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Perspectives

DCN’s media industry must reads: week of April 3, 2025

Here are some of the best media stories our team has read so far this week

editor sending out newsletters to build subscription and support subscription strategy
Featured Post | Revenue

How MIT maximizes editorial value with newsletters

For subscription-driven publishers, newsletters can be a valuable way of building relationships with potential paying readers. But it can be a challenge to effectively promote newsletters and justify the extra work required to create them. However, MIT Technology review has seen success with a portfolio of editorially-driven newsletters published across the week. Key to their growth strategy is effectively reusing the newsletter content online to drive sign-ups, and maximizing opportunities to promote the newsletters across all MIT activity.  

“Once someone has signed up to our newsletters, they’re two or three times more likely to become a subscriber,” said Niall Firth, executive editor, newsroom at MIT Technology Review.

With newsletters forming a key part of the publication’s subscriber funnel, promotion and growth of these products is a priority. Here’s how MIT Technology review structures its newsletter portfolio and promotes sign-ups to begin building those vital reader relationships.

Using the editorial to go deeper

MIT Technology Review has a variety of editorial newsletters in their portfolio. The Download is a daily weekday newsletter that features short, snappy summaries of key stories. It also includes a quote of the day, links from around the internet, and a throwback to a feature story that was published during the last year.

MIT also offers a selection of weekly “beat” newsletters. AI newsletter The Algorithm publishes every Monday, led by AI and hardware reporter James O’Donnell. Energy and climate newsletter The Spark comes out every Wednesday,  and The Checkup, focused on health and biotech news, is released on Thursdays. Editor in Chief Mat Honan then publishes The Debrief, an analysis of the biggest tech news story, every Friday.


In terms of editorial strategy, these newsletters begin with a full editorial piece of around 700 words, which can be used for scoops, analysis, or context around bigger stories. “These are written from scratch every week,” Firth explained. “[The writing] that goes in there is in there first, so if you sign up to a newsletter, you’ll get to read it before it appears anywhere else.”

The second half of these beat newsletters is used for other relevant links, news and bite-sized updates, as well as subscription upsells and event promotions.

Each beat newsletter is led by a named editor, as they find readers connect better with a person or expert. Editors are encouraged to be conversational.  “They’re like your smart friend guiding you through [topics]. So,  if something is complicated in the world of your beat, your reader can rely on them. They’re going to lay it all out to you and tell you what’s important, which bits you can ignore, what you should be aware of,” said Firth.

It also offers the opportunity to go behind the scenes in a way web-first articles don’t. Casey Crownhart, MIT Technology Review’s senior climate reporter and writer for The Spark newsletter was at the ARPA-E Energy Innovation Summit recently, a conference dedicated to energy technology. For the newsletter, she wrote about what it was like to be there, and the undercurrents around emerging technology and climate change. “The vibes were weird,” she reported, using a more explanatory and informal tone than would normally be used for an article.

Publishing newsletters as stories

One of the key drivers of MIT Technology’s newsletter growth strategy is effective use (and reuse) of the content. Although newsletter articles are written first and foremost for the inbox, they are then republished the following day as a story on MIT Technology’s website, with a note pointing out that newsletter subscribers saw the story first.

This achieves an often tricky balance between offering newsletter readers exclusive content. It offers an exclusive window to subscribers, yet allows MIT to promote articles to as wide a readership as possible.

“Once they’re on the site, they get treated and promoted like every other story,” Firth said. He also pointed out that sometimes these newsletter-first stories do as well as, or even better than, standard web-first pieces. 

When newsletter articles are published online, they appear with multiple notes about originally being published as newsletters, with sign-up boxes to capture interested readers. This also provokes a bit of FOMO (fear of missing out), and highlights that the value of the newsletter is in being the first to get relevant news.

MIT’s newsletter-first strategy lets the editors go deeper on stories that have already been published, as well as smaller or more timely scoops. Firth explained that there may be a big story from earlier in the week with off-cuts or reporting that didn’t fit into the story, but can be used as a whole new story for the newsletter. “That does double-duty: It’s cool to read an interview with a researcher on a topic that only got a line in the main story but is worthy of a whole separate interview. But then it calls back to the main story, and all fits together,” he said.

Although newsletter stories contain multiple calls-to-action (CTAs) for the relevant newsletter, Firth also noted that contextual newsletter sign-up boxes are promoted on relevant stories throughout MIT Technology’s site. Energy stories will have a promotion for The Spark, AI stories for The Algorithm, and so on. This means site visitors are given visible and frequent opportunities to sign up to newsletters, even on a first visit.

Linking newsletter strategy with events

Another tactic which has seen success in driving audience growth is visible promotion of newsletters at MIT events. The publisher has a stable of large-scale conferences and focused gatherings, from their flagship EmTech emerging technologies summit to digital leadership “classroom,” Future Compute.

“At all of our events, we have these massive boards in the lobby of the event. They have QR codes for all the different newsletters, with a specific UTM so we know it came from that event for that newsletter,” Firth outlined. 

He explained that both new event registrants or new subscribers to the brand get a dedicated email about the newsletters they can sign up to. For example, a registrant for their EmTech AI conference would also get an email from James O’Donnell, newsletter writer for The Algorithm, showcasing their weekly AI deep dive.

Relevant newsletters are also promoted at online events, including webinars and live streams.

Other growth tactics

Firth outlined a number of other strategies used to grow their newsletter audiences. MIT Technology Review has a hard paywall for around a third of the stories on the site. But for stories promoted on social media platforms, the team will offer access in return for signing up to a related newsletter.

“On Instagram, if we have a new big feature around AI, we do Instagram Stories where the ‘front page’ of the story would be the article, and the second page is a sign-up box to The Algorithm to get access to it,” said Firth.

The team has seen success using this tactic with some more surprising platforms like Reddit, too. Firth noted that Reddit attracts people who want to go particularly deep into various topics, rather than surface-level technology coverage; an audience their newsletters suit well.

Last year, the publisher experimented with exit intent popups – banners that appear when a user looks like they’re about to click off the page. Firth shared that these drove 4,000 new sign-ups over the test period last year. They are hoping to roll out a wider test of exit intent popups this year.

In October last year MIT launched a free six-week limited series newsletter, Intro to AI. Newsletter courses like this can be a good way of letting potential readers sample work without committing to a more regular newsletter. Each newsletter in the course takes the opportunity to promote the Algorithm.

Chief Executive Officer and publisher Elizabeth Bramson-Boudreau told A Media Operator that since launching, the course had attracted 17,000 subscribers with an average open rate of 57%. Now, the publisher is looking at other complementary areas to its regular beat newsletters, like healthcare.

MIT Technology review has also been experimenting with newsletter promotion swaps as part of its growth strategy. Axios and Semafor have been early partners for this, with newsletters exchanging ads for the other publication to attract interested audiences who are already engaged with newsletters.

Crucially, all newsletter promotions make it as simple as possible to sign up, with readers being asked for just their email address. 

There’s no silver bullet or one tactic that will result in sustainable newsletter growth. MIT Technology Review’s approach is to ensure that beat newsletters are consistently promoted across relevant pieces online. Every opportunity is taken – from events to social stories – to funnel audiences into topical newsletters. It is this combined, holistic approach that fuels MIT’s success.

Levers controlling revenue from multiple sources to show the revenue streams for streaming and digital video
Industry-Research | Video

Streaming revenue sources are shifting 

The transition away from traditional pay-TV is accelerating. In fact, traditional TV no longer dominates the video subscription market. By 2028, traditional pay TV’s share of video subscription revenues will decrease to just one-third. Meanwhile, digital pay-TV services, also known as virtual multichannel video programming distributors (vMVPDs), will increase their share from 13.2% in 2025 to 15.4% by 2028. These services, including YouTube TV, Fubo, and Sling TV, deliver linear TV content over the Internet, making them appeal to consumers seeking flexibility and lower costs than traditional pay TV. 

Emarketer’s Digital Video and Trends report for Q1 2025 shows that streaming services are poised to achieve even greater growth, increasing their share of video subscription revenues by about eight percentage points by 2028. Notably, YouTube has become a significant player in the subscription business. While YouTube remains known for its free, ad-supported platform, its YouTube Premium and YouTube Music services collectively boast over 100 million subscribers. YouTube TV, which claimed 8 million U.S. subscribers in 2024, is also contributing significantly to the growth of digital pay TV. 

Rising costs and consumer behavior 

Although subscription revenues still dominate the streaming sector, rising prices are reshaping consumer behavior. In recent years, both traditional pay-TV and streaming services have raised prices, driven by inflation. However, streaming services have increased prices at a faster rate over the past two years, surpassing the cost growth of traditional pay TV. This price disparity has triggered consumer pushback, especially as streaming services introduce price hikes and clamp down on password sharing. 

the prices of streaming services outpace inflation which drives streaming revenue

Streaming giants like Netflix, Hulu, and Disney+ employ strategies to boost profitability, including raising subscription costs and limiting account sharing. These actions, along with content cuts, have led to some consumer dissatisfaction. Despite these challenges, streaming services remain profitable on paper. 

Among the streaming platforms, Hulu and Disney+ have made some of the largest price increases for their ad-free plans. While Apple TV+ stays relatively affordable, its library lags behind competitors. All the while, it has  doubled its subscription price since launch. 

Live sports drives subscription growth 

Streaming services are capitalizing on the growing demand for live sports, which increasingly draws subscribers away from traditional TV. Major streaming platforms, such as NBCUniversal’s Peacock and Amazon Prime Video, continue to invest heavily in sports rights. This is further shifting the sports broadcasting landscape from traditional TV to streaming platforms. By 2027, digital sports viewership will surpass traditional TV viewership by 52 million viewers, signaling the ongoing transition in how consumers watch live sports. 

YouTube TV’s growth and the digital pay-TV market 

YouTube TV is seeing significant success among the growing digital pay-TV services. As traditional pay-TV continues to shed subscribers, YouTube TV is adding them at a steady pace. By 2026, it will become the largest pay-TV operator in the United States. Although YouTube TV is not yet profitable, it is an important player in the broader digital pay-TV market, now accounting for about one-fifth of total pay-TV subscription revenues. 

The digital pay-TV market is also experiencing consolidation. In January 2025, Hulu + Live TV and Fubo TV announced a merger. Disney will hold a 70% stake in the new venture, with Fubo’s leadership overseeing operations. Although Hulu + Live TV and Fubo will remain separate offerings, this consolidation may lead to further streamlining of the digital pay-TV space. 

Shifting streaming revenue streams: subscription vs. advertising  

Streaming subscription revenue

While subscriptions still represent the majority of revenue for streaming services, advertising is growing in importance. From 2023 to 2027, advertising’s share of total streaming revenues will increase by nearly four percentage points. This rise in ad spending reflects the growing significance of connected TV (CTV) platforms, a critical avenue for advertisers looking to reach consumers on streaming services. 

In fact, CTV ad spending may exceed 15.8% year-over-year growth in 2025, outpacing the 10.6% growth forecast for U.S. streaming subscription revenues during the same period. However, both advertising and subscription revenues in traditional TV are in decline, though price increases for subscriptions help slow the rate of decline. 

While this Emarketer report focuses on the U.S. market, it’s important to note that streaming services are also seeing significant growth worldwide. As of Q2 2024, nearly 60% of Netflix’s revenues come from outside of North America. While prices are lower in regions like Asia and South America than North America and Europe, the global growth potential for streaming services remains immense. Countries across North America, South America, Europe, and Asia-Pacific are seeing high levels of subscription penetration, with streaming services continuing to expand their reach internationally. 

Digital Pay TV contributes to streaming revenue

The video subscription landscape is undergoing a dramatic transformation. Traditional TV’s dominance is slipping as streaming services and digital pay-TV providers continue to capture an increasing market share. For media executives, this shift presents both challenges and opportunities.  

Subscription revenue remains the primary source of growth for streaming services. Rising costs and consumer demand for more flexible, lower-cost options continue to shape the industry. At the same time, the increasing importance of advertising revenue, coupled with the global expansion of streaming platforms, offers new avenues for monetization. Staying ahead of these trends and adapting to the evolving market dynamics is key to maintaining a competitive edge in this rapidly changing ecosystem. 

Ad Operations Professional using automation
Advertising | Supporter Spotlight

The tactical wins that follow automation in ad ops

For many Ad Operations teams, the deadlines haven’t changed, and neither have the expectations. But how the work gets done is finally starting to shift. Automation is leading the way, helping teams speed up processes, reduce errors, and ease operational strain.

However, the true value of automation begins after workflows are streamlined. From proactive optimization to deeper cross-functional collaboration, the real impact of automation is showing up in ways that go far beyond simply eliminating manual tasks. Here’s what changes when Ad Operations teams finally get the time and space to think strategically.

From bottlenecks to bandwidth: wins with the first wave of automation

For Ad Operations teams, the case for automation often starts with urgency. Reporting that takes hours. Campaign setup bogged down by manual handoffs. These aren’t abstract challenges, they’re daily frictions that delay progress, introduce risk, and drain team energy.

That’s why the first wins with automation tend to be tactical. This includes automating reporting, streamlining QA, and improving consistency in trafficking. And these wins are transformative. Workflows get faster. Makegoods and errors decrease. Pressure eases. But that initial wave of automation – as valuable as it is – only scratches the surface of what’s possible.

Because speed, while essential, isn’t the endgame. It’s the beginning of a broader shift. When time is no longer devoured by repetitive tasks, the conversation changes. The real opportunity emerges: what to do with the space automation creates.

How Ad Operations teams use the space automation creates

As automation clears the deck of manual tasks, the shape of the work starts to change. Hours lost to reports and errors are now redirected to analysis, optimization, and strategic collaboration.

Teams start catching issues earlier. They engage more closely with sales and strategy. They make in-flight adjustments that actually move the needle. Instead of being pulled in ten different directions, they finally have the space to focus on outcomes.

In our research, 63% of Ad Operations professionals  said their teams don’t have enough time to be proactive. That kind of constraint doesn’t just create stress – it blocks progress. But the teams that lean into automation aren’t just running faster. They’re thinking smarter, working better, and stepping into a more strategic role.

As one ad sales leader put it, “The benefit of automation is saving time and allowing me to do the other 60% of my job.” When the noise of execution quiets down, what emerges is a function that drives innovation, insight, and impact.

Unified workflows unlock better outcomes

Still, making the shift from execution to strategy takes more than time. It requires systems that support the shift. Ad Operations professionals need systems where workflows are connected, not scattered, with teams stitching the process together by hand.

In many organizations, media planning, creative approvals, campaign setup, and billing still live in separate systems. Teams rely on handoffs, manual updates, and cross-checking just to keep campaigns moving. The result? Details slip through, errors multiply, and opportunities to optimize are missed.

Automation is what brings those moving parts together. By integrating processes end to end, it eliminates manual gaps, accelerates handoffs, and ensures that data flows cleanly across tools. With real-time visibility, teams can catch issues early, make faster adjustments, and collaborate more effectively.

It’s no surprise that 59% of professionals named quality control as a top priority for automation. When workflows align, quality isn’t something you chase; it’s something built in from the start.

Automation makes scale possible – without more headcount

When workflows are unified and quality is built in, teams work more efficiently and are positioned to scale without breaking pace or adding headcount. That’s what automation makes possible. It doesn’t just help teams catch up. It gives them the infrastructure to take on more without compromising quality or timelines.

One Media & Entertainment company from our research saw automation increase their operational capacity by 30% to 50% – all without impacting headcount. For organizations facing tighter budgets and rising demands, that kind of lift matters.

It also evolves roles. As repetitive work is automated, time opens up for work that actually requires expertise: optimizing campaigns, solving problems before they escalate, and collaborating across sales and strategy. Our research found that 90% of professionals  are open to their roles evolving with automation because the nature of the work is already shifting.

Scaling used to mean doing more with more. Now, it means doing better – with the same team and the right tools already in place.

How automation aids Ad Operations from bandwidth to business impact

Automation may start as a fix for inefficiency, but its long-term value runs deeper. It redefines how teams operate, the way work flows, and where time gets spent. When repetitive tasks fall away, what fills the space is more revealing. Ad Operations professionals find themselves with greater capacity for strategic work, the ability for sharper decision-making, and a clearer path to performance gains.

This shift isn’t theoretical. It’s already underway. Teams are scaling without adding headcount. Workflows are aligning. Roles are evolving. And the impact of ad operations is expanding well beyond execution.

What automation ultimately brings to the table isn’t just speed. It delivers the momentum and operational readiness required for sustainable growth. And it offers Ad Operations teams a competitive edge in a dynamic, performance-driven market.

A concept image that shows elements of digital video production and measurement to suggest finding the ideal length for video
Featured Post | Video

Is there a perfect length for digital video?

England Women’s National Team soccer player Lucy Bronze is sitting in an armchair, in front of the camera, being interviewed for the BBC by her former teammate turned TV presenter Alex Scott. She explains that she was diagnosed with autism and ADHD four years ago and outlines how the conditions have impacted her hugely successful career.

It’s a significant conversation, but it didn’t go straight to a BBC channel. Instead, the final six-minute edit appeared on the BBC iPlayer last week and then YouTube. It was a perfect demonstration of an increasingly popular and important video format – and length.

Standing out from the video crowd

Videos that are a few, even 15, minutes long might not seem on trend in our scroll-happy world. However, in genres such as news and explainers this content length has proved to be powerful and increasingly popular.

There is an overwhelming amount of video available now and certain formats and lengths of duration are starting to stand out. Most noticeable are very long podcast episodes (think three-hour Joe Rogan episodes) and tightly edited, punchy social media clips lasting 60 to 90 seconds.

However, structured, often scripted, work lasting in the region of six to 15 minutes, is becoming a crucial part of some publishers’ strategies. Adam Tinworth, a lecturer at City St George’s in London and a commentator on audience strategy, said that “seven to 15 minutes is a kind of nice slot,” because publishers can “get a decent amount of depth without boring people.”

One outlet that produces this kind of content as part of a wide range of output is The News Movement. It publishes an eight-to-15-minute video on YouTube each month. Editor-in-Chief Rebecca Hutson told Digital Content Next that the work is “a kind of reinvented or slightly deconstructed documentary”.  She explained that her team strips out b-roll and lots of the other quirks we are accustomed to seeing on television because “it just doesn’t quite suit the medium”. The objective is to balance pace as well as depth. “The sequences are tight,” said Hutson.

Again, YouTube is the destination. Quite simply, the media companies want to go where they already know there is an audience, instead of trying to drag them to their own website.

“All our content appears quite differently on different platforms,” Hutson added, and this impacts the kind of work published there. “On Instagram, it’s a little bit more of a kind of leaning in experience, people are in a slightly different headspace…that content is appearing next to people’s friends and family.” 

It’s a point Tinworth echoes. He noted that TikTok is “not an environment where people are hunting for news-based stuff. They will encounter it, and they might consume it, but it’s not where they’re looking for it.”

Longer, perhaps more serious videos are viewed in a whole different context. Videos of longer lengths will be much more palatable on somewhere like YouTube. Viewers are increasingly comfortable with longer formats as they watch more YouTube on big TVs. Data from Tubular Labs published in July 2024 found that the number of videos over 20 minutes long being uploaded to YouTube each month rose from 1.3 million in July 2022 to 8.5 million in June 2024.

Specialist shows optimized for video length

Indeed, there are companies that are built around making highly produced videos in the six-to-15-minute-length sweet spot. Complexly, for instance make a range of shows, including science education content for children. Underknown also do this kind of work. (I particularly enjoyed learning what would happen if I fell into Jupiter as part of their “What If” series”.)

Explainers, in which a specific topic is unpacked in depth, work well “because those videos have an inherent longer life,” said Tinworth.  “You can build up this sort of body of explainer videos, which then drive traffic over long periods of time.”

Complexly is, at least in part, supported by Patreon. However, in general monetization of this kind of content seems to be based on the familiar pillars of advertising and brand sponsorships, sticking with the consensus where it is published.

Traditional broadcasters are experimenting with this format too. In addition to the Lucy Bronze interview, the BBC has previously created Ranked, a game show where groups compete for cash by guessing the correct ranking of things related to their shared passion or profession. It went out on both YouTube and the iPlayer CNN has created the more documentary-style Great Big Story on YouTube too. Nigel Dacre, a former editor of ITV news who now works as a media and digital executive said:

“In TV News, there’s an ongoing debate about how much TV news organizations should cut up their normal TV programs into short form reports. It’s not just for social media (which they all do), but also for their new streaming apps. ITV News really focuses on short form videos on ITVX, for example… a lot more than BBC News does on the iPlayer.”

Keeping control of your work

Giving work over to third parties who have… changeable… algorithmic and monetization criteria is something Jane Ferguson is trying to push back against. The eminent former foreign correspondent spent much of her career at PBS and has now founded Noospere, a subscription-based service that lets journalists own their own work instead of giving it to giant tech platforms. Think of it as a mix between Substack and a social media feed.

Yes, it’s another platform but “we’ve taken control of the distribution and put it in the hands of the journalists so effectively, you know, disintermediating the news business,” Ferguson explained.

Furthermore, “many of our colleagues and our contributors come from a Vice background where they really leaned into longer form filmmaking, but also that magazine length. I think that many field reporters have felt has been something that audiences, for years, have responded so well to. They want these more substantive pieces, but they don’t want to give you 45 minutes of their day,” said the Noosphere boss.

Ferguson also refutes the idea that not posting on giant tech platforms means you’re not going where consumers are. “We’ve gone to where the eyeballs are by going on our phones app first,” she said. For her, the hardware platform seemingly matters more than the software one.

As media executives strive to engage younger audiences, finding the sweet spot for digital video will be critical. Certainly, it’s not a one-size-fits-all proposition. Like the vast breadth of content that appeals to people, different lengths will suit different individuals.

As ever with creative work, this as much an art to finding the right length for video as there is a science. Testing with your audience will always be crucial. However, the success of companies like Complexly and Underknown, and the successful individual pieces of content like the Lucy Bronze interview demonstrates that seven to 15-minute-long videos are a powerful way to get in-depth information to viewers in an accessible format, particularly in the news and explainer genres.

Perspectives

DCN’s media industry must reads: week of March 27, 2025

Here are some of the best media stories our team has read so far this week

Closeup of helmeted female athlete's eyes to demonstrate a focus on niche streaming sports
Innovation | Video

How AI is changing the game for “niche” sports streaming

Sports and sports media outside of the major leagues often are labeled as “niche.” But that term is quickly becoming obsolete. Easy and inexpensive AI tools are changing the game. They create new sports media and marketing opportunities for free streaming and social-first athlete-creators, regardless of traditional audience bases and reach.

How is AI accelerating this transformation? It’s helping underrepresented sports and athlete-creators identify and capture new fans, super fans, and monetization opportunities. With smarter data analysis and faster content distribution, sports once considered “niche” have a chance to grow their media audiences and revenues in many ways.

How AI Is expanding the reach of sports

AI is widely used in sports media but it’s not just for the majors. AI presents opportunities for targeted streamers and independent creators. Here’s how leaders are using it to grow:

1. Identify and engage new fanbases

AI is helping sports organizations analyze viewership patterns, social media engagement, and fan demographics to uncover potential new audiences. By leveraging machine learning, teams and leagues can:

  • Identify super fans: Find those most engaged and willing to spend on tickets, merchandise, and streaming subscriptions.
  • Uncover new fan segments: AI can pinpoint audiences with similar behaviors and interests, even if they haven’t engaged with the sport yet.
  • Optimize monetization strategies: AI-driven insights help organizations determine the best ways to engage and convert fans through advertising, merchandise, and licensing opportunities.

2. Speed up content distribution

The way fans – particularly Gen Z fans – consume sports content has changed. Short-form videos, highlights, and real-time updates dominate engagement, and AI is making it easier to deliver this content faster than ever. AI-powered tools now handle:

  • Video ingestion and indexing: AI quickly processes and categorizes game footage for highlights.
  • Automated captioning and headlines: AI helps create more engaging, searchable content.
  • Smart clip generation: AI identifies the best in-game moments and instantly produces highlight reels.

This reduces production time and costs, allowing sports organizations to share media with fans faster and at scale.

3. Break language barriers and expanding globally

AI-powered translation tools are making sports media more accessible and global. Now, leagues and teams can automatically translate commentary, subtitles, and captions into multiple languages, opening doors to international markets and audiences.

  • More inclusive media: AI-driven translations provide accessibility for fans who speak different languages or have hearing impairments.
  • Stronger international engagement: With real-time translations, sports can reach new audiences without the need for costly localization efforts.

Athlete-creators: the new hybrid skill set

From NIL-driven revenue opportunities to the dominance of the Paul brothers, athlete-creators are increasingly leveraging AI. Are we looking at a future of sports in which the highest-performing athletes are not the best-known athlete-creators and vice versa? Yes, it may be challenging for some athletes without the resources or a team of assistants to fully realize their earning potential. However, AI may help level the playing field for athlete-creators. Here are some ways athlete-creators are using AI:​

  • Content creation and editing: AI tools can simplify design and enable quick creation of engaging content without professional design expertise.
  • Social media engagement: AI analysis of social media trends and audience preferences can be used for targeted creation strategies.
  • Streamlining distribution: Automation of delivery can make it easier for athletes to focus on training and performance while staying engaged with fans and optimizing revenue opportunities. ​

Ascendant sports: the next stage of AI-driven growth potential 

For an underrepresented sport looking for media expansion potential, new AI tools can help with assessing and answering some key questions:

  • Does it have a strong but underserved fanbase? If finding free, high-quality broadcasts is a challenge, it’s now much easier to explore serving a fanbase via free streaming options, from FAST to YouTube to other live social short-form distribution outlets. 
  • Does it need better production and distribution? AI-enhanced production – from graphics to real-time statistical analysis – can help sports that have previously not been considered TV-friendly, making them more exciting to watch and easier to follow on digital platforms.
  • Are there marketers looking to align with its fanbase? Using AI-enabled analysis of data, it’s easier to identify cost-effective and targeted opportunities to connect with sports fans. 

With the right application of AI and streaming strategies, ascendant sports can dramatically expand their audience and become stronger players in the sports content ecosystem.

The future: AI will define the next era of sports growth

The sports industry is at an inflection point. The traditional “big vs. small” sports hierarchy is being disrupted by technology, streaming, and AI-driven content strategies. Many sports, regardless of their historical followings, now have the opportunity to thrive and expand their reach.

A confused robot to show how AI search has trouble with news citations and attribution
Research

AI search has a news citation problem

Artificial intelligence is transforming the way people search for and consume news. With nearly one in four Americans now using generative AI chatbots instead of traditional search engines, the way journalism reaches audiences is shifting dramatically. While AI-powered search promises speed and convenience, it presents serious challenges for news publishers, including loss of attribution (citations), declining referral traffic, and misinformation.

A new Tow Center for Digital Journalism study highlights these risks, revealing how AI-driven search tools often fail to credit, or to accurately credit, sources and bypass publisher controls, such as paywalls. As AI search rapidly evolves, media executives must understand its implications and develop strategies to protect journalism’s integrity and financial viability.

AI search engines struggle with accuracy and attribution

The Tow Center analysis studies eight AI-powered search tools: Perplexity, Google’s AI Overviews, Bing Chat, ChatGPT, Claude, Gemini, Meta AI, and Grok. The research concludes that over 60% of AI-generated responses contain incorrect or misleading information. Unlike traditional search engines that list multiple sources for verification, generative AI tools present single, authoritative-sounding answers—often with a false sense of confidence.

When AI search engines provide sources, they cite syndicated or republished versions rather than providing a citation for the original publisher. This practice diminishes the visibility of primary news organizations and deprives them of direct traffic. Even more troubling, some platforms, such as Grok and Gemini, regularly generate broken or fabricated URLs, misleading users and reducing referral traffic to legitimate news sites.

AI platforms ignore publisher controls

Beyond attribution issues, many AI search tools fail to respect industry norms designed to protect publishers’ content. The study finds that AI platforms routinely retrieve content from sites even when publishers explicitly block them using robots.txt, a standard tool for controlling web crawling. This disregard for publisher restrictions raises ethical concerns and undermines publishers’ ability to manage the use of their content.

The Tow Center analysis also identifies inconsistencies in using publishers’ content with licensing agreements. Some news organizations with formal partnerships with AI companies still experience misattribution or see their content surface in ways that do not drive traffic back to their platforms. These findings suggest that agreements alone are insufficient to ensure proper credit or compensation for news publishers.

Revenue and engagement threat

For media companies, the rise of AI search directly threatens digital traffic, audience engagement, and revenue generation. Traditional search engines drive referral traffic to news sites, supporting subscription models, advertising revenue, and brand visibility. If AI search tools continue to bypass proper citation and link attribution, they could significantly weaken publishers’ brand recognition, authority, and ability to monetize their content.

Additionally, AI-driven search changes user behavior by reducing the need to visit source websites. Instead of clicking through to read full articles, users increasingly rely on AI-generated summaries, limiting publishers’ opportunities to engage audiences directly. This shift challenges established business models and forces publishers to rethink how they distribute and monetize content in an AI-driven search environment.

Responding to AI search disruption

Despite these challenges, there are opportunities to influence how AI search evolves. Since AI search models rely on high-quality journalism to function effectively, publishers have the leverage to demand better attribution, transparency, and enforceable policies. This study suggests four key strategies for publishers:

  1. Advocate for stronger AI regulations: Industry groups and publishers can push for more transparent policies that require AI search engines to cite and link to sources properly.
  2. Negotiate licensing agreements: While existing agreements show inconsistencies, publishers can strengthen negotiations to ensure AI companies provide meaningful attribution and compensation.
  3. Develop AI-optimized content strategies: As publishers adapted to search engine optimization (SEO), they must now consider how AI models surface content and explore ways to maximize visibility.
  4. Educate readers on AI search limitations: Publishers can inform audiences about the risks of AI-generated misinformation and encourage direct engagement with trusted news sources.

The Tow Center study concludes that media companies must remain proactive and ensure that AI search platforms operate with fairness, transparency, and respect for original reporting. The long-term health of the news industry depends on ensuring that AI-driven discovery tools do not replace or undermine the very sources that power them. By pushing for industry-wide standards and holding AI companies accountable, publishers can work toward a digital ecosystem where AI search enhances, rather than diminishes, quality journalism.

Perspectives

DCN’s media industry must reads: week of March 20, 2025

Here are some of the best media stories our team has read so far this week

A golden light bulb leaning against a copyright symbol to show how copyright protection supports AI innovation
Featured Post | Innovation | Policy

Copyright and AI: a win win

In terms of public policy debates, Artificial Intelligence continues to be the belle of the ball with nearly every major government courting the industry to locate their investments and jobs within their jurisdictions. Europe, China, Korea, and the U.S. (among others) have laid out competing tax and government spending plans to entice and encourage AI companies. Against this backdrop of AI frenzy, President Donald Trump, via the Office of Science Technology and Policy, has solicited input on the formation of an “AI Action Plan” in order to “define the priority policy actions needed to sustain and enhance America’s AI dominance.”

Unsurprisingly and unabashedly, tech companies advocate that the U.S. government allow their content-generating AI models to train on copyrighted material without consent or compensation. However, as DCN noted in our comments regarding the action plan, a key component to achieving the stated goal of enhancing America’s AI dominance – and the broader success of American businesses – is the robust protection and enforcement of U.S. intellectual property law including the Copyright Act.

The longstanding legal rights for copyright holders are derived from the U.S. Constitution (Article I, section 8, clause 8), which affords them the opportunity to monetize the results of their hard work and investment in a variety of ways and incentivizes them to reinvest in the creation of additional content and new innovative delivery mechanisms to potential consumers. As a result of these longstanding rights, American content creators, including news organizations and other publishers, are able to contribute significantly to U.S. economic growth, including through employment, exports and important trade surplus, and digital services and goods. 

According to a recent study, copyright-based industries accounted for 12.31% of the U.S. economy and 63.13% of the U.S. digital economy. From 2020 to 2023, these industries outpaced U.S. economic growth almost threefold. In the digital sector alone, copyright-based industries employ 56.6% of all employees in the digital sector. The annual compensation paid to core copyright workers is approximately 50% higher than the average U.S. annual wage. As for the global impact, the sales of select U.S. copyrighted products in overseas markets amounted to $272.6 billion, which exceeded the sales of other IP industries including pharmaceuticals, agriculture, and aerospace.

Unfortunately, the manner in which many AI developers have exploited original content without consent or compensation – to build and operationalize their commercial products – has unjustifiably violated the rights of copyright holders. It has upended the existing balance which has historically sustained and promoted innovation.

AI developers use copyright protected content not only to “teach” their models to predict and mimic language skills, but also as a means to create compelling outputs which have the compounding harm of substituting for the original works on which the models were trained. This activity unfairly competes with those who invested in the creation of the original material and undermines their ability to seek a fair economic return. In fact, U.S. Senior District Judge Beryl Howell noted earlier this week in a copyright case attempting to argue fair use that the publisher’s content is “so valuable they put a copyright on it.” Exactly.

By “reaping that which they do not sow” AI companies cause harm to creators, publishers and the ecosystem as a whole. It is important that this form of destructive misappropriation be deterred, whether by copyright law or other appropriate means. In the U.S, there are 39 related lawsuits and counting. The outcome of these suits will provide much-needed clarity regarding the application of existing copyright law, including the fact-specific defense of fair use, to the infringement of the rights of copyright holders to develop generative AI technology.

However, one U.S. District Court recently confirmed that licensing is required for the use of copyrighted content to train an AI system. In Thomson Reuters Enter. Ctr. GmBH v. Ross Intel. Inc., the court, applying clear and recent precedent from the U.S. Supreme Court, held that the defendant’s unauthorized use of the plaintiff’s works to train the defendant’s AI system was direct infringement and did not constitute fair use. The Court reaffirmed that the impact of the use on existing and potential markets is the single most important element of a fair use analysis, and that there was clearly a potential market to use the materials at issue in the case to train AI. 

Lest the VC crowd be dismayed, a licensing framework is emerging as many deals have been struck by publishers, record labels, motion picture industries, and others. OpenAI, Google, and Perplexity have all made efforts to pay for the right to use protected content to power their models and tools. This is a clear acknowledgment that this model is not only necessary, but eminently feasible.

While publishers’ rights are coming into clearer focus in the U.S., AI companies are  beginning to feel a shared pain as evidenced recently by DeepSeek’s R1 model. OpenAI accused the company of IP theft, claiming that DeepSeek may have used OpenAI’s IP and violated its terms of service to develop its AI model. 

“We know PRC (China) based companies – and others – are constantly trying to distill the models of leading US AI companies,” OpenAI said in a statement to Bloomberg. “As the leading builder of AI, we engage in countermeasures to protect our IP, including a careful process for which frontier capabilities to include in released models, and believe as we go forward that it is critically important that we are working closely with the US government to best protect the most capable models from efforts by adversaries and competitors to take US technology.”

A rising tide can lift all boats. Only maintaining existing copyright protections will lead to a robust, free market where creators are incentivized to make high quality works and AI companies are incentivized to license them. Importantly, in this robust market, AI companies would continue to have access to quality content which is critical for training and outputs. The American values of IP protection have been a cornerstone in our country’s innovative spirit and competitive edge over foreign adversaries. Protecting IP is a matter of preserving the core principles that distinguish American businesses in the global market. For the history of the U.S., copyright and innovation have gone hand in hand and there is no reason to deviate from that successful combination as we build the next chapter.

Read DCN’s Comments on the AI Action Plan, which were filed with the Office of Science and Technology Policy on March 15, 2025

Fingerprints on a face to suggest identity solution in digital advertising
Advertising | Supporter Spotlight

Why fingerprinting has a complex relationship with addressable advertising 

On February 16, Google relaxed its restrictions on fingerprinting for ad targeting and user tracking across a wide range of devices. Their December 2024 announcement reignited debates about privacy, security and the role of passive device identification in digital advertising. The announcement was certainly a radical reversal from 2019, when Google said it would block fingerprinting for its lack of transparency. But with this recent change of heart, Google now refers to fingerprinting as a technology designed to make it easier for advertisers to reach audiences across the open Internet and to harness the hyper-growth of connected TV (CTV) programmatic advertising.  

Google justifies its about face because, they suggest, advances in privacy-enhancing technologies (PETs) make it possible to protect audience data—including IP addresses and device fingerprints—in ways that are now more sophisticated than they were in the past.  

Maybe, but there’s a catch

Open Internet digital advertising—particularly programmatic advertising—is all about real-time addressability, measurement and performance optimization. Facing signal loss from fewer cookies and mobile device IDs, our industry has cleverly created a handful of new identity systems that utilize hashed emails (HEMs) and device fingerprints. While each of these technologies delivers a unique value to advertisers and publishers, they all come with certain downside commercial risks beyond their challenges to online privacy. Among the group, fingerprints tend to elicit a more negative reaction from privacy professionals. Frankly, it’s entirely reasonable to be concerned.  

That’s because fingerprints are passive and permanent. They’re passive because fingerprinting technologies can uniquely identify a browser or mobile device without anyone’s active acknowledgement or consent. They’re permanent because fingerprints can’t be deleted unless you change your browser or device. 

An express lane to data commoditization  

When publishers permit their audiences to be fingerprinted, that unique—and permanent—identity data immediately falls into the hands of a third party. Each fingerprint has the potential to siphon away valuable audience data, eroding the very asset publishers rely on for revenue.  As they say, “you can’t put the genie back in the bottle.” The audience data leakage risk for publishers is acute, and the impact is inventory value commoditization. Simply stated, when advertisers can find your uniquely identifiable audience more cheaply, they will. 

Despite these data leakage risks, it’s important we don’t throw out the baby with the bathwater. Device fingerprints serve an important commercial purpose because the lion’s share of the open Internet remains unauthenticated. Thus, absent a third-party browser cookie or mobile device ID, deterministic addressability and measurement are simply impossible.  

To put this commercial challenge into perspective, Safari and Firefox block third-party cookies, leaving 35% of the U.S. web unmeasurable. Apple holds 58% of the U.S. mobile market and more than half of users have entirely opted out of third-party in-app tracking with the remainder only selectively opting in.  

Fingerprinting can be an effective way to mitigate the commercial downside of these open Internet statistics. Yet there’s clearly a tension that requires advertisers and publishers to balance the business benefit fingerprints create for addressability and measurement. They must also factor in the importance of privacy—both in the face of regulation and in the context of consumer trust—as well as the underlying economic value of each party’s customer data and intelligence. 

Choose your next PET carefully  

If the Google Chrome team makes good on its promise of a “global cookie prompt,” then it’s very clear why the Google adtech team is suddenly much less opposed to device fingerprinting. When Chrome third-party cookies disappear, extended IDs—and especially fingerprints—will become the open Internet’s most scalable options for addressability, measurement, insights and optimization.  

Which is why now is when advertisers and publishers need to be investing in solutions that balance data protection with data accessibility at the speed, scale and low-cost parameters required for open Internet programmatic advertising. For brands, customer intelligence is a key competitive advantage. And for publishers—so many of whom have experienced first-hand what a decade-and-a-half of audience data leakage has done to the value of their inventory—the negative economics of loose data sharing practices are abundantly clear. For both sides of the buy-sell equation, consumer data is the key to performance.  

As the industry grapples with the evolving landscape of identity and privacy, the debate over fingerprinting underscores a broader truth: no identifier—whether fingerprint-based, email-derived, or otherwise—is without risk. The key lies not in avoiding identifiers altogether but in implementing strong, enforceable protections that preserve consumer trust while enabling addressability, measurement and performance across the digital ad ecosystem. 

human hands at a computer with lightening bolts to indicate Journalism and Journalists use of AI
Industry-Research | Innovation | Research

Journalists confront the reality of media use of AI

The rapid adoption of Generative AI (Gen AI) in newsrooms sparks important discussions among journalists and media professionals, especially about transparency and trust. Across the industry, publishers vary in how they communicate their AI strategies to their workforce. Reports suggest that some journalists seek more transparency around management’s AI implementation efforts and agreements with AI companies. This lack of clarity also applies to content, as some publishers explore AI-generated articles without consistently informing staff or readers.

A lack of transparency around AI fuels distrust

Mike Ananny and Jake Karr examine how news media unions are trying to manage and stabilize the use of Generative AI. Their analysis, How Media Unions Stabilize Technological Hype, draws from a review of industry reports, expert interviews, and case studies of newsrooms integrating generative AI. The methodology emphasizes qualitative insights to understand AI’s impact on editorial processes, ethics, and audience trust.

According to the authors’ analysis, many employees only learn about AI licensing deals through sudden announcements, often without prior consultation. Some must rely on external reporting to understand their company’s AI initiatives. Union representatives consistently face resistance when requesting information, reinforcing a broader mistrust of employer intentions.

However, solutions are emerging. Some unions are pushing for contractual guarantees to ensure greater transparency. The Associated Press and certain Gannett-owned publications propose contract language requiring 90 days’ notice before implementing new AI-related newsroom technology. Similarly, The Onion and Wirecutter unions successfully bargain for advance notice and transparency requirements regarding AI procurement. These efforts signal a path to restoring trust through openness and accountability.

Journalists defend creativity and quality

News professionals ensure accuracy, provide context, and uphold ethical standards that AI alone cannot fulfill. Ananny and Karr conclude that AI’s so-called “creativity” is a remix of existing human work, lacking the depth, insight, and contextual awareness that define quality journalism. No matter how advanced AI becomes, skilled journalists must verify facts, interpret events, and shape narratives with integrity.

Recognizing this, some media organizations are implementing safeguards. The Associated Press is committing to using Gen AI only with direct human oversight to maintain compliance with journalistic standards. Another example includes editorial employees reviewing AI content before publication at The Onion, The A.V. Club, Deadspin, and The Takeout. And the MinnPost treats AI-generated material as a source requiring human editing and fact-checking.

But beyond oversight, journalists are pushing for the right to decide whether or not to use AI. Many unions argue that workers, as experts in their field, should determine the appropriate role of AI in journalism. The CNET Media Workers Union demands the right to opt out of using AI if it fails to meet publishing standards. The Atlantic Union similarly insists that journalists may use AI within ethical guidelines, but no one should force them to do so.

These demands reflect a broader principle: journalism is, at its core, a human-driven endeavor. AI may assist but cannot replace the judgment, creativity, and accountability that define quality reporting. The analysis concludes that to integrate AI responsibly, newsrooms must prioritize transparency, trust, and human journalists’ role in safeguarding the profession’s integrity.

Beyond transparency and journalistic integrity, the rise of Gen AI raises significant ethical and legal questions. One of the most pressing concerns is intellectual property: Who owns the content produced by AI models trained on vast amounts of copyrighted material? Many publishers argue that AI-generated work lacks originality and merely regurgitates existing human-created content. This also raises potential plagiarism and copyright infringement issues. In response, some media companies are taking legal action.

Additionally, there is concern about AI’s ability to spread misinformation. Unlike human journalists, AI lacks the critical thinking skills to discern fact from fiction. Without rigorous oversight, AI-generated content can amplify biases, fabricate sources, and misinterpret data, posing a direct threat to public trust in news media.

Regulatory bodies are beginning to take notice. Governments worldwide are considering policies to ensure AI transparency and ethical implementation in journalism. For example, the European Union’s AI Act includes provisions requiring companies to disclose AI-generated content and implement safeguards against misinformation. The Federal Trade Commission warns companies against deceptive AI practices, signaling potential regulatory intervention in the media industry.

Balancing innovation and integrity for journalism and AI

Despite the challenges, AI’s presence in newsrooms is likely to grow. Some publishers are taking a proactive approach by developing AI policies that prioritize ethical considerations. Reuters, for example, offers internal guidelines to ensure journalists use AI tools responsibly and transparently. The BBC is similarly on board to maintain human oversight over AI-generated content and clearly labeling AI-assisted reporting.

Ultimately, the future of AI in journalism will depend on striking the right balance between technological innovation and journalistic integrity. The authors concur that if publishers prioritize transparency, enforce accountability, and uphold journalists’ fundamental role, AI can be a valuable tool rather than a disruptive force.

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