The Scholarly Kitchen: AI Isn't Going to Pay for Content — Part Two: The Path Forward (Guest Post)
Created with ChatGPT

The Scholarly Kitchen: AI Isn't Going to Pay for Content — Part Two: The Path Forward (Guest Post)

Jonathan WoahnFeb 4, 20261 min read
AI PublishingAI Content StrategyContent Monetization

The second installment continues exploration of AI's impact on content compensation, shifting focus to where genuine economic opportunity may emerge as AI systems become operationalized.

We're pleased to share that the second installment of Jonathan Woahn's guest series on The Scholarly Kitchen has been published.

Building on Part One's analysis of why AI training won't become a durable revenue engine for publishers, Part Two shifts focus to where genuine economic opportunity may emerge as AI systems become operationalized.

Key Topics

The article explores:

  • The Great Reallocation — How technology disruptions cause consumption and payment to fall out of sync, drawing parallels to the music industry's Napster-to-Spotify transition
  • Three Emerging Economic Models — Pay-Per-Use (PPU), Bring-Your-Own-License (BYOL), and Licensing on Demand (LOD)
  • Norms Worth Locking In Early — Why publishers should establish expectations around paid inference, attribution, usage transparency, and direct relationships before industry norms harden

The piece argues that "Publishing is not at the end of its economic arc; it is in the turbulent middle of a reallocation."

Read the full guest post on The Scholarly Kitchen

Stay in the loop

Get the latest insights on AI, content licensing, and the future of publishing.

Subscribing...

You're subscribed! We'll keep you in the loop.

Read More

No articles in this category.