All over the world, publishers are trying to extract money from AI.

That’s because generative AI companies (like OpenAI) train their large language models on news companies’ products. But as recent court rulings have highlighted, these models only use a small portion of news content and, therefore, aren’t direct copyright infringement. As a recent Nieman Lab article says, “That publishers choose to make their content available to web users makes it harder to argue that an OpenAI or Meta web crawler had done special harm.” Thus, to infringe copyright, AI must generate outputs identical or near-identical to existing work to be infringing. This will be a hard battle for publishers to fight—even though a group of them began trying this summer to sue AI companies.

However, even if it isn’t to the tune of millions or billions of dollars, there are still several ways in which AI can help publishers make more revenue while reducing costs—all without taking writers’ and journalists’ jobs. About half of news publishers surveyed by WAN-IFRA in May 2023 said they are actively using ChatGPT or similar tools, with 70% expecting them to help, not harm, journalists. 

The monetary value of AI 

At a high level, AI can help save money because it allows publishers to do more with less and more quickly. The ability to produce more content—and the tasks associated with researching, copyediting, publishing, and distributing it—drives down costs for publishers in several ways: 

  • Slashing operational costs by automating repetitive manual tasks
  • Helping smaller teams and newsrooms scale faster 
  • Providing actionable insights to optimize content and marketing strategies 
  • Creating images quickly and cheaply
  • Increasing personalization and distribution accuracy

At the same time, AI can boost revenue for publishers by:

  • Personalizing content recommendations, improving user engagement and ad revenue
  • Refining audience segmentation so advertisers can better target specific demographics
  • Identifying spikes in traffic and on which pages to see the most popular stories
  • Strengthening subscription strategies by learning which content resonates most 
  • Improving search rankings for SEO by identifying trends, keywords, and user behavior

Now, for the specifics of how different applications of AI in publishing help achieve the above. 

Ideation

AI publishing tools can be used as thought starters to help recommend article topics based on what a writer has previously written in addition to headlines. These tools analyze large data sets to pinpoint patterns and trends that could produce a good story and provide background research. Examples of publishers using these tools include Forbes’ AI-powered CMS robot Bertie, which has helped double monthly visitors to the site, and Reuters’ Lynx Insight, which uses metadata to quickly match stories and keywords to available video or image media to speed production. 

Content creation 

Internet users want more and more content faster than ever. We can thank the one-click, instant delivery world we now live in, where we want everything from a pizza to personalized news stories with a snap of our fingers. AI steps into the rescue here with its ability to help publishers generate thousands of words in seconds, delivering information with speed and efficiency never seen before. Take the Associated Press, which has used AI for almost 10 years to provide breaking news and financial updates, or the Washington Post’s AI-powered Heliograf, which generates short articles on local events. 

Research and fact-checking

We all know the internet can send us down a rabbit hole when searching for the correct information. AI can help publishers and content creators sift through large amounts of text to pinpoint the best sources and linkages between information. For instance, new/s/leak by Hamburg University’s Language Technology helps navigate information on Wikileaks, and the University of London’s DMINR supports research and verifies news so journalists can work better with big data.

Copy editing

Anyone using Grammarly can attest to how helpful it can be for checking and cleaning up content. This is one example of an AI tool that can help edit articles faster than the human eye in alignment with specific style guides. These tools also help in creating a consistent and polished website. 

Optimizing reach in the cookieless future

Publishers and advertisers have had their work cut out in assessing new solutions to replace third-party cookies when they gradually descend into oblivion next year. First-party data is fantastic, but you can only do so much with information about known users. They need a little something extra to identify new potential readers. AI can help publishers use logged-in user attributes to build predictive modeling for targeting unknown audiences with similar characteristics to logged-in users.

Comment moderation 

Using AI to produce more content means more community comments to wade through, taxing publishers’ time and resources. AI-informed moderation tools can help flag users and comments before they drag down the quality of a conversation. When you no longer have to focus teams on removing spam and offensive commentary, publishers can pivot to higher-value, more strategic tasks. Disqus’ advanced moderation suite is one example of an AI-driven tool that offers comment filters with more specific categorization and controls so publishers can remove objectionable content with more precision and automation.

Betting your bottom dollar on AI

AI will continue to evolve and be tested by publishers of all kinds worldwide. Wherever you stand on these tools, exploring their use cases now will help you make sound decisions on their applicability to your website and its community going forward. Considering these tools alongside a robust audience engagement platform builds a secure foundation for innovation, engagement, loyalty, and revenue—something we can all agree that quality publishers want and deserve.