Business leaders are feeling almost the entire spectrum of human emotions when it comes to using artificial intelligence (AI) to drive their businesses forward. Many media executives have told us that it is hard not to be curious, cautious, and overwhelmed by all the possibilities that AI offers. In particular, large language models (LLMs) are opening up new possibilities as organizations seek to optimize the teams and tools they already have to extract value from their exploding volumes of text-based data.

AI isn't here to replace the jobs of publishers and journalists; it's here to revolutionize the way they work, empowering them and streamlining their processes. In publishing, LLMs can improve efficiency, enhance the evaluation of new content, enable collaborative writing, and usher in a new age of media publishing.

Content Evaluation

One of the biggest challenges in publishing for this user is managing the vast amounts of text data in the form of documents, archives, research, and notes. The role of AI here is not to replace editorial decision makers, but to assist them.

Consider this: a 2018 study found that the publishing industry lost more than 15 million hours of productivity just evaluating manuscripts that were ultimately rejected. Using as²t to weed out unpublishable manuscripts and summarise document archive in the form of videos, charts or text manuscripts would dramatically reduce this time and improve their efficiencies. Employees would be free to focus on high-priority projects that really matter – such as identifying and advancing quality content.