A tale of two strategies

As AI rewrites the rules of content production, publishers face a new kind of goodbye - not to audiences, but to old habits.

May is publishing-conference season, and once again, we're caught between AI doomsday predictions and comforting assurances that quality content is irreplaceable.

But - what exactly is ‘quality content’?

AI will inevitably disrupt certain types of publishing - it disintermediates information, processes it on demand and is available through ubiquitous interfaces. Can AI delight readers with a style so unique that it dazzles the senses and sings odes to the human soul? Maybe not. But it would be presumptuous to assume that, for many practical purposes, AI-generated content is not good enough - or that audiences would even care enough to notice. 

Evolution of the Publishing Value Chain - Consumers

Before the Internet, publishers owned the whole user journey - from interviewing sources to physically delivering newspapers and magazines to doorsteps. Newsstands may have stocked sweets or books, but their main attraction was always printed media.

Search engines disrupted the first link of this chain. Suddenly, information such as weather forecasts and sports scores was available instantly, free of charge, and everywhere, pushing publishers towards deeper analysis and commentary. Generative AI now takes this further, radically reducing the cost to create content from less structured and predictable datasets.  

AI Push vs. Pull

Besides enabling audiences to ‘pull’ content directly from public sources (such as an analyst retrieving company financials), AI also dramatically decreases the cost for organisations to ‘push’ their stories directly. Entities traditionally dependent on journalists and PR firms -  such as parliaments, police, courts, industry associations, local governments and sports teams -  can now create and disseminate their own content.

This opens up new opportunities for monetisation, creating space for low-cost ‘publishing enablers’ to undercut traditional content marketing agencies. 

Some of these outputs will require humans in the loop and will be consumed by humans, competing with conventional publishers. Others will be fully automated and/or AI consumed, driving the emergence of bot-friendly flat formats.

So, where do publishers fit in Robotland? 

Publishers’ vulnerability to AI depends on how easy it is to substitute their content. Pricing and user sophistication play a role: high-value B2B clients, for instance, who pay thousands for information, are more likely to explore substitutes. However, the two key drivers of differentiation are specialisation and exclusivity. 

Specialisation is defined by the level of precision in fulfilling user needs, either through user experience or through coverage of niche interests..

Exclusivity can arise from proprietary data and insights, a recognisable editorial style, or the reputation of named authors.

Coverage based on publicly available information, especially content reliant on curation and summarisation, which features heavily in some journalistic genres and B2B information services, is particularly vulnerable to AI competition. 

Impact of AI cannibalisation depending on content characteristics

Trust as a competitive advantage

Proprietary, trusted content has always been a major driver for differentiation: exclusive interviews, original analyses or primary research. The FT and other successful publishers fiercely guard their star writers, well-connected reporters and Pulitzer-winning investigative journalists. As free content proliferates (and trust declines) unique perspectives become even more valuable. 


Reinforcing the ‘human touch’ by building the personal profiles of journalists and analysts, and enabling direct audience interaction through live events, Q&A chats and social media will help maintain trust and audience loyalty. However, this approach can be costly. Top talent is a limited resource. Recognisable names also become more difficult to retain as they are tempted by platforms such as Substack and YouTube, where they can monetise their content independently. 

Two paths to resilience

The Multi-Specialist Approach

Publishers can also thrive by packaging non-proprietary information in ways that directly solve readers’ precise problems or save them time. This opportunity is most obvious for specialist and hyper-local publications, but it can also be successful for building communities around shared niche interests, even when relying on user-generated content and commentary. 

Generative AI enables hyper-focused segmentation and personalisation through scraping and processing of data and automated, customised aggregation and distribution of content. The more targeted the niche, the more likely it is that it adds value to the audience. This opportunity is most obvious for specialist and hyper-local publications, but developing communities of interest around different themes, even if reliant on user content, can also generate a network effect and be difficult to replicate once established. 

A faster product development lifecycle will create demand for agile, innovative-driven thinking within newsrooms - editorial culture will be a major differentiator - or inhibitor - to evolution, as will the availability of audience analytics and testing capabilities.

Conclusion: Lessons for publishers

• Scale will matter - the ability to invest in product development, talent retention is crucial. Publishers need to think big and focus their resources. Consider mergers, acquisitions and partnerships that can speed your time-to-market. 
• Move quickly to claim new audience segments. Markets are being created as we speak. Once established, dominant voices in niche areas are difficult to displace. Identify and prioritise audiences and themes, develop products and test at scale. 
• Time for experimentation is over: build a robust product roadmap. Prioritise investments ruthlessly, building the necessary data foundations and evidence-led methodology to guide the launch of new products. 
• Set up governance processes to generate ideas, invest, test, assess and be ready to pivot quickly if necessary. Define clear goals and success tests at fixed intervals. 
• Review your organisation and workflows to ensure that resources are being focused on the most critical processes and products.  

FT Strategies offers practical insights and methodologies to navigate AI disruption, helping clients to future-proof their publishing strategy by:

• Developing an AI resilience check to assess portfolios’ vulnerability to AI competition.
• Assessing options for revenue diversification, including brainstorming new AI products, content analysis and audience/addressable market quantification
• Prioritising product roadmaps through ROI and ensuring flexibility for long-term growth
  -  Supporting the implementation of governance processes to evaluate initiatives. 
  -  Reviewing organisation and processes to ensure opportunities from new technologies are being used and workflows are optimised for success. 

At FT Strategies, we understand the power of AI, technology & data for future-proofing your business. Our specialist team of consultants have years of experience launching new products, assessing opportunities and transforming organisations to enable innovation and growth. To find out more about our services, please get in touch with us today.