Insights: Strategic priorities in media archive monetisation
Chapter 6.
Creating value through AI-enhanced content formats
Beyond improving archive management and discovery, AI enables the creation of entirely new content formats and experiences that can drive additional revenue streams. These innovations allow media organisations to extract more value from existing content while meeting evolving audience needs.
McKinley Muir Hyden describes concrete applications at the Financial Times: "We've developed an internal custom AI tool that ensures all content adheres to our style guides, enabling us to create features like bullet-point summaries for busy executives who need quick access to key information. We're also exploring the creation of 'taxi packs' for busy professionals who need quick access to critical information between meetings."
These applications address specific audience needs while maintaining quality standards. Hyden explains, "These applications are particularly valuable because they provide our clients with confidence that they're accessing trusted information from a reliable source while maintaining our distinctive voice."
Meropi Kylika highlights how AI allows for more personalised content delivery: "Depending on viewer preferences and characteristics, AI can dynamically adjust product placements within scenes. This level of personalisation extends to various aspects of content delivery – from tailoring article summaries for time-poor executives to customising promotional imagery based on user demographics and interests."
Stephen Thomas describes how structured knowledge enables new applications: "When we transform our articles from simple collections of words into structured knowledge components – factoids and relationships – AI models can work with them more effectively. This enables faster, more accurate analysis while maintaining information integrity."
Ayushman Saha emphasises the diverse possibilities for content repackaging: "With such extensive historical content available, we can tailor it to convey specific messaging and create new value streams. The flexibility of digital archives means organisations can shape and mine this content in ways that align with their specific strategic objectives, whether that's creating educational content, developing documentary series, or offering specialised research services."
For news organisations, AI allows more effective resource allocation. Kylika notes: "Consider financial news – there are regular scheduled announcements from institutions like the Bank of England that every outlet covers. These events aren't rare or exclusive, so there could be a scenario where AI manages the baseline coverage, while our journalists focus on sense-making and delivering deeper analysis."
The technical foundation for these innovations lies in sophisticated metadata and cataloguing. Thomas explains, "The key to unlocking archive potential lies in implementing intelligent systems with robust metadata capabilities, enabling swift and accurate search functionality. Having this AI adoption lens is critical for future success."
The key to success lies in media organisations' ability to:
- Identify specific user needs that can be addressed through AI-enhanced formats
- Maintain brand voice and quality standards in automated content
- Apply personalisation capabilities to improve audience engagement
- Create structured knowledge rather than simple text archives
- Develop formats that complement rather than replace human journalism
These innovations represent a fundamental shift in how media organisations conceive of their content assets. As Saha summarises: "Content monetisation strategies are fundamentally about creating new value from existing resources. Historical content provides invaluable context and understanding of how things evolved at different points in time, which is why we consistently return to reference materials and historical records. The key is finding innovative ways to present this information to modern audiences."
Key Insights Recap
AI enables micro-personalised content engineering—from machine-curated knowledge objects to multi-channel narrative assets for scalable distribution—from voice-activated executive briefings to adaptive visual content formats for AR/VR environments—opening monetisation avenues in sectors like digital education and corporate training and experiences, from executive summaries to personalised delivery. These innovations allow media organisations to extract more value from existing content while meeting evolving audience needs.
Quick Action Guide
Key Insights Recap
AI enables micro-personalised content engineering—from machine-curated knowledge objects to multi-channel narrative assets for scalable distribution—from voice-activated executive briefings to adaptive visual content formats for AR/VR environments—opening monetisation avenues in sectors like digital education and corporate training and experiences, from executive summaries to personalised delivery. These innovations allow media organisations to extract more value from existing content while meeting evolving audience needs.
Quick Action Guide
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