The newsroom at CNET fell silent on a Tuesday morning in January 2023. Not from breaking news or deadline pressure, but from the realisation that artificial intelligence had been quietly publishing articles under bylines that didn't exist. The AI-generated content, riddled with errors and lacking the nuanced understanding that defines quality journalism, became a cautionary tale that rippled through an industry already grappling with existential questions about its future. Yet from this chaos emerged an unexpected revelation: in a world hungry for authentic, expertly curated information, news media wasn't becoming obsolete—it was becoming indispensable.
The Automation Experiment That Backfired
The early months of 2023 witnessed what industry insiders now call "the great AI experiment"—a period when media companies, seduced by the promise of cost reduction and infinite content generation, began replacing human journalists with artificial intelligence. The results were swift and sobering.
CNET's AI-written articles contained fundamental errors about financial advice, prompting the company to add corrections to dozens of pieces. G/O Media's attempt to automate content creation across its portfolio of sites led to a staff revolt and public embarrassment when AI-generated articles about sensitive topics lacked the context and empathy that human writers provide. Microsoft's experiment with AI-generated news summaries produced content so divorced from reality that it had to be quickly withdrawn.
These failures weren't merely technical glitches—they revealed something profound about the nature of journalism itself. The craft of reporting, the ability to synthesise complex information, to understand context and nuance, to ask the right questions and challenge assumptions, proved irreplaceable. As one industry veteran observed during the 2024 Trust Conference in London, "We don't want to create a situation where all the journalistic risk is on the content producers and all the profit is on Big Tech."
The backlash was swift and decisive. BuzzFeed, which had initially embraced AI for content creation, found itself scaling back automation efforts after quality concerns mounted. CNN's experiments with AI-generated summaries were quietly shelved. The industry began to recognise that whilst AI could assist journalists, it couldn't replace the fundamental human elements that make journalism valuable.
The Hidden Value of Editorial Curation
As the dust settled from these early experiments, a more nuanced understanding emerged. The real value of news media in the AI age wasn't just in the stories themselves, but in the editorial process that creates them. Every article published by a reputable news organisation represents layers of human judgement: source verification, fact-checking, contextualisation, and ethical consideration.
This editorial curation process creates something that AI companies desperately need: high-quality, reliable training data. Large language models are only as good as the information they're trained on, and the internet is awash with misinformation, bias, and low-quality content. Professional journalism, with its editorial standards and fact-checking processes, represents a gold mine of curated, reliable information.
The irony wasn't lost on industry observers. Tech companies that had initially seen news media as a cost centre to be automated were now recognising it as a premium supplier of the very content their AI systems needed to function effectively. The relationship dynamic began to shift from replacement to partnership.
Legal Battles and Power Dynamics
The transformation of this relationship played out dramatically in courtrooms and boardrooms throughout 2024. The New York Times' lawsuit against OpenAI marked a watershed moment, not just for its legal implications, but for what it revealed about the true value of journalistic content in the AI ecosystem.
The lawsuit highlighted how AI companies had been training their models on copyrighted news content without permission or compensation. This wasn't merely a legal technicality—it was a fundamental question about the value chain in the digital economy. If AI companies could freely use news content to train models that then competed with news organisations for audience attention, the entire economic foundation of journalism would crumble.
The legal battles forced a reckoning. News organisations began implementing technical measures to block AI crawlers from accessing their content. The robots.txt files that had once welcomed search engine indexing were rewritten to exclude AI training bots. Publishers started treating their archives not just as historical records, but as valuable datasets that required protection and strategic licensing.
This shift in approach reflected a broader understanding of leverage. News organisations realised they weren't just content creators—they were data suppliers in an economy increasingly dependent on high-quality information. The question became not whether to engage with AI companies, but how to do so on terms that recognised the true value of journalistic content.
The Emergence of Licensing Models
The recognition of news content as valuable training data led to the emergence of sophisticated licensing frameworks. The News/Media Alliance's partnership with ProRata AI represented one of the first systematic attempts to create fair compensation structures for publishers whose content was used in AI training.
These licensing agreements went beyond simple payment structures. They included provisions for attribution, ensuring that AI systems would credit original sources when drawing on journalistic content. They established quality standards, recognising that not all content was equally valuable for training purposes. Most importantly, they created ongoing revenue streams that could help sustain journalism in an era of declining traditional advertising revenue.
The New York Times' licensing deal with Amazon marked another significant milestone. Unlike the adversarial relationship that had characterised earlier interactions between news organisations and tech companies, this partnership was built on mutual recognition of value. Amazon gained access to high-quality, fact-checked content for its AI systems, whilst The Times secured both revenue and assurance that its content would be used responsibly.
These partnerships began to establish templates for the industry. Google, Microsoft, and Meta all began negotiating similar deals with major news organisations. The terms varied, but the underlying principle remained consistent: news content had value that deserved compensation, and AI companies were willing to pay for access to high-quality, reliable information.
The Rise of Dataset SEO
As licensing deals proliferated, a new form of optimisation emerged: dataset SEO. Just as publishers had once optimised content for Google's search algorithms, they began optimising for inclusion in AI training datasets. This wasn't simply about creating more content—it was about creating the right kind of content.
AI training datasets favoured certain characteristics: factual accuracy, clear attribution, structured information, and authoritative sourcing. News organisations that understood these preferences could position themselves as premium suppliers in the AI content marketplace. The concept of "dataset inclusion" became as important as traditional search engine visibility.
This shift had profound implications for editorial strategy. Publishers began considering not just how their content would perform in search results or social media, but how it would contribute to AI training datasets. Articles with clear sourcing, comprehensive fact-checking, and authoritative expertise became more valuable than ever.
The phenomenon extended beyond individual articles to entire publication strategies. News organisations with strong editorial standards and consistent quality found themselves in high demand from AI companies. The investment in journalistic rigour that had once seemed like a cost centre became a competitive advantage in the AI economy.
Editorial Transformation and Human-AI Collaboration
Rather than replacing journalists, AI began finding its place as a powerful tool in the editorial workflow. News organisations discovered that AI excelled at certain tasks: transcribing interviews, generating initial drafts for routine stories, analysing large datasets, and identifying patterns in complex information.
The Washington Post's use of AI for election coverage exemplified this collaborative approach. AI systems processed voting data and generated initial reports, but human journalists provided context, analysis, and the narrative structure that made the information meaningful to readers. The technology amplified human capabilities rather than replacing them.
This collaboration model proved particularly valuable for investigative journalism. AI could process vast amounts of documents, identify connections, and flag potential leads, but human journalists provided the critical thinking, source cultivation, and ethical judgement necessary for meaningful investigation. The combination proved more powerful than either humans or AI working alone.
The editorial transformation also extended to audience engagement. AI-powered personalisation helped news organisations deliver more relevant content to readers, whilst human editors ensured that important stories reached audiences even when they might not align with individual preferences. The balance between algorithmic efficiency and editorial judgement became a defining characteristic of successful news organisations.
The Credibility Premium
As AI-generated content proliferated across the internet, readers began developing a heightened appreciation for authentic, human-authored journalism. The credibility premium—the additional value that readers placed on content from trusted news sources—became more pronounced in an environment saturated with AI-generated material.
This credibility premium translated into tangible business value. Subscription rates for established news organisations remained stable or grew, even as AI-generated content became freely available. Readers were willing to pay for the assurance that content had been created, fact-checked, and curated by human professionals.
The premium extended to advertising markets as well. Brands became increasingly concerned about their advertisements appearing alongside AI-generated content of uncertain quality. The brand safety that came with established news organisations became a valuable commodity in the digital advertising ecosystem.
Challenges for Smaller Publishers
Whilst major news organisations found themselves in strong negotiating positions with AI companies, smaller publishers faced different challenges. The licensing deals that provided revenue streams for large organisations were often inaccessible to smaller outlets that lacked the negotiating power or content volume to attract AI company interest.
This disparity threatened to exacerbate existing inequalities in the media landscape. Local news organisations, already struggling with declining revenues, found themselves excluded from the new AI economy despite producing content that was often more relevant to their communities than national publications.
Industry organisations began developing collective licensing frameworks to address this challenge. The News/Media Alliance's approach with ProRata AI included provisions for smaller publishers, recognising that diversity in news sources was valuable for AI training and essential for democratic discourse.
The Global Perspective
The transformation of news media's relationship with AI wasn't limited to English-language publications or Western markets. International news organisations faced similar challenges and opportunities, but with additional complexities related to different legal frameworks, cultural contexts, and economic conditions.
European publishers, operating under GDPR and other privacy regulations, found themselves with additional leverage in negotiations with AI companies. The regulatory environment that had once seemed burdensome became a source of strength in establishing fair terms for content licensing.
Emerging market publishers discovered that their unique perspectives and local knowledge were particularly valuable for AI companies seeking to develop globally relevant systems. Content that provided insights into different cultures, languages, and contexts commanded premium prices in licensing negotiations.
Technical Infrastructure and Future Capabilities
The partnership between news organisations and AI companies drove innovation in content management and distribution systems. Publishers invested in technical infrastructure that could support both traditional publishing workflows and AI integration requirements.
These technical improvements had benefits beyond AI partnerships. Enhanced content management systems improved editorial efficiency, better metadata structures increased discoverability, and improved analytics provided deeper insights into audience behaviour. The investment in AI-compatible infrastructure strengthened news organisations' overall digital capabilities.
The technical evolution also enabled new forms of journalism. AI-assisted data analysis allowed reporters to identify stories in complex datasets that would have been impossible to discover manually. Automated transcription and translation services expanded the reach and accessibility of journalistic content.
Economic Sustainability and Revenue Diversification
The licensing revenue from AI partnerships provided news organisations with a new stream of income that was less dependent on traditional advertising or subscription models. This diversification proved particularly valuable as digital advertising markets became increasingly competitive and subscription growth plateaued for many publications.
The revenue from AI licensing wasn't just supplementary—for some organisations, it became a significant portion of their income. This financial stability allowed news organisations to invest in editorial quality, hire additional staff, and pursue ambitious journalistic projects that might not have been financially viable under traditional revenue models.
The economic impact extended beyond direct licensing fees. News organisations that established strong relationships with AI companies found themselves with preferential access to new technologies, early adoption opportunities, and collaborative development projects that provided additional value.
Ethical Considerations and Editorial Independence
The financial relationships between news organisations and AI companies raised important questions about editorial independence. Publishers had to navigate the tension between securing valuable licensing revenue and maintaining the editorial freedom necessary for credible journalism.
Industry leaders developed ethical frameworks to address these concerns. Editorial policies were established to ensure that licensing relationships didn't influence news coverage of AI companies or technology issues. Transparency requirements were implemented to disclose financial relationships that might create conflicts of interest.
The ethical considerations extended to the use of AI in editorial processes. News organisations developed guidelines for when and how AI could be used in content creation, ensuring that readers were informed about the role of artificial intelligence in producing the journalism they consumed.
The Competitive Landscape
The AI revolution reshaped competitive dynamics within the news industry. Organisations that successfully navigated partnerships with AI companies gained advantages in both revenue and technological capability. Those that resisted or failed to adapt found themselves increasingly disadvantaged.
The competitive pressure drove innovation and collaboration within the industry. News organisations began sharing best practices for AI integration, developing common standards for content licensing, and collaborating on technical infrastructure that benefited the entire ecosystem.
The competition also extended to talent acquisition. Journalists with technical skills and understanding of AI systems became highly sought after, as news organisations recognised the importance of having staff who could effectively collaborate with artificial intelligence tools.
Looking Forward: The Next Phase
As the relationship between news media and AI matured, new opportunities and challenges emerged. The initial focus on licensing existing content began expanding to collaborative content creation, where AI companies and news organisations worked together to develop new forms of journalism.
Experimental projects explored AI-assisted investigative reporting, automated fact-checking systems, and personalised news delivery that maintained editorial integrity whilst providing relevant content to individual readers. These collaborations pointed toward a future where the boundary between human and artificial intelligence in journalism became increasingly fluid.
The success of early partnerships encouraged more ambitious collaborations. News organisations began participating in the development of AI systems specifically designed for journalistic applications, ensuring that the technology evolved in ways that supported rather than undermined quality journalism.
The Transformation Complete
The journey from existential threat to strategic partnership represented one of the most dramatic transformations in media history. News organisations that had initially feared replacement by artificial intelligence discovered that their expertise, credibility, and editorial standards made them indispensable partners in the AI ecosystem.
The transformation wasn't without casualties. Publishers that failed to adapt, that couldn't maintain quality standards, or that lacked the strategic vision to navigate the new landscape found themselves marginalised. But for those that successfully made the transition, the AI revolution provided new sources of revenue, enhanced capabilities, and renewed relevance in the digital economy.
The relationship between news media and artificial intelligence continues to evolve, but the fundamental principle has been established: quality journalism isn't threatened by AI—it's empowered by it. The future belongs to news organisations that can harness artificial intelligence whilst maintaining the human elements that make journalism valuable.
In this new landscape, the most successful news organisations are those that understand their role not just as content creators, but as curators of truth in an age of information abundance. They provide the editorial judgement, fact-checking, and contextualisation that artificial intelligence cannot replicate, whilst leveraging AI tools to enhance their capabilities and reach.
The great reckoning has revealed that in a world increasingly shaped by artificial intelligence, the need for authentic, credible, human-centred journalism has never been greater. News media hasn't just survived the AI revolution—it has discovered its true value in the digital age.
References and Further Information
Reuters Institute for the Study of Journalism, "How AI is Reshaping Copyright Law and What it Means for the News Industry"
News/Media Alliance, "ProRata Licensing Partnership Framework"
The New York Times, "Amazon AI Licensing Agreement Coverage"
Digital Content Next, "The Future of Journalism: Defining Copyright in the Age of AI"
Best AI Blog, "The New York Times and Amazon Strike Landmark AI Licensing Deal"
Various industry reports from NPR, AdWeek, The Verge, CNBC, Futurism, Axios, and Vox
2024 Trust Conference proceedings and speaker testimonies
Congressional committee hearings on AI and copyright in journalism
Industry analysis from media trade publications and analyst reports
Publishing History
- URL: https://rawveg.substack.com/p/the-great-reckoning
- Date: 21st June 2025
About the Author
Tim Green
UK-based Systems Theorist & Independent Technology Writer
Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.
His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.
ORCID: 0000-0002-0156-9795
Email: tim@smarterarticles.co.uk
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