Local & Specialist Publishing

Yahoo becomes first licensee of collective AI content scheme

Friday, 13 November 2026 5:00AM UTC

The deal gives Yahoo’s Scout search product access to participating publishers’ content under a shared licensing model that links payments to how AI services use their work.

Yahoo has become the first company to take a licence from the Internet Licensing Collective, a publisher-led non-profit that aims to replace separate negotiations with a shared framework for AI content use. The agreement gives Yahoo’s AI-powered search product, Scout, access to participating publishers’ material, with payments intended to reflect the contribution that content makes to its services. Digiday reported that more than 3,000 publishers are part of the collective; ILC’s website puts participation at more than 3,100 media brands, content owners and publishing platforms. (Sources? prohibited parentheses. attribution naturally.)

A licensee pays for access to the collective’s content, with the sum available for publishers tied to the licensee’s revenue. ILC co-founder Doug Leeds told Digiday that this means the compensation pool could expand as a business grows, while also allowing new AI products and companies to join. He declined to disclose the terms of Yahoo’s agreement. The collective says its approach is designed to make licensing workable at scale, reducing the need for AI companies and publishers to negotiate one deal at a time.

The model also separates payments by licensee. Rather than pooling all income and dividing it among every participant, ILC creates a distinct royalty fund for each AI company. That is intended to ensure publishers are paid from the fund associated with products that use their work, and to protect specialist outlets from having their earnings diluted by material used across broad, general-purpose services. ILC says the value of a work, including how it helps shape or ground an AI response, matters more than the size of a publisher’s catalogue.

Within each fund, allocation rules are expected to account for how a publisher’s material is used: whether it is retrieved or used to support an answer, how often the AI relies on it, and whether it is displayed or credited. The precise formula has not been made public. Leeds told Digiday that a specialist health product could generate greater value from a limited body of medical material than a general search service would derive from a much larger volume of content. The framework is intended to reward that difference rather than treat every use as equivalent.

Publishers are also meant to retain control over where their work is licensed. ILC says participants can choose which agreements to approve and can continue to make direct deals outside the collective. Digiday reported that publishers will be able to select licensees through an online portal as more companies join, and to see how their content is being used, including for retrieval-augmented generation or AI training. ILC’s launch announcement describes participation as non-exclusive, allowing publishers to retain existing arrangements.

The collective builds on Really Simple Licensing, or RSL, a separate technical standard for stating rights and conditions in a machine-readable format. The RSL guide describes terms that can cover uses such as AI training and web search, including pay-per-crawl and pay-per-inference arrangements. ILC’s website presents the collective as a licensing organisation, while RSL provides a way for publishers to communicate usage terms to software and crawlers. The organisation’s name change is intended to distinguish the collective licensing operation from the standard itself.

The potential scale of the market remains uncertain. Mather Economics estimates that publisher payments under collective AI licensing could amount to 15 to 35 per cent of AI-company revenue, and says the market could exceed the size of the US display advertising market within three years. Its initial analysis draws on annual revenue run rates from OpenAI and Anthropic, rather than the entire AI sector, and is based on economic modelling and assumptions about the growth of AI demand. The estimate is therefore a forecast, not a guarantee of future payments.

The broader case for collective licensing is that AI systems can use or summarise publisher material without necessarily sending readers to the original sites, weakening the value of referral traffic. In an article for INMA, Mather Economics’ authors describe collective arrangements as one possible way to reduce the cost and complexity of negotiating across many publishers and AI buyers. Leeds told Digiday that individual agreements may bring revenue to particular publishers, but argued that a shared system could help sustain the wider content infrastructure. ILC says it is in discussions with other potential licensees, but has not named them.

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Source: Noah Wire Services

More on this

https://digiday.com/media/yahoo-becomes-first-licensee-of-spotify-like-collective-ai-content-licensing-model/?utm_campaign=digidaydis&utm_medium=rss&utm_source=general-rss - Please view link - unable to able to access data
https://digiday.com/media/yahoo-becomes-first-licensee-of-spotify-like-collective-ai-content-licensing-model/ - Digiday reports that Yahoo is the first licensee of the Internet Licensing Collective (ILC), formerly associated with Really Simple Licensing (RSL). The agreement lets publishers make their content available to Yahoo’s AI-powered Scout search product and receive compensation based on how their material contributes to AI services. ILC’s model replaces isolated publisher-by-publisher deals with a collective licence: a participating AI company pays a blanket fee, while the amount available for publisher payments is linked to the licensee’s revenue. The article explains that ILC keeps a separate royalty pool for each AI company, so publishers are compensated from the pool associated with products that use their content. Allocation rules consider whether material is retrieved, used to ground an answer or shown to users, as well as whether the publisher is credited. The formula has not been disclosed. The approach is intended to recognise specialised content’s value rather than dilute its payment among all participating publishers. Publishers can choose which licensees may use their work and can remove content if they make a separate deal. The article also discusses a Mather Economics estimate that collective AI licensing could generate publisher compensation equal to 15–35 per cent of AI-company revenue. It describes RSL as a machine-readable standard for communicating licensing terms and notes that ILC is in discussions with other potential licensees.
https://internetcollective.org/ - The Internet Licensing Collective’s website introduces ILC as a nonprofit, publisher-led organisation that provides collective licensing for AI companies and content owners. It says one blanket licence can give AI businesses authorised access to a large body of digital content, while publishers can earn ongoing revenue when their work contributes to AI products. The site presents ILC as a way to make licensing practical across a broad publishing ecosystem, reducing the need for repeated individual negotiations. It reports participation by more than 3,100 media brands, content owners and publishing platforms, and describes a repertoire containing billions of licensable works. Its explanation of compensation emphasises content value rather than the size of a publisher’s catalogue. Factors include how a work helps shape or ground an answer, how often AI relies on it, and the value of the AI use. The site also outlines a publisher sign-up process based on RSL declarations and says existing website publishing workflows need not be replaced. For AI companies, it describes access through existing crawling infrastructure rather than custom integrations with each publisher. The homepage highlights Mather Economics’ projection that collective AI licensing could become a major market. It also presents ILC as an organisation connecting publishers and AI companies through a common framework, while promoting publisher control over licensing choices and the prospect of payments that grow with use and commercial demand.
https://rslstandard.org/guide/what-is-rsl - This RSL guide explains Really Simple Licensing as an open, machine-readable framework for communicating rights and compensation conditions for digital content. It traces the idea to RSS, which enabled publishers to syndicate material to third-party services and crawlers. RSL extends that approach by allowing publishers to specify licensing terms and usage conditions for content that may be crawled, processed or used in AI applications. The guide describes RSL as an XML-based document format covering many asset types, including webpages, books, videos, images and datasets. It says publishers and creators can define terms such as free access, pay-per-crawl and pay-per-inference for uses including AI training and web search. The standard also includes mechanisms intended to automate licensing and payment, and protocols for restricting unauthorised crawlers and AI agents. For non-public assets, the guide describes a secure licensing approach, while RSS feeds can be used to create public catalogues of licensable works. The page presents RSL as infrastructure for expressing permissions and commercial terms in a format that software can interpret. This directly supports the article’s description of RSL as a technical standard that complements the ILC’s collective licensing organisation. It also clarifies that the standard concerns machine-readable rights and usage conditions, rather than being only a payment arrangement between a publisher and a particular AI company.
https://web.inma.org/blogs/value-content/post.cfm/ai-pushes-licensing-to-become-a-third-revenue-stream - This INMA article, written by economists at Mather Economics, considers AI content licensing as a potential revenue stream alongside advertising and subscriptions. It argues that AI systems may consume and summarise publisher material without sending readers to the original website, weakening the traditional exchange of content for referral traffic. The article discusses publisher responses such as blocking crawlers, litigation, direct licensing, marketplaces and metered access. It notes that individual negotiations can be difficult to scale across large numbers of publishers and AI buyers, presenting collective licensing as a way to reduce transaction costs by bringing rights and buyers into a shared framework. Mather says it modelled the economics of AI demand for licensed content using the RSL collective model as a working case. The authors advise publishers to understand which rights they control, identify content likely to attract machine demand, and distinguish among training, retrieval and search uses because these may have different commercial effects. They also recommend measuring machine use alongside human engagement and revenue, and packaging material in structured formats that AI systems can discover and use under licence. The article acknowledges that the market’s final structure remains uncertain, but argues that publishers with distinctive, rights-cleared content should assess licensing strategically. It provides broader context for the collective model in the supplied article, explaining why publishers may seek a scalable alternative to one-off agreements.
https://www.mathereconomics.com/price-of-intelligence/ - Mather Economics’ page presents The Price of Intelligence, a report analysing the possible economics of collective licensing for AI content. The page estimates that publisher compensation could amount to 15–35 per cent of AI-company revenue, potentially creating a market worth tens of billions of dollars. It says the market could exceed the 2025 US display advertising market within three years, while clarifying that the initial calculation uses annual run-rate revenue from the two largest frontier-model companies rather than the entire AI industry. Mather describes content as an essential input to AI alongside computing power and energy, and argues that collective licensing could provide a scalable way to compensate rights holders. The proposed framework is presented as reducing repeated negotiations for AI companies and offering publishers a more transparent mechanism to earn from the value their material creates. The report’s reasoning draws on AI scaling laws and economic models of demand, and estimates that AI companies could be willing to allocate 15–35 per cent of revenue to retain licensed-content access. Mather also argues that the value of licensed content may increase as AI firms use more publicly available human-created text. The page compares collective revenue sharing with established practices in music and online video, while emphasising that its market forecasts are estimates rather than guaranteed outcomes. It supports the article’s reported compensation range and potential scale of the opportunity.
https://internetcollective.org/press/ilc-launch-2026 - This ILC press release announces the collective’s launch with Yahoo Scout as its first commercial licensee. It describes ILC as a nonprofit, publisher-led organisation bringing together more than 3,000 media brands, content owners and publishing platforms. Under the arrangement, Yahoo Scout receives access to permissioned content to inform its AI answers, while publishers can participate without charge and retain control over which licences they approve. The release says ILC offers AI companies a single blanket agreement covering extensive online material, with costs that can scale with use and business growth. It explains the framework’s main principles: one agreement can replace many individual negotiations; publishers choose which content, uses and licensees to permit; and royalty allocation is intended to reflect the content’s contribution and the value of the AI product. Allocation factors include how content is used and how frequently it is relied upon. The release also describes ILC as non-exclusive, allowing publishers to retain direct licensing deals and choose participation in particular licences. It cites Mather Economics’ estimate that collective licensing could generate publisher compensation equal to 15–35 per cent of AI-company revenue, with a potential market exceeding US display advertising within three years. Finally, it explains the connection between ILC and the RSL standard, which lets websites communicate machine-readable licensing terms for different AI uses.

Yahoo
artificial intelligence
publisher licensing