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Publishers and AI developers are moving away from upfront training fees toward ongoing, usage-based licensing tied to live access and attribution. The Digiday explainer on grounding and RAG signals a sector-wide shift in monetisation, with high-profile licensing deals showing real-time sourcing as the new revenue driver while flagging ongoing IP questions for rights holders.<\/p>\n<\/div>\n
Publishers and AI developers are reshaping the economics of content in real time, moving away from one-off training payments toward ongoing, usage-based models that tie money to live access and attribution. The Digiday explainer on grounding, RAG and related terms frames a sector-wide shift in how content is monetised as large language models increasingly fetch current material from publishers rather than rely solely on pre-trained data. Industry observers say this shift is more than jargon: it is now a central pricing lever. Aaron G. Rubin, a partner at Gunderson Dettmer, notes that per-usage pricing has become the preeminent slice of the licensing pie, as deals migrate from lump-sum training payments to recurring charges linked to how often publishers\u2019 content is surfaced. The same piece also highlights publishers\u2019 caution around licensing for training, with real-time grounding seen as the more valuable revenue stream. The interviewees stress that real-time content sourcing creates ongoing opportunities for attribution and visibility, but it also raises ongoing IP questions for rights holders. And the article points to real-world examples that underline the trend, including Gannett\u2019s foray into Perplexity\u2019s Publisher Program, a move that ties licensing to advertising revenue rather than to training datasets.<\/p>\n
The Times\u2019s foray into licensing with a major platform marks a headline moment in the licensing shift. TechCrunch reported on May 29, 2025 that The New York Times agreed to license its editorial content to Amazon to train the tech giant\u2019s AI systems, covering Times articles as well as material from NYT Cooking and The Athletic, with the potential for integration into Alexa. The Times stressed that the arrangement will connect readers with direct links to Times products where appropriate, while noting that terms remained undisclosed. CNBC echoed the development, saying the deal allows real-time display of summaries and short excerpts within Amazon products and services (including Alexa) and could extend to training Amazon\u2019s foundation models. The Times\u2019s move, framed against its own litigation against other AI players over copyright, signals a broader industry drift toward licensing content for live, live-tested AI outputs rather than payment for training alone. The broader context is not without tension: in August 2025, a major copyright case involving Perplexity AI progressed, with News Corp\u2019s Dow Jones and The New York Post succeeding in pushing forward their claims, underscoring publishers\u2019 intensifying enforcement of their rights as AI operators experiment with grounding and RAG licensing. The case illustrates why publishers are increasingly favouring licensing models that ensure linkability and attribution in AI responses.<\/p>\n
Publisher programmes and the monetisation framework themselves have continued to evolve in 2025. Perplexity\u2019s collaboration with Gannett\u2014announced in the Digiday piece as part of the platform\u2019s grounding approach\u2014illustrates how publishers are turning to ad-revenue-sharing models to monetise AI-enabled visibility. Perplexity\u2019s own communications describe Gannett joining the Perplexity Publisher Program to make USA TODAY and USA TODAY Network journalism available within Perplexity\u2019s AI-powered search and its Comet browser, with Gannett gaining access to Perplexity\u2019s Sonar API and Enterprise Pro for staff use. The arrangement reflects a broader attempt to reward quality journalism within AI ecosystems by tying revenue to how often a publisher\u2019s content is surfaced and cited in AI answers, rather than relying on a single up-front fee. Perplexity\u2019s stance is that this model helps ensure publishers receive ongoing value from AI-enabled discovery, while readers receive more credible, source-attached information. The partnership comes in the context of a rapidly expanding ecosystem of publisher programmes and evolving monetisation standards, with publishers and AI platforms both refining the balance between licensing, attribution, and new automated discovery tools.<\/p>\n
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