American media publications with multiple websites, typically 20-30, are at a pivotal moment. They face declining traditional advertising revenue and fierce competition from digital platforms, yet they are eager to innovate and increase revenue. They focus on leveraging AI and exploring alternative ad strategies to stay competitive and effectively engage audiences.
Current Challenges
These publications are grappling with several issues:
Decline in Traditional Ads: The shift to digital has reduced the effectiveness of print and TV ads, impacting revenue.
Digital Platform Competition: Social media and other online platforms capture audience attention and ad dollars.
Trust and Economic Pressures: Growing mistrust in the media and rising costs, such as paper and printing, add to their challenges.
Changing Consumer Behavior: Audiences increasingly turn to digital devices for news, requiring new content delivery methods.
What They Are Looking For
For those with multiple websites, they need:
Scalable Solutions: Technologies that can be applied across all sites efficiently.
Centralized Tools: Systems to manage content, ads, and analytics across websites.
Personalization at Scale: AI will tailor content and ads for different audiences.
Cost-Effective Operations: Ways to reduce costs while maintaining revenue.
Detailed Analysis of Media Publications' Innovation and Revenue Strategies
American media publications, particularly those owning 20-30 websites, navigate a complex landscape marked by declining traditional advertising revenue, intensified competition from digital platforms, and shifting consumer behaviors. As of February 26, 2025, these entities actively seek innovative strategies to boost revenue, strongly emphasizing AI adoption and alternative advertising models. This note provides a comprehensive analysis, drawing from recent industry trends and specific examples, to outline what these publications seek and how they address their challenges.
Industry Context and Challenges
The media industry is transforming significantly, driven by technological advancements and changing audience preferences. Research indicates that traditional advertising revenue, particularly from print and TV, is declining due to the shift to digital platforms (Addressing the decline of local news, rise of platforms, and spread of mis- and disinformation online). A Pew Research Center report from September 2024 highlights that 86% of Americans get news from digital devices at least sometimes, with TV at 63%, underscoring the digital pivot (News Platform Fact Sheet, 2024 | Pew Research Center). This shift has led to competition from social media and other online platforms, which capture both audience attention and advertising dollars, as noted in a 2024 Deployteq article on media industry challenges (Challenges facing the Publishing and Media industry in 2024 | Deployteq).
Economic pressures, such as a 65% surge in paper prices in 2023, have made traditional models unsustainable, with some publications closing or rethinking strategies, like NME shifting to bi-annual editions (Challenges facing the Publishing and Media industry in 2024 | Deployteq). Additionally, growing mistrust in media, as detailed in a Pew Charitable Trusts report from October 2024, affects credibility and revenue, with local news trusted more than national outlets (Media Mistrust Has Been Growing for Decades—Does It Matter? | The Pew Charitable Trusts). Changing consumer behavior, with a preference for digital news, further complicates the landscape, as seen in a 2022 Census Bureau report on the decline of traditional media revenue (Internet Crushes Traditional Media: From Print to Digital).
What Media Publications Are Seeking
To address these challenges, media publications are focusing on several key areas:
Diversified Revenue Streams: The evidence leans toward exploring beyond traditional ads, with subscriptions, events, and e-commerce gaining traction. For instance, a 2024 NetSuite article on publishing industry challenges suggests diversifying revenue as a solution to economic pressures (6 Top Challenges in the Publishing Industry and How to Solve Them | NetSuite).
Enhanced Digital Presence: Improving online platforms is crucial to attracting digital ads and engaging audiences. A 2024 Digiday article on media buying notes the increasing use of AI in content production, which can enhance digital engagement (Media Buying Briefing: Agencies wonder whether generative AI leads to more wasted ad spending and production—Digiday).
AI and Data Analytics: AI is a game-changer for understanding audience preferences, optimizing content, and targeting ads. A 2025 Datafeedwatch blog lists AI advertising examples, showing how brands use AI for personalization, which media companies can adopt (11 Best AI Advertising Examples of 2025). Forrester’s 2024 report indicates 91% of US ad agencies are using or exploring generative AI, suggesting a broad industry trend (Forrester: 91% of US ad agencies are currently using and exploring generative AI | Marketing Dive).
Building Trust and Credibility: With mistrust on the rise, publications are focusing on transparent reporting. A 2024 Pew Trusts report emphasizes the importance of local news trust, which can be enhanced through community engagement (Media Mistrust Has Been Growing for Decades—Does It Matter? | The Pew Charitable Trusts).
Innovative Content Delivery: New formats like vertical video and AI-generated content are being explored. A 2023 AdExchanger article on BuzzFeed highlights their focus on short-form vertical video to compete with TikTok, showing innovation in delivery (With Advertising And Content Revenue Down, BuzzFeed Turns To AI And Vertical Video | AdExchanger).
For media companies with 20-30 websites, the needs are more specific:
Scalable Solutions: They require technologies that can be efficiently applied across multiple sites, as noted in a 2025 Setupad blog on ad networks for publishers, emphasizing scalability (15 Best Ad Networks for Publishers in 2025).
Centralized Management Tools: Systems to manage content, ads, and analytics are crucial, as seen in a 2024 NetSuite article on media industry challenges, highlighting the need for integrated solutions (14 Media Industry Challenges Explained | NetSuite).
Personalization at Scale: AI can tailor content and ads for different audiences, as evidenced by a 2024 Pecan AI blog on companies using AI for marketing, including personalization strategies (8 Companies Using AI for Marketing | Pecan AI).
Cost-Effective Operations: Reducing costs while maintaining revenue is vital, with a 2023 American Express article suggesting alternatives to social media marketing to cut costs (6 Alternatives to Social Media Marketing).
Specific Examples and Case Studies
To illustrate these strategies, consider the following examples of media companies with multiple websites actively adopting AI or alternative ad strategies:
BuzzFeed: Owns multiple websites, including HuffPost, and has been using AI for content creation since 2023, particularly for quizzes and personalized content. They partnered with OpenAI to enhance content generation, with CEO Jonah Peretti noting AI as part of their core business (BuzzFeed says it will use AI tools from OpenAI to personalize its content - The Verge). This has helped boost user engagement, potentially increasing ad revenue, as seen in a 2024 Hollywood Reporter article on their advertising gains (BuzzFeed Sees Small Advertising Gain Amid Push Toward AI).
The New York Times: With multiple digital properties, they are developing AI-driven ad targeting tools, such as BrandMatch, which uses generative AI to align ads with relevant articles, achieving a 0.40% average click-through rate, outperforming their averages (Exclusive: How The New York Times' Granular Gen AI Tool Drives Campaign Performance). They also use AI for content enhancement, like headline drafts, while maintaining journalistic oversight, as outlined in their 2024 principles for AI use (Principles for Using Generative A.I. in The Times's Newsroom | The New York Times Company).
Vox Media and OpenAI Form Strategic Content and Product Partnership - Vox Media
Why Adapting Advertising Strategies Is So Hard
1. Editorial Integrity vs. AI Automation
AI-driven news automation, such as Gannett’s use of algorithms to generate sports scores, aims to cut costs and speed up content production. However, this often clashes with the editorial standards and unique brand voices that readers expect from these publications. For instance:
The New York Times, known for its high-quality journalism, risks undermining its credibility if AI-generated content feels impersonal or off-brand.
Readers may distrust automated articles, leading to lower engagement—a critical problem for ad revenue, which depends on audience attention. When content quality slips, the ads tied to it can seem irrelevant or poorly placed, reducing their effectiveness and driving advertisers away.
2. Scaling AI Across Diverse Portfolios
These media giants oversee sprawling networks of publications, each with distinct audiences and content styles. This diversity makes scaling AI a logistical challenge:
Patch Media manages over 900 hyperlocal sites, each requiring tailored content and ads.
Lee Enterprises juggles 77 brands, each with its own identity. A standardized AI system struggles to meet these varied needs, forcing companies to invest heavily in customization. Without seamless integration, ad targeting suffers—AI can’t deliver personalized ads effectively across platforms, leading to wasted resources and missed revenue opportunities.
3. Ad Targeting That Misses the Mark
AI’s potential to revolutionize advertising lies in its ability to deliver highly targeted ads based on user data. Companies like The New York Times (with its BrandMatch tool) and BuzzFeed (focusing on personalization) are betting on this. But success hinges on the following:
Access to vast, high-quality datasets.
Sophisticated algorithms that adapt in real-time. When AI implementations are rushed or underfunded, the result is often irrelevant ads that annoy readers rather than entice them. Smaller, more agile competitors capitalize on this, adopting nimble AI solutions that outpace the clunky efforts of larger firms, further eroding ad revenue.
4. Resistance from Within
The human element complicates matters further. Journalists and editors at legacy companies like Hearst Communications and Advance Local often view AI with skepticism:
They fear job losses as automation takes over tasks traditionally done by humans.
They worry about declining journalistic quality, which could tarnish their brands. This internal pushback slows the adoption of AI tools, leaving advertising strategies stuck in limbo. Companies can’t pivot to data-driven ad models fast enough to stay competitive without full integration.
Real-World Examples of the Struggle
The table showcases how these companies are trying—and often failing—to bridge AI automation and advertising:
Gannett: Automates news like sports updates but risks diluting trust, impacting ad engagement.
Vox Media: Partners with OpenAI for product development yet struggles to scale solutions across its diverse brands, limiting ad effectiveness.
Future Outlook
Media publications with 20-30 websites are at a crossroads, needing to balance traditional values with modern technological advancements. By adopting AI and exploring diversified revenue streams, they can survive and thrive in the digital age. The key is to use these tools to enhance core strengths—quality content and audience engagement—while addressing operational efficiencies. As of February 26, 2025, the industry is witnessing a shift toward AI-driven innovation, with companies like BuzzFeed, The New York Times, and Vox Media leading the way, offering valuable lessons for the sector.
Key Citations
Challenges facing the Publishing and Media industry in 2024 | Deployteq
Media Mistrust Has Been Growing for Decades—Does It Matter? | The Pew Charitable Trusts
6 Top Challenges in the Publishing Industry and How to Solve Them | NetSuite
Forrester: 91% of US ad agencies are currently using, exploring generative AI | Marketing Dive
BuzzFeed says it will use AI tools from OpenAI to personalize its content - The Verge
Principles for Using Generative A.I. in The Times's Newsroom | The New York Times Company
Exclusive: How The New York Times' Granular Gen AI Tool Drives Campaign Performance
Vox Media and OpenAI Form Strategic Content and Product Partnership - Vox Media
With Advertising And Content Revenue Down, BuzzFeed Turns To AI And Vertical Video | AdExchanger