The recent boom in AI has brought both excitement and apprehension to the world of publishing. After discussions with many executives in publishing in companies such as Axel Springer, FT, World Media Group, and many more, I explore the best and worst-case outcomes for publishers navigating the AI landscape, examining potential revenue models, organizational changes, and the broader implications for the industry.
Best Case: Publishers Leverage AI for Enhanced Value and Experience
Revenue Models: In the best-case scenario, publishers harness AI to create more engaging, personalized, and diverse content for their audience. AI-driven analytics can enable publishers to understand reader preferences more deeply, tailoring content to individual interests and improving engagement. Additionally, AI can automate routine content creation tasks, allowing human writers to focus on complex, investigative, or nuanced stories that add significant value.
Publishers might adopt dynamic paywalls adjusted by AI to optimize subscriptions, where the system learns the most effective times and content types to prompt readers for a subscription. Advertising models could also become more sophisticated, with AI enabling hyper-targeted ads that are more relevant to the reader’s current context, significantly increasing their value to advertisers. A notable example of this in action is The New York Times, which uses AI to personalize content and recommend articles to readers based on their browsing history and preferences, resulting in higher engagement and subscription rates. [NY Times added 210,000 digital subscribers in last Quarter + Adjusted operating profit increased of about 41 per cent from a year earlier. source]
Organizational Outcomes: With AI integration, the structure of publishing organizations could evolve towards more fluid, interdisciplinary teams. Specialists in AI, data analytics, and user experience would work closely with journalists and content creators to develop stories that are both compelling and highly optimized for engagement. This could foster a culture of innovation, where data-driven insights lead to continually evolving content strategies.
Pros and Cons: Pros include increased efficiency, the ability to publish a higher volume of quality content, and enhanced reader engagement through personalization. However, challenges include the potential for over-reliance on AI, leading to a homogenization of content and the risk of undermining journalistic ethics if not carefully managed.
Jamie Credland, CEO of the World Media Group says
“The wide adoption of genAI will mean that content is easier to create than ever before, which means that ultimately the readers/audience will find it harder than ever to find the most quality news, insights or analysis on any subject. The good news here is that for some groups, e.g., speciality publishers or B2B publishers, who have sector-specific knowledge that is hard to replicate convincingly with genAI, the value of their content will increase, offering great subscription opportunities.”
Worst Case: Publishers Absorbed by Social Media and Generative AI Platforms
Revenue Models: In a less favourable outcome, publishers may find themselves increasingly dependent on social media and generative AI platforms for distribution and revenue. In the best version of this scenario, publishers could earn through a share of ad revenue generated from their content on platforms like Twitter or from subscription revenues of language models that utilize their data. This model risks commoditizing high-quality journalism, as the primary value becomes the data and content fed into AI systems rather than the stories themselves.
Organizational Outcomes: Publishers may see a shift towards producing content that is optimized for AI consumption rather than human readers, potentially leading to a dilution of brand identity and editorial voice. The emphasis on AI-friendly content could also lead to job restructuring, with roles focused on data analysis and AI optimization becoming more prevalent.
Pros and Cons: The advantages of this model include access to broader audiences and potentially lower costs associated with content distribution. However, the cons are significant: reduced control over content, the potential loss of direct relationships with readers, and a decrease in the perceived value of original journalism.
Jamie Credland, CEO of the World Media Group says
“The worst case scenario is that businesses stop valuing quality, investigative journalism, relying instead on using AI to rehash publicly available information and press releases. While this will be extremely cost-efficient and effective, genAI will never be able to hunt down stories, knock on the doors of key people, ask politicians questions they don’t want to answer, etc. If that’s the case, the media landscape as a whole will have much less quality information in it.”
What does the future hold?
The future of publishing in the AI era is not predetermined and will likely feature elements of both scenarios. Publishers that successfully navigate this landscape will be those that leverage AI to enhance their core strengths—creating compelling, high-quality content—while also experimenting with new revenue models and distribution strategies. The key will be maintaining a balance: using AI as a tool to augment human creativity and decision-making, rather than allowing it to dictate the direction of content creation and distribution.
Ultimately, the publishers that thrive will be those that adapt to the new technologies while preserving the integrity and value of their content in the eyes of their readers.
Alessandro De Zanche, founder of ADZ Strategies
“The impact of AI on publishers from a business perspective will mirror the impact programmatic advertising had on their revenues. Will they use AI as a tool to support their audience-centric strategies, or will they see it as an end goal? Depending on the mindset and approach, AI will be their best ally or worst nightmare.”
Case Study: A real-world example of a publisher leveraging AI effectively is The Washington Post, which developed its own AI tool, Heliograf, to cover routine and data-heavy stories. Arc XP (A CMS that aims to bring AI features) was also born out of the newsroom of The Washington Post.
It doesn’t hurt when your owner is Jeff Bezos!