From archives to assets: Exploring media monetisation in the age of AI
Our research included polling of senior media and entertainment executives, providing structured insights that complement our in-depth interviews. These findings highlight industry priorities, challenges, and strategic approaches to archive monetisation in the age of AI.
Strategic priorities and opportunities
Stephen Thomas from the Financial Times emphasises this evolution:
“We need to shift our focus beyond just managing current content and web pages to really understanding the value of our archives – and protecting it. For professional audiences seeking context around market events and price changes, historical content becomes incredibly valuable.”
Ayushman Saha reinforces this perspective:
“Monetisation is paramount – organisations need to carefully consider how to extract value from their archives, whether through articles, documentation, videos, documentaries or podcasts. With such extensive historical content available, we can tailor it to convey specific messaging and create new value streams.”
Meropi Kylika describes this multi-faceted approach:
“We need to shift our focus beyond just managing current content and web pages to really understanding the value of our archives – and protecting it. For professional audiences seeking context around market events and price changes, historical content becomes incredibly valuable.”
Technology priorities and implementation
McKinley Muir Hyden highlights concrete applications:
“We're already seeing practical applications through products like AskFT, which allows users to ask questions in natural language and receive answers drawn exclusively from FT content. We've also 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.”
Thomas explains a successful approach:
“Monetisation is paramount – organisations need to carefully consider how to extract value from their archives, whether through articles, documentation, videos, documentaries or podcasts. With such extensive historical content available, we can tailor it to convey specific messaging and create new value streams.”
Saha notes,
“If an organisation lacks a clear strategy for leveraging their archived information, the investment becomes questionable regardless of how impressive the technology might be.”
Implementation challenges and considerations
Kylika articulates one key challenge:
“There's significant apprehension about submitting intellectual property to AI systems – questions arise about ownership and control once content is processed through these systems. Media companies need to carefully evaluate how to integrate with AI while protecting their unique assets.”
Hyden emphasises this approach:
“Any new technology must fulfil a genuine commercial or customer need rather than being adopted for its own sake. Second, we need to consider both short-term returns and long-term implications for our business model. Finally, ethical considerations must be central to our decision-making.”
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.”
Key patterns and implications
Five notable patterns emerge from our executive survey:
AI centrality is unanimous (100%): Every executive identified artificial intelligence as the technology with the greatest potential impact on archive monetisation, signalling a clear industry consensus.
Revenue focus dominates (75%): Three-quarters of respondents cite new revenue opportunities as the primary driver for archive transformation, highlighting the shift from cost centre to profit centre mentality.
Implementation gaps persist (75%): Despite universal agreement on AI's importance, 75% of executives express uncertainty about their organisation's current implementation status, suggesting significant strategic alignment opportunities.
Multi-faceted challenges require comprehensive approaches (25% each): The equal distribution of challenges across content discovery, rights management, expertise, and legacy systems indicates the need for holistic transformation strategies.
Hybrid monetisation models prevail (50%): Half of respondents favour comprehensive approaches combining multiple monetisation models, reflecting recognition that no single approach will maximise archive value.
These findings provide structured validation for the insights shared by our industry leaders, demonstrating clear patterns in how media organisations are approaching content monetisation in the age of AI. The results indicate both strong strategic alignment on ultimate objectives and significant variation in implementation approaches and priorities.
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