📊 Full opportunity report: Raw-feed licensing. The contract that doesn’t exist yet. on ThorstenMeyerAI.com — validation score, market gap, and execution plan.

There is currently no industry-standard contract for raw-feed licensing in artificial intelligence, despite the existence of licensing frameworks for training data and display rights. This gap is creating economic and legal uncertainty in the AI industry, with stakeholders actively avoiding formal agreements to maintain leverage.

In 2026, the AI industry has established licensing for training data and display rights, but the third category—raw-feed licensing for downstream per-audience rewriting—remains without a formal contractual framework. This missing contract is critical because the economics of AI inference, which can cost as little as $0.003 per rewrite, collide with the traditional music-streaming royalties that are set by statutory law at about 15% of platform revenue. Despite the clear economic parallels, no standardized contract exists because each of the four main parties—AI labs, publishers, wire cooperatives, and search engines—prefer to avoid formal agreements that would set clear prices and rights.

Sources indicate that the absence of a contract stems from structural resistance: stakeholders benefit from the current mis-pricing, which favors certain parties and discourages regulation. The legal framework that supports music licensing—rooted in laws dating back to 1909—serves as a precedent, but the industry has yet to adapt this to the AI context. The missing contract would need to specify key elements such as pricing units, attribution, derivative-work scope, rights to ingest data, audit and reporting obligations, and modification rights. Its absence hampers transparency and fair remuneration, especially for downstream rewriting tasks.

Implications of the Missing Raw-Feed Contract in AI Licensing

The lack of a formal contract for raw-feed licensing in AI creates economic and legal uncertainty, risking a future regulatory crackdown and uneven market development. Without clear rules, stakeholders may continue to benefit from mis-pricing, but this could lead to disputes, reduced transparency, and potential legal challenges. Establishing a standardized framework is crucial for sustainable growth, fair compensation, and legal compliance in the evolving AI ecosystem.

Historical and Industry Context of Licensing Gaps

The AI licensing landscape currently includes well-established frameworks for training data and display rights, with major deals such as OpenAI’s 2023 archive license and News Corp’s 2024 display licensing agreement. However, the third category—raw-feed licensing for downstream rewriting—remains unregulated and without standard contracts. This situation echoes the early 1900s in music licensing, after landmark cases like White-Smith v. Apollo, when legal frameworks were still developing. The current gap reflects a structural resistance by industry players to formalize agreements that could limit their leverage or introduce regulatory oversight. As AI inference costs fall below traditional licensing costs, the economic collision is becoming more acute, highlighting the urgent need for a contractual solution.

“The missing contract category for raw-feed licensing is a structural moment similar to early 20th-century music licensing, where legal scaffolding was still in development.”

— Thorsten Meyer

Unresolved Questions About Future AI Licensing Frameworks

It is not yet clear when or if a standardized raw-feed licensing contract will be established, as negotiations among AI labs, publishers, wire cooperatives, and search engines continue. Stakeholders’ differing interests and strategic incentives suggest that the resolution may be delayed or take a non-standard form. The potential regulatory response and legal precedents that could influence this process remain uncertain.

Next Steps Toward Formalizing Raw-Feed Licensing Agreements

Industry stakeholders are likely to face increasing pressure from regulators and policymakers to develop a formal licensing framework. Future negotiations may focus on defining key contractual elements, possibly inspired by existing music licensing models. Legislative or regulatory interventions could accelerate the process, especially if disputes or legal challenges arise from the current lack of standardization. Monitoring these developments will be critical for understanding how the industry adapts to the economic and legal challenges of AI inference.

Key Questions

Why does the raw-feed licensing contract matter now?

The absence of a standardized contract creates economic and legal uncertainty, which could hinder sustainable growth and invite regulatory intervention in AI licensing practices.

What are the main obstacles to creating this contract?

Stakeholders benefit from the current mis-pricing and lack of regulation, and they are reluctant to agree on terms that could limit their leverage or impose new legal obligations.

How does this situation compare to historical music licensing?

Similar to the early 20th century, when legal frameworks for music licensing were still evolving, the AI industry faces a moment where formal contracts are needed but have not yet been established.

Who are the key parties involved in this licensing gap?

AI labs, content publishers, wire cooperatives, and search engines are the main stakeholders, each with differing incentives to formalize or avoid formal licensing agreements.

What could accelerate the creation of a standard contract?

Regulatory pressure, legal challenges, or significant market disputes could prompt stakeholders to negotiate and establish a formal framework for raw-feed licensing.

Source: ThorstenMeyerAI.com