are narrowing how they use it. 

Sentiment declines alongside this shift. Only 36% say social media benefits their mental health, and 40% say their screen time feels too high most days. Less exploration and lower satisfaction point to a more cautious and selective user mindset. 

Data awareness is on the rise 

Most users understand that their data gets collected, with 89% aware of this. However, only 31% can identify how that collection happens. 

While 86% use at least one security measure, 26% still reuse passwords. People understand the risks around data privacy and security, but do not always act on them. At the same time, attitudes toward data use remain divided, with 34% comfortable and 37% uncomfortable with personalization. 

Younger does not mean more media literate 

These gaps are not evenly distributed. It is easy to assume younger audiences, particularly those aged 16–24, navigate digital environments better, but the data does not support that view. Younger users perform well in some areas, with 88% correctly identifying fake profiles. At the same time, only 52% recognize paid content in search. 

Older users, especially those aged 55 and over, often take a more cautious approach when dealing with scams or suspicious content. Media literacy depends more on behavior and experience than age, and it develops unevenly across contexts rather than following a generational pattern. 

The audience is recalibrating how it engages online. They still see value but feel less positive about the experience. This shift raises expectations. Trust is shaped by signals that show who created the content, where it comes from, and the context in which it appears. In this environment, clarity is a competitive advantage. 

The post Media audiences are engaged, but selective and skeptical  appeared first on Digital Content Next.

What seemed especially significant was not simply the scale of the change media leaders face. It was the degree to which they recognize what this moment requires. They must move from reacting to disruption to setting terms for it by defending the value of their content, deepening direct audience relationships, investing in unmistakably human differentiation, and applying AI where it creates real business advantage.

This became clear from the four big themes that stood out this year:

1. AI is redrawing the value chain around content

Unsurprisingly, AI was a nearly constant topic across sessions. One idea that cut across the event with unusual clarity, however, was that AI is not just another technology wave. It is forcing a fundamental reset in how media leaders think about the value of content, the economics of publishing, and the terms by which others get to access journalism and other professionally created content.

In his opening remarks, DCN CEO Jason Kint described AI as “the latest and most consequential event of an ongoing story” saying that it is disrupting “the value chain on the Web.”

That sense of responsibility and urgency echoed across many sessions. Nicholas Thompson, CEO of The Atlantic, talked in no uncertain terms about the fact that media leaders must work to shape the model so that publishers “will get the compensation they should,” even as he acknowledged the larger risks around scrapers, declining search, and disintermediation in an “agentic future.” Guardian CEO Anna Bateson emphasized the need to establish “the value of our IP” and protect the investment behind centuries of journalism.

Scott Havens, Chief Growth Officer and Global Head of Consumer of Dow Jones was even more direct about the value media companies bring to LLMs. In describing the way in which agentic AI is reliant on current, quality information, he said, “AI companies need our content and that’s not going to change.” The implication was unmistakable, however. If the industry does not actively assert the value of its work, someone else will define that value.

Perhaps the starkest articulation came from Jon Roberts, Chief Innovation Officer at People Inc. “Index for discovery is fine. Stealing our content is absolutely not.”

2. Audience strategy is replacing reach strategy

For decades, the industry’s growth logic was built around distribution at scale. Reach was the organizing principle. However, AI answers fundamentally change the math. Therefore, search strategies will no longer be reliable or sufficient to drive traffic or revenue.

Axel Springer’s Supervisory Board Chairman Jan Bayer noted that Business Insider has become “more focused on engagement and time spent now, less on reach.” That shift was emblematic of a broader theme. Again and again, leaders returned to the audience as the center of gravity: not traffic, not sheer distribution, but the depth and durability of the audience relationship.

COO Alex MacCallum described CNN as a “consumer first organization” focused on “delivering the most value to their audience.” That language resounded in other conversations about consumption habits, format flexibility, and the need to build around how audiences actually want to consume and engage with information.

At the Guardian, Bateson described a shift from being reader-funded to “audience-funded,” a semantic shift which recognizes that people are consuming journalism in many forms across video, audio, and visual formats. Award winning investigative journalist Julie K. Brown talked about the way her Substack and work for the Miami Herald reach different readers and create a bridge to new audiences. This approach is complementary, she said, rather than competitive. It allows her to use different tones, formats, and distribution models to grow the audience for her reporting.

As discovery is becoming less reliable, the business value of a direct relationship with the audience has risen sharply. This impacts product development and higher-level strategy. Media companies that know the audience, serve focused and meaningful needs, and create value across multiple formats are better positioned than those optimizing for reach. As Ankler CEO and Editor-in-chief Janice Min pointed out, the opportunity is not merely to serve narrow audiences, but to “broaden the total addressable audience” through sharper value and stronger relevance.

3. Human connection, talent, and voice may be the moat

Much of the AI conversation has been understandably dominated by automation, efficiency, and scale. But one of the most interesting through-lines of the event was the opposite idea: that the more abundant and synthetic content becomes, the more valuable human connection, recognizable talent, and editorial voice will be.

That point surfaced when COO Jen Wong described the agentic Reddit search experience as one designed not to replace conversation, but to drive people toward “human communication.” That framing stood out because it runs counter to the grain of so much AI hype. Wong says they must “never disintermediate human communication.” And, as CNN’s MacCallum pointed out: “AI can’t do the human-to-human connection,” which makes it a defensible moat.

That same logic extends to creators and talent. If human connection is becoming more valuable, then the people who embody that connection matter more, not less. In a market flooded with interchangeable output, audiences gravitate toward individuals they recognize, trust, and want to spend time with. That gives journalists, creators, and other distinctive voices a different kind of strategic value: They are not just contributors to the product. They are increasingly central to how media brands build authority, loyalty, and differentiation.

As Christine Cook, Chief Commercial Officer at Bloomberg Media put it: “Aren’t journalists the original creators?” Thus, surfacing their authority, authenticity and lived experience will build loyalty. Carlos King, Founder & CEO, Kingdom Reign Entertainment spoke about the strategic importance of “recognizable talent” and the “creator perspective” in an increasingly fragmented consumption landscape. And Min argued for “the value of voice.”

That connection between humanity and distinctiveness may be one of the most important takeaways from the event. In a noisy world with too much content, what stands out is not generic output but rather trust, perspective, and personality. As others pointed out, what matters is offering information people “can’t get anywhere else” and face-to-face experiences that create “genuine connection.” As King put it, we must harness the power of “human advantage.” Havens talked about the futility of ignoring creators and other talent ecosystems and encouraged his peers to find “ways to work with them.”

For leaders, this means the industry has to stop thinking about talent, journalists, creators, and experiences as nice-to-have complements to the brand. Particularly in an AI-dominated landscape, the people who create our content and human to human connection will define the brand.

4. Operational change is no longer optional

Many of the most grounded comments across the event were not about AI-generated content or media products. They were about AI’s impact behind the scenes to improve workflow, efficiency, product development, emphasizing the practical ways AI can help companies move faster and operate smarter.

Thompson from The Atlantic warned that too many companies are focused on AI in the “front of house” when it is “really useful in the back office.” Min drew a similar line for the deployment of AI in media companies: “On the backend: opportunity. On the front end: not so interesting.”

CNN’s MacCallum categorizes AI as something that can help create “better consumer experiences” and help media companies “be more efficient.” And Bayer from Axel Springer described the need to create experiences that are “personalized and relevant,” while still arguing that content creation itself should remain “a human area.”

These comments point to a meaningful leadership test: It is no longer whether or not to use AI, but rather where, how and to what end. Leaders who approach AI strictly as a shiny consumer-facing feature, or as a way to replace journalists risk missing the deeper opportunity to rethink internal systems, reduce friction, improve decision-making, and better align product, editorial, and business teams. For example, Havens from Dow Jones made a clear case for how AI can help business leaders accelerate the “speed to approval” to enable growth and innovation.

Guiding the future of media

Overall, the tone from the speakers and attendees at this year’s DCN Summit was one of leadership. Of stepping up and owning the challenges they face in order to shape the future.

They recognize that the old search and platform dynamics are weakening, that AI is reshaping the economics of content and that audiences want relevance, flexibility, and value on their terms. They also see that human connection, distinctive voice, and trusted talent are not being diminished by this moment. If anything, they are becoming more valuable.

Media leaders know the value of content and need to set equitable terms around access and compensation. They need to double down on business models that center on audience value rather than reach. A human-differentiated media market requires investing in journalists, creator partnerships, experiences, and products that offer unique value. But that doesn’t mean ignoring the value of AI. Rather, it requires understanding how to use AI where it strengthens the business — behind the scenes, in operations, in product intelligence, in speed and efficiency.

As ever, the future will be neither predictable nor easy. But, as the conversations at the DCN Summit made clear, it can and will be shaped by informed leadership.

The post Four forces shaping digital media and the leadership this moment demands appeared first on Digital Content Next.

But TIME is not just relying on AI companies citing their work. They have also developed and rolled out their own tool, TIMEAI. This is an interactive agent that has been trained on its 103 year archive in order to enrich the user experience on-site.

Time to train

TIMEAI, which appears on the site as a toolbar overlay, was initially tested at the end of 2024 with the annual reveal of TIME’s Person of the Year, Donald Trump. The toolbar was also put live on the three prior Person of the Year honorees; Taylor Swift, Volodymyr Zelensky and Elon Musk.

“There were several hundred articles about all four of them that we trained [the AI] on,” explained Mark Howard, Chief Operating Officer at TIME. “Person of the Year is our single biggest editorial event of the year. So it’s not like we put it on some back catalogue just to see if we could get some basic data. We put it on our most prominent release.”

The tech used was a small language model rather than a large one (LLM), so it was more straightforward to deploy. But it still needed training on TIME’s editorial styles, and guardrails added. TIME’s Editor in Chief Sam Jacobs and some of the newsroom team were brought in to help train TIMEAI in terms of style and tone.

“We had to, given the personalities involved, make some decisions about how it was going to handle questions that had nothing to do with anything we had written about,” Howard said. Even though there is a lot of publicly available information on these public figures, they decided they didn’t want the AI to use content outside of TIME. “It’s not a complete picture when somebody wants to converse, but we made a lot of those trade-offs in a very contained way,” he added.

The version deployed in December 2024 enabled users to translate the article, summarize it in various lengths, chat with it, and even speak to it using voice and audio in 13 different languages. Rather than just having one type of function, Howard said that being able to mix and match requests – for example, to ask for an audio summary then go into detail via text – sets this AI tool apart from many others on the market.

A wider rollout of TIME AI agent

The initial launch was a success. Howard said that the original toolbar was kept live while the team worked on bringing more TIME content into the AI. This wasn’t a straightforward task.

“Because of the way media companies operated over the decades, we had [content] in five different databases going back to the 1920’s, some of them were just PDFs of magazines that needed indexing and digitizing,” he explained. “Now it’s trained on well over three-quarters of a million pieces of content.”

Since November 2025, the TIMEAI agent has been visible on almost every piece of TIME content. Newly published pieces are also indexed in near real-time, ensuring that the answers given are up-to-date.

The team have also been experimenting with ways to get users to interact. The agent has a number of preset prompts to show how sophisticated queries can be. These can range from, ‘Try reading this article out loud’ to ‘Debate AI’s impact on humanity’ using TIME’s reporting and opinion archives.

The results so far have been encouraging. Users who engage with TIMEAI are 139% more likely to return to TIME when compared to those who don’t. Those using the AI agent also double their time spent on the TIME website.

Now, the focus is on encouraging those who may not be as familiar with AI tools to engage. Howard said that this may include putting more instructional overlays in, or feeding more preset prompts into the toolbar. But they are cautious about the extent to which people are routed into the full AI experience, rather than the standard web page. 

For now, Howard sees TIMEAI as an opportunity to increase engagement, rather than a revenue generator. “If we can get people to engage, every surface represents a monetization opportunity,” he added. “But the focus has been on the product itself in the beginning.”

A trusted agentic AI source

Given TIME’s licensing deals with other AI engines, there is a question about why users would come to TIME, rather than ask an AI which pulls in a wider range of sources, including TIME itself.

Howard was emphatic that trust is something the other AI tools don’t yet have, but TIME does. “A lot of people grew up with TIME, knowing and trusting that the red border stood for something, and there was a level of quality that is behind it,” he explained. “We want to carry that forward.”

ChatGPT and other answer engines do cite TIME content, but alongside a wide range of other sources, including sites like Reddit. These answers aren’t always trustworthy, and Howard said that there is a high burden on the consumer to deconstruct what is accurate and what isn’t.

“We think [TIMEAI] can be a trusted source of information to try and help explain the world in a way that TIME can, because of this vast archive,” he said, pointing out that users will only encounter TIMEAI if they’re already on the TIME site. This already signals a level of intent and interest in TIME’s reporting.

“It’s a way for us to pull our archives, our history, our heritage and our brand equity forward in a way that we can present more through an AI-based interface and experience.”

Howard is also clear on the role AI has to play in TIME journalism going forward. “Our journalists get information that only humans could by speaking to their sources and doing the work,” he emphasised. “AI can never do anything like that. It’s not intended to do anything like that. 

“Its purpose is to take the great journalism and then be able to make it accessible to those who want audio briefings, roundups and other formats to be able to better understand everything that we’re publishing.”

Walking the tightrope between using AI tools to help reporting, and letting them take over is something a number of publishers have fallen down on in the past months, with potential long-term implications for audience trust. 

Interactive agents present an opportunity for quality publishers to surface decades of reporting to add context and enrich the user experience. TIME’s approach is cautious, and they are wary of detracting from a carefully-designed web experience. But as similar tools roll out rapidly, readers will become more familiar with what they can do and how to interact with them. TIMEAI’s multi-feature functionality will set it apart as a leader.

The post Inside TIME’s rollout of its TIMEAI interactive agent appeared first on Digital Content Next.

• Wired | The FCC Has a Fast Lane for Complaints About Trump’s Media Critics (13 min read)
• Digiday | In Graphic Detail: New data shows publishers face growing AI bot, third-party scraper activity (8 min read)
• The Independent | Americans quit subscription streaming services in droves as cost of living continues to climb, report finds (5 min read)
• NiemanLab | Social traffic kinda stinks for news publishers now, in 3 charts (2 min read)
• Bloomberg | EU Unveils Age Verification App as Social Media Bans Gain Steam (3 min read)
• The Financial Times | Can the traditional British tabloid survive the digital age? (9 min read)
• Wired | The Internet’s Most Powerful Archiving Tool Is in Peril (9 min read)

The post DCN’s media industry must reads: week of April 16, 2026 appeared first on Digital Content Next.

While media companies tend to focus on periodic major events like new releases, fans want a steady stream of engagement with their favorite personalities, teams, and series across multiple platforms. Studies indicate that fans travel freely among formats in search of new content and experiences to satisfy their intrigue. The latest Digital Media Trends report by Deloitte explores how media leaders can engage fans more completely. 

The explosion of streaming, gaming, and digital media has given consumers unprecedented choice, but has also splintered their attention. As competition intensifies, media companies are doubling down on subscriber retention and audience growth. Feeding fan enthusiasm is essential to that effort – because fans aren’t a niche segment; they’re the majority.

The value of fans

About 80% of consumers self-identify as fans, according to Deloitte’s survey of 3,575 U.S. adults. That means they are enthusiasts of at least one entertainment category such as sports, TV series, films, gaming, or music.

Fans aren’t just a majority – they’re also extremely valuable to providers based on behavior. Fans spend almost an hour longer using media and entertainment daily than non-fans. They subscribe to more services (including gaming, music, and SVOD) – and spend more money on those services.

Demographically, fans tend to skew younger and engage more widely. They average 44 years of age (compared with 58 among non-fans). More than half (55%) of all fans, including 70% of millennial and Gen Z fans, say their fandom spurs involvement across multiple platforms, services, channels, merchandise, and events.

Lost Opportunities

While providers focus on new releases, fans often turn to social media to feed their fascination – via creators, user posts, and studio marketing. Half of fans say they discover new entertainment primarily through social media – that figure jumps to 73% of Gen Z and 68% of millennial fans. Yet this “social media first” approach isn’t being fully addressed by media companies.

While fans often discover content on social platforms, they frequently consume it elsewhere, splitting monetization across different services. This disconnect leaves media leaders with little visibility into fan behavior.

Over a third of fans (36%) report relying on fan or companion podcasts to stay involved with their favorites. This means leaving the main IP. Losing fans between new releases means providers spend heavily rebuilding excitement. Providers that can nourish these scattered audiences within their own ecosystems stand to gain in ROI.

Aggregation is key

Keeping fans connected off-season starts by aggregating fan experiences. Media companies don’t need to own every fan touchpoint, but they do need visibility and coordination across them. Embedding experiences like social feeds, podcasts, commerce, or games around their IP, even if powered by partners, would keep fans engaged within a single environment. Many would welcome this: about 40% (and nearly half of Gen Z and millennials) say they want all content related to their favorite IP aggregated in one place.

About a third of fans report buying merchandise related to their fandom in the last six months – a figure that increases to 37% among those who want fandom content aggregated. Fan‑focused bundles could package exclusive content, products, services, and experiences into personalized subscription or membership offerings, creating new partnership and revenue opportunities.

Keeping fans within a unified ecosystem gives providers richer first‑party data to personalize experiences, boost engagement, and drive revenue. With fans – especially younger ones – willing to share data for better personalization, coordinated touchpoints can turn the off‑season lull into a continuous relationship.

What about AI?

Can GenAI drive further engagement without alienating users? GenAI can help media companies produce content faster, personalize experiences at scale, and connect fragmented interactions into a unified destination. Research shows that fans are increasingly open to AI‑generated recaps, highlights, and personalized digests. Many fans report being open to AI‑generated ads, recommendations, and co-creating content, opening the door to more interactive experiences and revenue avenues.

Almost 40% of fans say they would accept AI-created content on SVOD, social media, music services, and in video games – if it is clearly labeled. 27% of fans say they may be interested in AI‑generated personalized digests about their favorite shows, and roughly a third of sports fans would be open to AI-generated custom highlight reels and commentary tailored to their teams and athletes.

But these figures reveal most consumers still have qualms. Media companies who employ GenAI in new ways to target content must develop clear terms of service around transparency and privacy. Reassurance around responsible use of GenAI is wise considering rising awareness of AI harms.

Consumers aren’t the only ones worried– media companies have valid concerns about losing control of their IP with open GenAI tools. Features that let users become creators can pose a risk to brand integrity and security. Embedding features inside their own platforms – with guardrails, tracking and moderation – may help media companies foster fan creativity while still protecting rights and capturing value.

The future of fandom

Fandom has evolved into a dynamic, always-on ecosystem. For media companies, winning strategies will reflect the full spectrum of fan behavior, from discovery to community. Those that capture and sustain that engagement within their own environments will turn fragmented attention into lasting relationships and real business value.

The post How the shift from audiences to fans drives media value appeared first on Digital Content Next.

Publishers understand what they’re up against. They’ve done the math. They know they need to engage audiences across social video, YouTube, audio platforms, and emerging AI interfaces, environments where discovery is driven by algorithms, not direct visits. Every day they work to balance maximizing short-term revenue while maintaining the user experience that builds and keeps an audience over time.

But execution is hard. And it’s getting harder.

To operate across more platforms and environments requires people and know-how that most publishers no longer have. Short-staffed teams can’t juggle dozens of disconnected tech vendors. Data doesn’t flow where it needs to flow. And the operational debt from years of patching together point solutions is making it harder to move fast.

Create. Transform. Distribute. Engage. Monetize.

To compete in a market now dominated by platforms, creators, and AI-driven discovery, publishers need to reorganize their operations around a clear set of functions: creating content, transforming it for different environments, distributing it effectively, driving engagement, and monetizing it across channels.

Create

Every successful content creator–from influencers to the best known media brands– has their secret sauce; their unique style or point of view. Many are rightly concerned that unconstrained use of AI will commoditize quality content, or that a torrent of AI slop will drown out the good stuff. This is why publishers have to be maniacal about quality and authenticity to create real consumer engagement. 

Transform

But how do you scale that quality content across today’s fragmented consumer landscape?  Here is where AI finds purpose. It turns out that AI is really good at taking content and adapting it to different environments and formats. With some expertise and guidance, it can maintain brand standards of quality, trust, and authenticity across many surfaces. 

Today, the words “publisher” and “website” cannot be synonymous. Content has to be created to meet the consumer where he/she lives. That includes the social platforms where the goal to drive traffic back to the publisher’s website is in opposition to the platforms’ imperative to keep the audience within their walled garden. The content then has to do double duty; yes drive traffic, but also maximize monetization programs that encourage customer engagement within even if the audience is experiencing your content outside of your site or app. 

Distribute

Once you’ve got content that’s tailored and transformed, the next problem is getting it everywhere it needs to be really fast. You cannot brute-force this. There aren’t enough hours in the day and there aren’t enough people on your team.

The market for consumer attention shifts constantly. The lifespan of a piece of content is finite: hours or days for news and longer for evergreen, explanatory, or enthusiast content. You need a real-time feedback loop telling you what’s still relevant, what’s gaining traction, and what’s already dead. Without that, you’re flying blind. And a piece of content that could have driven real revenue at hour two is worthless by hour six.

Speed isn’t a nice-to-have. It’s the whole game.

Engage

The goal of distribution is to drive engagement, because engagement drives revenue. The challenge is that the best format to engage with you may not be the same as what’s needed to engage with me. Some in your audience will prefer long-form video, some will prefer audio, some still prefer reading, and others will opt for short-form video. Other consumers will respond to more interactive experiences, like community boards, polls, quizzes, and games. Getting that right, at scale, for each individual is the engagement opportunity. And the publishers who solve it  are rewarded with more content consumed, more time spent, and more frequent repeat visits. 

Monetize

Let’s be honest about something. The platforms were not designed to make publishers rich. They were designed to keep audiences inside their walls, and they’re very good at it. For years, the monetization math outside your owned-and-operated properties was ugly, and most publishers knew it.

But something has shifted. Not because the platforms suddenly became generous. But because the pressure on them to attract and retain quality professional content has forced them to open doors they used to keep firmly shut.

YouTube now offers monetization models that generate real revenue for creators who treat their channel like a full-scale media business, not an afterthought. Its dynamic ad insertion tools give serious content owners the ability to operate more like TV networks, swapping sponsored segments in and out, extending the lifespan of sponsorships, and unlocking new monetization opportunities within existing content. Last year, Facebook made meaningful changes to its creator program, and publishers who wrote it off are quietly revisiting that math.

None of this is a windfall. The platforms will always take their cut. But “the platforms take a cut” and “there’s real revenue to be captured” are not mutually exclusive statements. The publishers extracting value from these channels aren’t doing it because the platforms are benevolent. They’re doing it because they’ve built the operational infrastructure to move fast, transform content for each environment, and actually work the monetization programs available to them.

That’s the opportunity. 

Shifting Thinking

While most publishers know they need expertise to help them extract value from their content wherever it is experienced, most are looking at the current moment with a clear-eyed view to extract as much value as they can. They are adapting to the current circumstances and are seeking out new partners who help them succeed. The partners who can consolidate data flows, simplify workflows and harness AI to automate processes will be their best friends. 

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As a result, notes AdExchanger editor Anthony Vargas, “Publishers, typically a tight-lipped crowd, have been surprisingly candid about losing 20%, 30% and in some cases even as much as 90% of their traffic and revenue over the past year.”

A survey of media leaders featured in the Reuters Institute’s latest annual predictions report revealed that publishers anticipate a further decline in traffic from search engines of more than 40% over the next three years. “Not quite ‘Google Zero’, contends author Nic Newman, “but a substantial impact none the less.”

In response, companies need to focus on how to address this challenge. And how to do so quickly, as traditional sources of referral traffic continue to hemorrhage. 

Five core factors to address Google Zero

Here are the five core factors that publishers should incorporate into their strategy and workflows.

1. Grasp the size of the problem

The term Google Zero stems from a question posed by The Verge’s Editor-in-Chief Nilay Patel who asked what would happen to businesses if their Google traffic were to go to zero?

Changes to social media and search algorithms have reduced referral traffic for some publishers. In the AI era, these dynamics are becoming even more pronounced. The impact of AI-snippets at the top of Google search results means that when users ask a question, they find answers at the top of the page and many don’t click through for more detail or scroll down for more options. 

Data from the Pew Research demonstrates the impact of this: when an AI summary appears, users click traditional search results only 8% of the time, compared to 15% without one. 

Meanwhile, for publishers pinning their hopes on Google Discover, it’s worth remembering that most of the growth in this space comes from breaking news, content which is often excluded from Google AI summaries. 

“Google Discover traffic is mostly a mirage,” contends the media analyst Simon Owens, recommending that media companies “avoid optimizing their content operations around it.” “Publishers never owned those audiences and therefore should never have counted on them,” he added.

Lastly, the situation is further exacerbated by content in replacing carefully crafted headlines from publishers with those generated by AI. Initially confined to content in Discover, this is now happening in Search too. As Sean Hollister, senior editor at The Verge, put it, “This is like a bookstore ripping the covers off the books it puts on display and changing their titles.” 

All of this is to say that if you’re still heavily reliant on Google as an engine for traffic, it’s time to think again. 

2. Understand that this is part of a wider shift in user behavior

Much of the coverage to date has focused on the supply side, centering on publishers and platform dynamics. Far less attention has been paid to the demand side and evolving user needs.

Traditional search feels increasingly outdated. In its place, users are turning not just to AI-generated summaries within Google, but to AI tools like Claude, ChatGPT, and Perplexity as they begin their information journey.

A recent study from Eight Oh Two Marketing, surveying 500 active AI users, found that 37% of those sampled now begin their search with these types of AI tools rather than traditional search engines. “Consumers are not choosing AI because it is trendy. They are choosing it [AI] because search has become too noisy, too effortful, and too slow.” 

At the same time, 85% of respondents said they still double-check AI-generated answers using traditional search, using these platforms for verification and deeper exploration.

Publishers need to recognize the implications of these behaviors. Those absent from the first phase, AI-driven discovery, may never be found in the second. Equally, those only visible in the verification phase are absent from the critical entry point of this new information funnel. If they’re not present in both of these environments, then they risk being overlooked and left behind. 

3. Recognize that visibility is increasingly binary

AI environments are far more winner-takes-most than traditional search. Previously, a publisher that ranked fifth on a search query would still earn traffic, as might those even lower. AI-mediated discovery cites a couple sources and if you’re not on the shortlist, you’re unlikely to be discovered.

For media companies, understanding how AI-generated answers are created is critical for ensuring that your content is featured in the places and spaces that LLM’s crawl. The foundations of good SEO, such as authority, clarity, credibility, still matter. Build on your SEO foundation; you don’t need to fully reinvent the wheel. 

Research on AI citation patterns shows that AI systems – like search engines before them – tend to favor sources with strong off-page authority. So, media companies will want to ensure that their content demonstrates the E-E-A-T (Experience, Expertise, Authoritativeness, and Trust) principles. 

That means having a presence on high-authority external platforms, citations in credible databases, earned media in leading publications, as well as content across the information ecosystem. This includes your own website, to thought leadership demonstrated by execs on LinkedIn and in publications like Forbes, through to engagement on Reddit forums, and material produced for other platforms such as company podcasts, YouTube videos, and so on.

A recent SEMrush analysis of 325,000 prompts across AI platforms found LinkedIn ranking second only to Reddit as a source for AI chatbot responses, particularly for professional queries. 

4. Build content that AI can’t replicate

Not all content is equally vulnerable to AI summarization. Sites that prioritize original storytelling, exclusive imagery, and strong visuals, can still thrive. 

According to The Digital Bloom, People.com saw a 27.52% year-over-year traffic increase through September 2025 by adopting this approach. Similarly, Substack witnessed a 40% year-over-year growth in July 2025. “This growth reflects users seeking authentic voices and first-hand perspectives,” they wrote. These are “content types that Google’s Liz Reid [VP, Search] specifically identified as gaining traffic in the AI era,” they added, referencing a discussion on wider online behavioral shifts that she had with The Wall Street Journal last year.

Conversely, if your content can be summarized in three bullet points by an AI, it is a commodity. That’s one of the reasons why a lot of evergreen content has been cannibalized and its traffic for many publishers has tanked. 

In response, many media companies need to simply produce less content and ensure that what they are doing is better. Content needs to be more meaningful. More impactful. More distinctive. Can it help to drive a conversion – in the form of a registration, a newsletter signup, or a subscription – so that audiences come to you first, and not their AI platform of choice? (And if not, should you be doing it at all?)

Similarly, media companies need to continue to invest in products that reduce dependency on external discovery channels. The New York Times is perhaps the best known proponents of this. Nearly half of Times digital subscribers now pay for more than one Times product, attracted by a mix of games, cooking, audio, news, opinion, product reviews and sport. Each of these are elements that can help to create habits and drive engagement that is independent of search.

5. Rethink what success looks like

The narrative is not so much that “AI is killing search,” but that AI should force us to rethink what search looks like. Search is no longer just a driver of traffic, it’s a multi-faceted arena covering discovery (AI chat), synthesis (AI chat and snippets), and verification (actually going to your content to dig deeper). 

As a result, publishers have to look more broadly at metrics they measure and value. In the AI-era, software company ClickRank, for example, points to areas such as citation frequency, brand mention rate, share of voice within AI answers, AI-driven referral traffic and sentiment of brand references.

And all of this sits alongside core metrics such as subscriber lifetime value, churn rates, and time on site. Chartbeat’s data shows us that “your most valuable traffic source might already be on your site,” reminding us that while addressing shift in search matters, engagement with existing visitors remains a key area of focus. 

As part of this conversation, at an industry level, we also need to move beyond discussing a reduction in referrals to better understand its impact on revenue. We know that clicks are down, but we know much less about what that means for subscriptions and ad yields. Hopefully publishers are already joining up these dots internally, but a wider industry conversation about this would also be beneficial. 

The bottom line

Worries about Google Zero are well founded, although its impact is uneven. Publishers that are most exposed to this shift are typically those with the heaviest dependence on evergreen, easily summarized content and platform-dependent traffic. Meanwhile, those that are best positioned to navigate these changes, are those who produce content that needs to be seen onsite or in-app, and who already have strong direct and habitual relationships with audiences. Off-platform discovery is part of their playbook, but they are not reliant on it.

There’s no point asking whether AI-powered search will disrupt the traditional referral model. We know the answer. Subsequently, Google Zero encourages us to think about distribution and engagement strategies at a time when search traffic is less predictable and the economics are increasingly hard to quantify.

As Press Gazette describes it, search is not dead, it is fragmenting. What the most successful publishers understand is that Google Zero doesn’t require a single response. It requires a range of them. That includes potential partnerships with tech companies and AI providers, optimizing distinctive content for generative engine optimization (GEO), as well as doubling down on user experience within your properties.  

These media companies recognize that we have moved beyond clicks to a more fragmented and distributed media ecosystem, one where value is defined not just by traffic, but by presence, influence, and direct relationships with audiences.

The post The publisher’s playbook for the Google Zero era appeared first on Digital Content Next.

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