Observed Signal · May 12, 2026 · Opinion · Source: AdExchanger · Impact: 3/5 · Sentiment: Positive
Content Licensing Needs Independent Settlement
David Kohl (Morgan Digital Ventures) argues that the rapid emergence of a content-licensing economy — driven by entrants like Microsoft and Amazon and startups such as TollBit and ProRata — exposes a structural problem: fragmented, proprietary settlement systems that cannot scale to the volume and opacity of LLM-driven usage. He cites examples (YouTube, Amazon Prime Video, Apple News+) to show how platforms currently build bespoke payment and reconciliation systems, and notes AI companies committed an estimated $2.9 billion in licensing fees in 2025 to a small set of large publishers. Kohl recommends building industry-governed, independent settlement infrastructure—comparable to ASCAP or the ACH network—to ensure neutral accounting, verifiable payments, transparency and trust before complexity and misaligned incentives recreate programmatic-era dysfunction at larger scale.
Argues for building neutral, industry-governed settlement infrastructure to address scaling, transparency and trust issues created by LLM-driven content licensing — a structural infrastructure topic with broad implications for publishers and platforms.
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Key Takeaways & Evidence Grounding
- Microsoft and Amazon have entered the content marketplace business.
- Startups TollBit and ProRata have built infrastructure to help publishers license content to large language models (LLMs).
- AI companies committed an estimated $2.9 billion in licensing fees in 2025 to a relatively small number of large publishers.
- YouTube tracks and attributes an estimated 5 to 8 billion content interactions daily across roughly three million monetized channels, using proprietary settlement infrastructure.
- The 2021 Syniverse security incident compromised credentials across nearly 235 carriers and exposed billing records, illustrating risks when critical infrastructure is not participant-governed.
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Related Market Signals & Shifts
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Are Content Marketplaces Becoming Real?
This Marketecture blog post argues that AI-driven content licensing could shift from traditional, lawyer-heavy licensing deals to automated, real-time content exchanges. It contrasts the current licensing landscape—with large publishers selling data for AI training—to a future model where per-article pricing and instant access through a content marketplace determine licensing costs for both training corpora and real-time inference data. The piece notes early momentum from Microsoft and the IAB Tech Lab, discusses legal friction (e.g., New York Times v. Perplexity), and highlights countermeasures like block lists (Cloudflare blocking AI crawlers). It covers incentives for publishers, potential liquidity questions, and the role of major platforms (Google, OpenAI, Meta) in shaping adoption. Overall, the article outlines a speculative but potentially transformative path for how AI providers acquire timely, licensed content and how publishers monetize it.
People Inc.: AI Licensing Boom, Revenue Still Lagging
People Inc. chief innovation officer Jon Roberts told a Digiday Publishing Summit audience that an influx of AI content-licensing marketplaces presents significant opportunities for publishers but has not yet produced large-scale revenue. People Inc. has multi-year, broad-access licensing deals with OpenAI and Meta and a pay-per-use arrangement with Microsoft. The company uses strict bot-blocking (allowing only permissioned crawlers) to protect content and is selectively permitting access to better understand marketplace economics. Roberts said publishers are collaborating on standards (IAB Tech Lab’s Content Monetization Protocols, Really Simple Licensing) and experimenting with compensation models such as "pay by demonstrated value". He also flagged cloud platforms (Azure, AWS, Google Cloud) as logical homes for such marketplaces.
Publishers Must Unite Against AI Content Theft Now!
An AdExchanger column argues publishers must unite to counter unauthorized content use by AI models. The author warns that training data theft threatens the economic incentives for original content and draws a Napster-era parallel to illustrate the risk. It outlines three paths to compel licensing: governmental intervention (SEC/DOJ injunctions); Google licensing via Google Search Console to curb access for unlicensed crawlers; and publisher unity to create a crawler-tight wall. The piece advocates building a Generative AI Licensing Matrix to guide negotiations and urges publishers to adopt a scalable licensing mechanism, akin to adding streaming rights to deals with platforms such as Spotify. It stresses that time is running out and that a coordinated front is essential to defend content creators and rebuild the business model, while noting that individual licensing efforts undermine broader collective action.
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