Amazon Wants to Be the Clearing House for AI Training Data. Media Should Be Careful What They Wish For
If Amazon turns journalism and entertainment into an AWS-style marketplace for AI training data, the question isn’t whether money will flow – it’s who will end up setting the price of reality. A prospective "content marketplace" for AI could finally put copyright on-chain, so to speak, after years of chaotic scraping. But it could just as easily consolidate power in the hands of a few platforms and a few mega-publishers. In this piece, we’ll unpack what Amazon is reportedly planning, why it matters for the AI and media industries, and what European players should do next.
The News in Brief
According to TechCrunch, Amazon is exploring the launch of a marketplace where media companies can license their content to AI developers. The idea, first reported by The Information, has been presented in meetings with publishing executives and in materials circulated around an AWS event for publishers.
Amazon did not confirm specific product details but told TechCrunch it has long-standing relationships with publishers across businesses like AWS, retail, advertising and Alexa, and that it is constantly working with them on new initiatives.
The move would mirror Microsoft’s recently announced Publisher Content Marketplace, which aims to give AI systems large-scale access to “premium content” while offering publishers a fresh revenue stream and a more transparent licensing framework. It also builds on a wave of one-to-one licensing deals between AI labs and media groups, such as OpenAI’s agreements with the Associated Press, Vox Media, News Corp and The Atlantic, amid ongoing copyright lawsuits and regulatory pressure around AI training data.
Why This Matters
What Amazon is circling is not just another B2B product; it’s an attempt to formalise a market that, until now, has largely run on scraping first and apologising (or settling) later.
Winners – at least initially
- Amazon stands to become the toll booth on the road between content owners and AI developers. For AWS, which already sells compute and model services, adding licensable data completes a vertically integrated, "lawful AI" stack.
- Large publishers could get a scalable licensing channel instead of having to negotiate piecemeal deals with every AI lab. If structured well, that’s recurring, contract-based revenue in an industry starved of predictability.
- Big AI players gain a cleaner legal story. Being able to say “we trained on licensed datasets from Amazon/Microsoft marketplaces” is powerful when facing regulators, courts and enterprise customers.
Probable losers
- Smaller AI startups and open‑source projects may find themselves priced out of top-tier content, entrenching today’s giants. The barrier to entry shifts from clever engineering to access to expensive, brokered data.
- Mid and small publishers risk being commoditised. A marketplace will not magically equalise bargaining power; it will likely enshrine it. The New York Times and News Corp will command one rate, a local investigative newsroom quite another.
- The open web could be further hollowed out. If enough value moves into closed licensing pipes, incentives to publish freely accessible, linkable content decline.
The deeper issue is that such marketplaces don’t just price content; they implicitly price influence over how AI systems understand the world. Whoever controls this layer will have outsized sway over whose voices are amplified in the next generation of interfaces.
The Bigger Picture
Amazon’s reported plans sit at the intersection of three converging trends.
From scraping to contracts
For a decade, AI models were trained on whatever could be scraped under a generous interpretation of fair use and “publicly available information.” That era is ending. High-profile lawsuits, like those filed by authors and news organisations in the US and elsewhere, are making investors and enterprise customers nervous. Marketplaces are an attempt to industrialise permissioned data access.Platforms becoming data brokers 2.0
We’ve been here before. In the early web, traffic brokers intermediated eyeballs; in music, post-Napster platforms brokered licenses between labels and listeners. AI training data is going down the same path. Microsoft’s Publisher Content Marketplace was the first large-scale signal. Amazon entering the same space suggests that “data exchanges” could become a standard part of the AI infrastructure stack.Regulatory pre-emption
By building structured licensing channels, tech giants can walk into courtrooms and regulatory hearings with a story: "We’re not pirates; we operate marketplaces where rightsholders are paid." That doesn’t eliminate liability for past scraping, but it helps shape how future rules are written – towards schemes that assume a small number of big intermediaries rather than decentralised solutions.
Compared with OpenAI’s bespoke publisher deals, a marketplace approach is more scalable but also more transactional. Instead of strategic partnerships that might include product integration, co-branding or traffic guarantees, you get something closer to a commodities exchange: tokens in, training data out.
In that sense, Amazon isn’t solving the crisis of media sustainability so much as creating a new, programmatic revenue line item within the same precarious system.
The European / Regional Angle
For European publishers and regulators, this development cuts both ways.
On one hand, a structured marketplace could finally operationalise elements of EU law that have so far been weakly enforced. The EU Copyright Directive introduced a specific press publishers’ right; the forthcoming EU AI Act leans heavily on transparency about training data. A licensing marketplace provides an actual mechanism to link rights ownership with usage, at scale.
On the other hand, history offers a warning. Europe has already lived through a decade of battles over how platforms use news content – from Germany’s and Spain’s fights with Google News over snippets to complex negotiations with Facebook over news tab payments. In most of those cases, the bargaining imbalance between US platforms and fragmented European media groups was glaring.
A global marketplace run by Amazon will not magically fix that imbalance. Major groups such as Axel Springer, Schibsted or large UK-based publishers might negotiate decent terms. A regional daily in Slovenia or Croatia, or a niche investigative outlet in Eastern Europe, may find itself asked to accept boilerplate contracts on a take‑it‑or‑leave‑it basis.
There is also a linguistic dimension: European languages beyond English are underrepresented in AI training data. That gives them strategic value, but only if local publishers coordinate and avoid dumping their rights cheaply. Otherwise, European cultural and linguistic diversity becomes a discounted input into US-led AI products.
For regulators in Brussels, Berlin, Paris or Madrid, the key challenge will be ensuring that any such marketplace complies with competition law and data-protection rules – and that it does not become yet another chokepoint controlled by a handful of global giants.
Looking Ahead
If Amazon goes ahead, expect several follow‑on developments:
Pricing models will define who can play. Will licensing be per document, per token, per model, or a mix? Will there be different tiers for training vs inference vs synthetic data generation? A high fixed cost plus minimum volumes would effectively lock out startups and open‑source projects.
Exclusivity and windowing will appear. Some publishers will try to sell “premium” or even exclusive access to their archives. That could create information asymmetries between AI models – imagine one assistant that “knows” certain newspapers and another that doesn’t.
Collective bargaining will matter. European and national publisher associations may try to negotiate framework deals rather than leaving members to go one‑by‑one. That’s especially important for smaller markets and niche languages.
Regulatory test cases are almost guaranteed. Competition authorities will be interested if two or three platforms end up controlling most licensable training data. Data protection authorities will ask awkward questions if personal data is swept into these datasets under opaque terms.
Timeline-wise, these marketplaces are unlikely to remain hypothetical for long. Microsoft is already rolling out its version. If Amazon is socialising the idea with publishers, it is probably not far from at least a private beta; AWS customers will demand it as they ramp up their own model training.
For media executives, the homework starts now: audit your archives, clarify where you actually hold rights, model different revenue scenarios, and – crucially – model the cannibalisation risk if AI products trained on your content reduce your direct audience and advertising.
The Bottom Line
An Amazon-run content marketplace for AI training could be both a lifeline and a Trojan horse for media. It promises much‑needed licensing revenue and clearer legal footing, but it also centralises yet another layer of the digital economy in the hands of a few US tech platforms. European publishers and regulators should treat this not as a windfall, but as a high‑stakes negotiation over who gets to encode our societies into machines – and at what price. The real question is whether the media will act collectively and strategically this time, or repeat the platform deals of the last decade.
