Nieman Lab: the AI content licensing market puts publishers in a double bind

In May 2026, Nieman Journalism Lab covered a report from the thinktank Open Markets Institute that maps the emerging market for AI content licensing — and names a structural problem at its center. The analysis argues that news publishers are caught in a double bind: the same large technology companies developing commercial AI products, which have already reduced publishers’ referral traffic, are now the ones dictating what alternative revenue from content licensing looks like.

The report identifies two tracks through which publishers are attempting to monetize AI access to their content. One involves direct licensing deals with large AI platforms. The other runs through new intermediary startups — Sphere, ScalePost, Defined, and TollBit are named — that aim to create a marketplace layer between publishers and AI developers. Both tracks are shaped by the same asymmetry: publishers need the revenue, and the AI companies setting licensing terms have little incentive to offer favorable conditions when they can also train on content available elsewhere.

The practical implication for content organizations and working journalists is that the revenue models being built around AI use of editorial content are being constructed on terms that publishers have limited power to contest. Newsrooms making decisions about paywalls, SEO, and whether to license content to AI platforms are doing so without a neutral market setting the price. Independent outlets and smaller publishers face this constraint with fewer options than large media companies, which have more leverage in negotiations.

The article is useful for editorial directors, newsroom leaders, and journalists who want to understand the economic structure forming around AI-generated traffic and content licensing, rather than just the technology itself. It does not address how individual journalists should adjust their own writing or publishing practices.