Publishers leveraging AI to optimize workflows, engage audiences, and streamline ad operations are driving innovation across their content and revenue strategies.
The AI race is sticky and has hurdles that could trip even the most seasoned publisher.
Despite regulatory and ethical hurdles, many publishers still see the tech as essential for crossing the finish line.
Publishers leverage AI to streamline workflows, generate audience-relevant content, and advance their ad and rev ops goals.
For instance, Burhan Hamid, CTO, TIME, views platforms like Glean as versatile tools that benefit multiple teams within a publisher’s organization. “Glean basically takes all of your company knowledge and turns it into a ChatGPT-like experience,” Hamid explains. “It’ll connect to your Salesforce, it’ll connect to your Google Drive, it’ll connect to all the tools you already use, and then allow you to ask it questions.”
He explained that having all information searchable and summarized in one place better prepares sales teams for client interactions, assists marketing with presentations, and equips ad ops with resources for wrap reports and similar tasks.
AI tools like this have massive potential to transform ad ops. “The opportunity for ad ops, if you look at things like what companies are doing with AI campaign generation platforms, is massive,” Hamid says. He also believes AI will shift the conversation around rethinking the end-to-end for an advertiser-to-publisher relationship.
In this AI tool guide, we’ll further explore how publishers leverage AI to bolster their ad and rev ops strategies.
Publisher’s AI Tools, Integrations and Partnerships:
New York Times – BrandMatch
New York Times Advertising has long been at the forefront of digital innovation, particularly in deploying AI and machine learning to refine ad targeting and drive monetization strategies.
Valerio Poce, Executive Director of Ad Product Marketing at The New York Times Advertising , explains, “For nearly seven years, our team has been leveraging proprietary data products to deliver advertising solutions that connect brands with highly valuable audiences.” This AI focus culminated in the launch of BrandMatch, a GenAI-powered product designed to offer advertisers more precise and personalized targeting.
Launched in July 2024, BrandMatch moves beyond traditional targeting methods, often relying on fixed audience segments. Instead, it uses AI to interpret each campaign’s marketing brief and create unique audience segments based on the readership of relevant articles.
“BrandMatch captures the nuances of each campaign by aligning targeting with content readership,” Poce says, “allowing advertisers to reach audiences in a highly tailored way.” This means similar campaigns can reach distinct audiences, maximizing relevance and impact by delivering customized experiences that connect more deeply with readers.
AI also helps The Times maintain its competitive edge, especially as third-party identifiers lose relevance. With expanded offerings like Games, Cooking, Wirecutter, and The Athletic, The Times now engages a wide range of audiences, opening up new opportunities for advertisers.
“Our investments in AI and first-party data allow us to align each brand’s message with the right content while offering resilient, privacy-conscious advertising solutions,” says Poce.
Hearst Magazines – Aura
Hearst’s AI tool, Aura, reshaped the company’s approach to audience targeting by blending behavioral, contextual, and predictive AI.
Mike Nuzzo, Senior Vice President, Data Solutions, Hearst, explains, “The industry has always done two things really well: behavioral targeting and contextual targeting. But they were always distinct and separate.” Aura’s unique approach combines these two elements through a proprietary taxonomy and predictive AI, creating what Nuzzo describes as “the third leg of the stool.”
This integration allows Hearst to identify audience interests and anticipate future behaviors accurately. For instance, Aura can identify that readers interested in pet food are also likely to be interested in outdoor activities or family vacations, offering brands a richer understanding of potential consumers.
Aura has a significant impact on ad effectiveness. “We looked at two metrics in the beginning—click-through rate and engagement rate—and saw double-digit increases in both,” Nuzzo says. Hearst’s new premium ad units, such as the Mega Hero Suite, further amplified these results. These premium placements drive even higher engagement when combined with Aura’s advanced targeting.
Beyond targeting, Hearst’s partnership with OpenAI demonstrates their commitment to harnessing AI while preserving the integrity of its editorial voice. “We partnered with them because they’re disrupting how consumers search the web,” Nuzzo says.
While Hearst remains enthusiastic about AI’s predictive power, it’s taking a measured approach to generative AI, aware of its limitations. As Nuzzo says, “We hope AI can support content ideation without replacing content creation. Our editors are the OG influencers, providing the creativity and depth that AI still lacks.”
Dotdash Meredith – D/Cipher
Jon Roberts, Chief Innovation Officer, Dotdash Meredith, explained the company’s approach to AI and machine learning, describing how they have utilized it for years through a dedicated data science team. Dotdash Meredith’s tool, D/Cipher, launched using pre-large language model tech, analyzes millions of articles and billions of annual user visits to understand consumer behavior across 40+ brands.
“Now that D/Cipher is fully integrated and powered by OpenAI, we are able to inform more sophisticated ad targeting solutions faster for our ad partners, still ensuring privacy since D/Cipher doesn’t rely on cookies.” Roberts noted.
Roberts also highlighted the benefits of integrating LLMs into brand safety efforts, especially in cases where traditional keyword-based filtering falls short.
“Keyword block lists are rudimentary and often lead to misclassification,” he said, recalling examples where advertisers blocked benign articles due to misunderstood keywords. LLMs, however, allow for nuanced content analysis, helping Dotdash Meredith maintain brand safety with greater precision. “This shift to LLMs lets us truly understand the content’s meaning, ensuring better alignment with advertiser standards and reducing unnecessary exclusions.”
Dotdash Meredith also understands the importance of collaboration between publishers and AI companies like OpenAI to enhance discovery and engagement.
“We see a real opportunity to create better information discovery by partnering with key AI companies,” Roberts explained. This partnership ensures that Dotdash Meredith’s content is cited and aligns with their commitment to producing unique, high-quality journalism without relying on AI for content generation. “We don’t publish content written by AI, but we see real value in using LLMs to help throughout the publishing process,” Roberts says.
Forbes – Adelaide and ForbesOne
In October 2023, Forbes unveiled Adelaide, an AI-powered search tool named after the wife of Forbes founder B.C. Forbes. Designed to transform news discovery and content recommendations for the publisher’s global audience, Adelaide harnesses advanced generative AI and provides users with personalized article suggestions and concise summaries from the past year’s content.
“We’re at a tipping point with AI, and every media company will need to decide whether to embrace it or not,” says Alyson Williams, SVP of Digital Operations and Strategies at Forbes. “At Forbes, we’re excited to strategically embrace it to build new products and to increase workflow efficiencies.”
During Williams’ keynote at AdMonsters PubForum last year in New Orleans, Adelaide was in beta for 5% of Forbes.com visitors. She announced how the AI-powered search engine would replace traditional site search with plans to incorporate Forbes’ complete content archive dating back to 1917. This AI-driven approach aims to enhance user experience and reader engagement, positioning Adelaide as an innovative solution for the growing needs of digital readers.
“We’re giving our editorial team insights they never had before,” Williams notes, “allowing them to learn about their audience in ways they couldn’t before and develop content that truly connects.”
Forbes’ commitment to AI integration has expanded beyond Adelaide, across editorial insights, subscription models, and personalization efforts. Editorial teams leverage the B2B publisher’s first-party data platform ForbesOne to uncover valuable insights, while predictive models boosted subscriptions by 187% compared to traditional methods. “AI has become crucial for personalizing experiences, whether for content, advertising, or subscriptions,” Williams shared.
Axel Springer – OpenAI and Microsoft Partnerships
Axel Springer was the first publisher to globally partner with OpenAI, integrating journalism more deeply into AI technologies.
Incorporating content from Axel Springer’s media brands, including Politico, Business Insider, and more the media company saw an opportunity to enrich ChatGPT’s user experience with factual and authentic information. ChatGPT users worldwide have access to summaries of selected global news content. This also includes articles traditionally inaccessible behind paywalls—which is especially interesting as some publishers are pushing against using paywalls. These summaries are accompanied by attribution and links to the full articles, ensuring transparency and providing users access to more detailed information.
Additionally, the partnership supports Axel Springer’s existing AI-driven ventures that build upon OpenAI’s technology. Beyond the OpenAI partnership, Axel Springer has expanded its collaboration with Microsoft, including new AI capabilities to pilot new AI-driven chat experiences and leverage Microsoft Advertising’s Chat Ads API for generative AI monetization.
Axel Springer CEO Mathias Döpfner sees AI as a force that could either transform media or elevate it. He stresses the need to embrace AI to boost journalistic efficiency and quality, envisioning AI handling tasks like layout, re-writing, and aggregation. This would allow journalists to focus more on meaningful work, like investigative reporting and uncovering new stories.
Vox Media – OpenAI Partnership and Forte
Vox Media collaborated with OpenAI to enhance user experiences across Vox Media’s portfolio of brands, including Vox, The Verge, and New York Magazine.
A key focus of this partnership was boosting the effectiveness of Vox Media’s affiliate commerce product, The Strategist Gift Scout. The search engine for gift recommendations employs OpenAI’s technology to better match shoppers with perfect Strategist-endorsed gifts. This application demonstrates Vox Media’s commitment to AI as it enhances revenue-generating features that benefit both users and the company.
But this wasn’t Vox’s first rodeo working with AI. Launched in 2019, Vox designed Forte to drive outcomes for advertisers, boasting targeted impressions that perform twice as well as alternative data sources. Utilizing OpenAI’s capabilities, Forte has become even more powerful. With AI enriching data management and ad ops goals, Vox’s advertising partners receive stronger creative optimization and more precise audience segment targetings.
Snopes.com – FactBot
Renowned fact-checking website, Snopes.com, has integrated an AI-powered tool called FactBot to enhance user interactions with its extensive repository of fact-checked articles. By leveraging an AI model with Snopes’ extensive archives, they designed FactBot to verify the truthfulness of various claims and rumors. Users can submit questions about various topics, including news, politics, and entertainment, to ascertain their validity.
Snopes developed the FactBot with Cal Poly’s DxHub and Amazon Web Services, using Amazon Bedrock, the Amazon Titan Text Embedding model, and Anthropic’s Sonnet 3-5 model.
This AI system quickly processes user queries to deliver concise, accurate summaries from Snopes’ content, enhancing user experience and spotting emerging content trends. When data is lacking, the system avoids generating inaccurate answers and notifies users instead. FactBot also avoids hallucinating answers when it lacks sufficient information, instead informing users that it doesn’t have enough data to respond.
As Snopes’ Chief Revenue Officer, Justin Wohl, explained on our recent LinkedIn Live, this strategy helps Snopes understand audience interests and expand content. Still, Wohl highlights the high cost of generative AI, with each query costing roughly five times more than it earns. He recommends thoroughly assessing potential benefits and costs for AI tools and focusing on practical uses that enhance efficiency and boost revenue.
Regulatory Roadmap: How Publishers Can Legally Leverage AI in Ad Targeting and Content Creation
Integrating AI-driven tools requires publishers to navigate privacy laws, intellectual property issues, and bias prevention strategies.
“Publishers should start by examining state AI laws in the U.S.—particularly in Colorado, Utah, and California—to see if these laws apply to them directly,” advises Myriah Jaworski, a Data Privacy attorney at Clark Hill.
For instance, California’s Privacy Protection Agency is developing rules focused on automated decision-making tools, including AI for ad targeting, which will directly impact publishers. These regulations may require publishers to offer consumer disclosures about how AI tools are used and may even involve transparency measures like AI watermarking or access to AI detection tools.
To address AI-related bias, publishers must regularly test and monitor algorithms to prevent discriminatory outcomes. “Businesses should consider conducting bias assessments for their AI tools, similar to processes outlined by New York Local Law 144,” Jaworski notes. This involves assessing for fairness pre-deployment, annually, or whenever publishers make major modifications to ensure compliance and maintain ethical standards.
Transparency and accountability are essential. Jaworski explains, “Clear disclosures, whether standalone or embedded in privacy policies, are key.” IP considerations are also crucial, especially in AI-generated content. For copyright protection, publishers must ensure substantial human involvement in AI-assisted creations. “IP standards are still being clarified, but publishers should work closely with counsel to navigate these emerging issues,” she emphasizes.
Incorporating AI technologies allows publishers to engage audiences in new ways, streamline ad operations, and develop tailored content. As they maneuver complex regulatory and ethical considerations, publishers are finding the balance between AI-driven efficiencies and the creativity and depth that define quality journalism. Through strategic partnerships, robust AI tools, and adherence to privacy and bias regulations, publishers are enhancing audience experiences and setting new standards for responsible AI use in media.
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