Mr Jonathan Jones

Mr Jonathan Jones

SEO & Digital Consultant

Shaping the AI Content Frontier: Deals, Data, and Value Exchange

I’ve been deeply immersed in the insights shared at the Dealbook Summit this weekend, listening with great earnest to some of the most influential CEOs and thought leaders shaping the future of AI. The discussions were nothing short of illuminating, particularly around the pressing issue of how AI should engage with and compensate the creators whose work underpins its capabilities.

This article aims to dissect the perspectives of those at the helm of the world’s leading AI companies—their thoughts on the evolving relationship between artificial intelligence and human creativity, and their vision for establishing fair compensation models. As the debate around intellectual property and AI intensifies, these insights provide a fascinating glimpse into how the industry might redefine the value exchange between creators and technology.

A New Era of Licensing and Data Partnerships

At the 2024 New York Times DealBook Summit, during a conversation moderated by Andrew Ross Sorkin, Google’s Chief Executive Officer Sundar Pichai responded to questions about the company’s evolving approach to content licensing. Rather than defaulting to passive web scraping and relying solely on “fair use,” Google has begun pursuing more deliberate arrangements with platforms like Reddit and publishers including The New York Times.

While Pichai’s comments did not suggest an intention to lavish agreements on all corners of the internet, his remarks indicated a recognition that content providers’ work is integral to refining the AI models powering Google’s services—and that this contribution may warrant formal compensation.

Related: Facing Google Search Disruption: Artificial Intelligence Optimization (AIO) — Embrace or Resist?

Similarly, Sam Altman, during his interview with Andrew Ross Sorkin at the same Dealbook Summit, was asked a similar question (I’ve even time-stamped the exact segment—you’re welcome).

The question from Sorkin:

“It just so happens that The New York Times Company has a lawsuit against OpenAI and Microsoft over training on content. There are many content creators in this room who make their living off of books, articles, movies, and other work that has been used for AI training—whether on the open web, the closed web, or YouTube. For those creators, how should they feel about this?”

Sam Altman’s response:

“I think we do need a new standard protocol, whatever you want to call it, for how creators are going to get rewarded. I very much believe in the right to learn—whatever you want to call it—and if an AI reads a physics textbook and learns physics, it can use that for other things just like a human can. I think those parts of copyright law, fair use, really need to keep applying. But I think there are additional things that we’re starting to explore and others are as well, where, you know, a particular passion of mine has always been: can we figure out how to do micropayments? Where, if you generate a story in the style of Andrew Worken, you can opt into that for your name and likeness and style to be used and get paid for it. There are many other ideas, too.

Altman pointed to the idea of micropayments—a system where creators could opt in to have their likeness or style used and receive compensation for it. While defending fair use principles, he also suggested that the current debate on copyright might be “at the wrong level” and hinted at more innovative solutions on the horizon.

I think the discussion on fair use or not is at the wrong level. Of course, we very much believe that you need one of these right-to-learn approaches, but the part I really agree with is we need to find new economic models where creators can have new revenue streams. On The New York Times—look, I don’t believe in showing up in someone else’s house as a guest and being rude, but I will say, I think The New York Times is on the wrong side of history in many ways. We can discuss and debate that—and we’ll do that, I think, in court. Um, look forward to seeing you.”

While Altman highlights the ‘right to learn’ argument, his acknowledgment of micropayments hints at a more practical path forward—one where AI companies take proactive steps to compensate creators fairly. Licensing agreements, already emerging between major publishers and AI firms (being led by OpenAI), demonstrate that models for equitable value exchange are not just theoretical—they’re achievable. If AI companies see content as critical infrastructure, much like cloud servers or GPUs, then paying for quality datasets should become standard practice.

Creators Designing Content for AI Systems

What’s truly novel is Pichai’s suggestion that entirely new classes of creators may emerge—individuals who craft text, music, images, and more, not for direct human consumption, but specifically to improve AI systems.

“I think there’ll be creators who will create for AI models … and get paid for it,”

Sundar Pichai, Chief Executive Officer, Alphabet

Succinctly capturing the idea of an emerging class of “AI-first” creators. These individuals could produce bespoke content tailored to help large language models recognise subtleties in language, or assist image-generation algorithms in mastering intricate artistic styles. Their labour wouldn’t go unrewarded: by establishing licensing fees and revenue-sharing frameworks, these creators would directly benefit from the quality their efforts bring to AI systems.

As OpenAI’s and Perplexity’s deals suggest, this concept is already in motion. Publishers providing data in exchange for compensation could inspire niche creators to develop training-specific material—from sector-specific glossaries for specialised AI models to carefully curated image sets for emerging generative systems.

Regulatory Uncertainty and the Future of Compensation

While Andrew Ross Sorkin pressed Pichai on the issue of regulation—often late, often vague—Pichai acknowledged that clear legal guidance may lag behind innovation. Yet, this delay need not prevent the industry from experimenting with fairer economic models.

Pichai expressed confidence in the eventual resolution of legal uncertainties, stating:

“I have deep faith in our judicial system.”

Sundar Pichai, Chief Executive Officer, Alphabet

This suggests that Google is prepared to let lawmakers guide the process towards regulatory clarity, potentially including mandates for compensating content creators whose work trains AI models.

Yet the industry need not stand still as it waits for new laws. Companies can move forward with voluntary licensing deals involving publishers, independent creators, and emerging AI platforms.

The EU Copyright Directive and Google’s existing content agreements demonstrate that it’s possible to establish practical frameworks without waiting for entirely new, AI-specific regulations.

Such initiatives may set the stage for future legal standards, potentially beginning at the European level and then influencing other regions. Observers, including participants in recent industry-focused podcasts, have noted that the European Union—often viewed as a global leader in technology regulation—is likely to act first, with the United States and others following in due course.

Even as lawmakers deliberate, technology companies can pursue voluntary deals with publishers, content creators, and emerging AI studios. The EU Copyright Directive and Google’s subsequent content licensing demonstrate that practical frameworks can be established without waiting on new, AI-specific mandates. It’s plausible that such arrangements will lay the groundwork for new legal standards, starting with proactive moves by the European Commission and gradually extending to other jurisdictions.

Over time, this could yield a stable, transparent marketplace where creators know their work will be valued in proportion to its usefulness, and tech firms can secure high-quality input data without accusations of exploitation or free-riding.

Recent industry developments underscore this shift. OpenAI has reportedly secured deals totalling $250 million over five years with major publishers including DotDash Meredith, News Corp, and Future PLC—collectively representing over 500 sites.

Similarly, emerging AI platforms like Perplexity are now entering revenue-sharing agreements with publishers such as TIME, Der Spiegel, Fortune, Entrepreneur, The Texas Tribune, and WordPress.com. These arrangements set a precedent for how high-quality publisher content might be integrated and monetised within AI-driven ecosystems.

There is also a growing legislative backdrop in Europe. By June 2023, Google had inked copyright licensing agreements with over 1,000 publications across the continent to comply with the EU Copyright Directive. This demonstrates a working model for compensating publishers for their content—a potentially instructive framework for future AI-related content deals. The question now is how these established precedents in the traditional news sphere will translate to AI training data scenarios, especially as technologies like Retrieval-Augmented Generation (RAG) gain traction. By blending licensed content directly into real-time AI outputs, RAG offers both an opportunity for deeper integration of high-quality data and a challenge in ensuring ongoing, fair compensation for content creators.

Charting a Path Forward

In short, the trajectory outlined by Sundar Pichai points to a future in which content creators and AI developers engage in a more balanced exchange. Rather than viewing data as a freely available resource, the industry may soon treat it as a critical commodity deserving of compensation.

As Pichai put it, “I think there’ll be creators who will create for A.I. models, or something like that, and get paid for it. I definitely think that’s part of the future.”

This perspective aligns with the sentiment expressed by Ilya Sutskever, co-founder and former chief scientist at OpenAI, who emphasised the singularity of the internet as the source of AI’s growth:

“We have but one internet… That data is the fossil fuel of AI. It was created somehow. And now we use it.”

Ilya Sutskever, former chief scientist at OpenAI,

Sutskever’s analogy likens data to fossil fuels, acknowledging its finite origins and the intricate human effort behind its creation.

As the AI revolution continues, the hope is that creators who produce high-quality training materials will find not just a seat at the table, but a meaningful share in the economic value their contributions help generate.

The evolving landscape—highlighted by OpenAI’s multimillion-dollar deals with publishers, Perplexity’s revenue-sharing program, and Google’s compliance with EU copyright directives, including its $60 million agreement with Reddit—demonstrates a rapidly maturing marketplace. If these initiatives prove successful, they could become blueprints for the broader industry, fostering a robust and equitable ecosystem for AI-ready content where fair remuneration is a central pillar.


Top Talks You Can’t Miss: AI, Innovation, and What’s Next

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