Every time you ask ChatGPT a question, there’s a chance it’s drawing on an article written by a journalist who won’t see a cent for that use. Generative AI models were trained on vast swaths of the open web, including copyrighted news, books, and essays. Publishers argue they deserve compensation; AI companies claim fair use. The result is a legal and economic standoff that will shape the future of digital content.
But money is already moving. OpenAI has signed licensing deals with major publishers like News Corp and Axel Springer. Google pays French publishers under neighboring rights. Perplexity shares ad revenue. These early arrangements offer a glimpse of what ‘giving back’ might look like—and who gets left out.
The Core Problem: Your Content Trained the Model
Generative AI models are built on web crawls like Common Crawl, which contains billions of pages. News articles, blog posts, and book excerpts form a significant chunk of that data. The models don’t store exact copies, but they learn patterns, facts, and styles from the text. This is where the trouble starts.
Publishers see this as unauthorized use of their property. AI companies call it transformative fair use. The U.S. Copyright Office hasn’t settled it, and the courts are only beginning to weigh in. The most closely watched case is The New York Times’ lawsuit against OpenAI and Microsoft, filed in December 2023. The Times alleges ‘massive copyright infringement’ and seeks billions in damages. OpenAI says the claim is ‘without merit.’ The outcome will likely set the rules for everyone else.
The Compensation Models Already in Play
While lawsuits drag on, some publishers have cut deals. These fall into three broad categories:
- Licensing agreements: OpenAI has signed multi-year deals with Axel Springer, the Associated Press, News Corp, and Le Monde. Google has similar arrangements with French publishers under the EU’s neighboring rights law. These are typically flat fees or annual payments for access to content.
- Revenue sharing: Perplexity, an AI search engine, launched a publisher program that shares a portion of ad revenue when its chatbot cites a source. It’s an experiment, but one that directly links compensation to usage.
- One-time payments: Some smaller outlets have accepted flat fees for content use, though the amounts are often undisclosed and rarely recurring.
Still, the vast majority of publishers and independent creators receive nothing. The deals are selective, favoring big names with legal teams and bargaining power.
Why the ‘Value Gap’ Matters
The real conflict isn’t just about unpaid training data. It’s about what happens after. AI tools like ChatGPT and Perplexity can answer a user’s question directly, without sending them to the publisher’s website. That means fewer page views, less ad revenue, and fewer subscriptions. Publishers call this the ‘value gap.’
AI companies counter that citations drive traffic and that the impact is overstated. Studies are mixed. Some show a decline in referral traffic from search engines; others suggest AI tools can boost brand visibility. The uncertainty hasn’t cooled the rhetoric.
Historical Precedents: Google Books and the Music Industry
This isn’t the first time technology outpaced copyright law. Google Books scanned millions of books and showed snippets. The Authors Guild sued, but courts ruled it was fair use. AI companies cite that case as precedent.
A closer parallel might be the music industry’s fight against Napster. After years of litigation, the industry shifted to licensed streaming—Spotify, Apple Music—which now generates billions in revenue. Some argue AI compensation will follow the same arc: disruption, litigation, then licensing. But the music industry had a central collection society (ASCAP, BMI) to manage royalties. Publishing has no such mechanism, making collective licensing harder.
Regulatory Pressure and the EU’s Example
The EU has moved further than the U.S. The 2019 Copyright Directive gave publishers ‘neighboring rights’—the right to be paid when their content is used online. The EU AI Act, passed in 2024, adds transparency requirements: AI companies must disclose what they train on. In practice, this has forced Google and others to negotiate with French publishers.
The U.S. has no federal AI copyright law. The Copyright Office has issued reports but stopped short of recommending sweeping changes. State-level bills are emerging, but a patchwork of laws could create more confusion. The UK has proposed a ‘text and data mining’ exception that allows training unless publishers opt out—a model publishers strongly oppose, because it puts the burden on them.
What Could ‘Giving Back’ Look Like?
Beyond the current deals, several models are on the table:
- Collective licensing: A central body (like a music rights society) that collects fees from AI companies and distributes them to publishers. The EU’s neighboring rights hint at this, but no equivalent exists in the U.S.
- Pro-rata revenue sharing: AI companies could set aside a percentage of revenue to be split among publishers based on how often their content is cited or used in training. This would require new metrics and transparency.
- Micro-payments and blockchain: Some startups propose per-use payments via blockchain, but adoption is low and the infrastructure is untested.
- Bundled deals with platforms: Rather than individual contracts, publishers could negotiate collectively through trade associations. The News Media Alliance has proposed a similar approach.
Each model has flaws. Collective licensing is slow to set up. Revenue sharing needs reliable tracking. Micro-payments may not scale. But the direction is clear: AI companies will have to pay for the content that powers them. The question is how much, and who gets to decide.
The standoff between AI companies and publishers won’t be resolved by a single lawsuit or regulation. The most likely future is a messy hybrid: court rulings that chip away at fair use, licensing deals that expand beyond the biggest players, and new technologies that track content usage in real time. For independent creators, the outlook is less certain—they lack the leverage of a News Corp. But the principles are the same: if AI profits from human creativity, some of that value should flow back to the creators. How to make that fair, efficient, and scalable is the defining challenge of the AI era.
Summary
- The problem: AI models are trained on copyrighted content without compensation, sparking lawsuits like The New York Times v. OpenAI.
- Existing models: Licensing deals (OpenAI with News Corp, Google with French publishers), revenue sharing (Perplexity), and one-time payments cover only a fraction of publishers.
- The value gap: AI tools reduce traffic to publisher sites, threatening ad revenue and subscriptions.
- Precedents: Google Books set a fair use precedent, but the music industry’s shift to licensed streaming suggests a similar path for publishing.
- Future options: Collective licensing, pro-rata revenue sharing, and micro-payments are emerging ideas, but none is fully realized yet.
FAQ
Q: Is AI training on copyrighted content legal?
A: It’s contested. AI companies argue fair use, while publishers say it’s infringement. The U.S. Copyright Office hasn’t ruled definitively, and the outcome of The New York Times v. OpenAI will be pivotal.
Q: What does a typical licensing deal look like?
A: Multi-year agreements with flat fees or annual payments for access to content. Examples include OpenAI’s deals with Axel Springer, the AP, and News Corp. Terms are usually confidential.
Q: How can independent creators get compensated?
A: Currently, they rarely do. Collective licensing or pro-rata revenue sharing could help, but no such system exists yet. Some startups are exploring micro-payments, but they’re not widespread.
Q: Will AI tools really hurt publisher traffic?
A: Evidence is mixed. Some studies show a decline in referral traffic, while others suggest AI can increase visibility. Publishers argue the impact is significant; AI companies say it’s overstated.
Q: What is the EU doing differently?
A: The EU’s 2019 Copyright Directive gives publishers neighboring rights, requiring compensation for online use. The EU AI Act adds transparency rules. This has led to licensing deals with Google in France.