The future of journalism is approaching, and it will be powered by Artificial Intelligence (AI). Throughout my career in news media, I’ve explored how AI can enhance journalism to create captivating storytelling experiences that not only engage readers but also encourage them to become paying subscribers.
The Traditional Approach to Journalism
Traditionally, journalism has followed a one-size-fits-all approach. Regardless of the audience’s diverse interests, everyone receives the same version of a story. This method overlooks the potential to better inform readers by tailoring content to their unique preferences.
The AI Revolution: Personalized Storytelling
Imagine a world where stories are personalized to each reader’s interests. Let’s take the example of a story about Amazon’s acquisition of Whole Foods, which was published in the Wall Street Journal where, as chief product & technology officer, I’m deeply involved in applying technology to empower journalism. This story can be tailored to different types of readers:
- The Investor: Primarily interested in the stock market implications of the story, they would receive a version highlighting this aspect, complete with interactive charts, graphs, and relevant visuals.
- The Health Food Enthusiast: Concerned about potential changes in food quality, their version would focus on the health and food aspects, accompanied by relevant charts, graphs, and images.
- The Concerned Local Citizen: Interested in the local impact of the acquisition, their version would focus on potential changes in local employment and food sourcing.
The Role of AI in Journalism
This isn’t about creating three separate stories. It’s about using AI to help journalists craft three distinct storytelling experiences from the same story. The journalist creates the content, and AI assists by drafting customized paragraphs and creating draft versions tailored to our readers’ interests. The journalists then review and edit the AI’s suggestions.
The result? A personalized story that enhances reader engagement, retains members, and attracts more paying members. This approach also makes it challenging for competitors to replicate our content.
The Future of Journalism: Superpowered Journalists
This is not about AI replacing journalists with bot-written stories. It’s about AI empowering journalists, giving them the ability to tell the story in a way that resonates best with each reader.
The power of AI allows us to customize headlines based on the reader’s persona. For instance:
- The Investor: Primarily interested in the financial implications, they might see a headline like “Amazon’s Strategic Acquisition of Whole Foods: What It Means for Investors.“
- The Health Food Enthusiast: Concerned about potential changes in food quality, their headline could read, “Amazon Buys Whole Foods: Will Food Quality Remain the Same?“
- The Concerned Local Citizen: Interested in the local impact of the acquisition, their headline might be, “Amazon’s Acquisition of Whole Foods: What Does It Mean for Your Neighborhood?“
This way, the headline directly speaks to the reader’s interests, making them more likely to engage with the story.
We can also tailor the images a reader sees based on their persona:
- The Investor: An image depicting stock market charts related to Amazon and Whole Foods.
- The Health Food Enthusiast: A picture showcasing high-quality, organic produce that Whole Foods is known for.
- The Concerned Local Citizen: An image of a local Whole Foods store that is familiar to the reader.
Personalized Story Body
Beyond headlines and images, AI can also help in personalizing the body of the story itself. This is where the concept of modular content comes into play. Journalists create the content as modules, like Lego blocks, that the AI can use to assemble in different ways to personalize it. The journalist still creates all the content. What changes in the personalized presentation is the order in which the modules (e.g., paragraphs) are presented to the reader and which modules are included in full, summarized, or omitted.
Let’s take our example of Amazon’s acquisition of Whole Foods and see how the body of the story could be personalized for our three personas:
- The Investor: For this reader, the AI might prioritize content modules that discuss the financial implications of the acquisition, the impact on Amazon’s stock price, and expert analysis on the future of both companies. It might also include a module summarizing the health and local implications, but these would be secondary.
- The Health Food Enthusiast: This reader would see modules that focus on the potential changes in food quality, Amazon’s history with food products, and expert opinions on the future of Whole Foods’ offerings. A brief module on the financial implications might be included, but the main focus would be on the health and food aspects.
- The Concerned Local Citizen: For this persona, the AI would prioritize modules discussing the potential local impact of the acquisition, including changes in local employment and food sourcing. It might also include a module summarizing the financial implications and the potential changes in food quality, but these would be secondary.
Previously, I referred to this as atomized content where editors create the content in the CMS analogous to atoms or molecules. However, I’ve found that the Lego analogy is more suitable. Just like Lego blocks, these content modules can be rearranged and assembled in countless ways to create unique, personalized narratives for each reader.
These personalized experiences could significantly increase click rates and reader engagement. After all, wouldn’t you be more likely to read and share the article if it was tailored to your interests? Such content sells itself.
The future of journalism lies in leveraging AI to create personalized storytelling experiences. It requires giving AI superpowers to our journalists and creating a more engaging and compelling reading experience for our audience. The future of AI journalism is approaching, and it’s exciting.