Monetizing Generative AI: YouTubers'Collective Knowledge on Earning from Generative AI Content

2026-03-07

AI Summary

This study investigates how YouTube creators leverage generative AI for monetization and uncovers the structural tensions embedded in their collective practices. Through qualitative content analysis of 377 relevant videos, the research systematically codes revenue models—including advertising, direct sales, affiliate marketing, and revenue sharing—and identifies ten archetypal application scenarios. It reconceptualizes generative AI–based monetization as a community-constructed knowledge system, revealing the collaborative logics and governance tensions that emerge as creators navigate platform algorithms either cooperatively or adversarially. The findings offer novel perspectives for designing creator-centric AI tools and reimagining platform governance. Furthermore, the study highlights critical ethical and practical concerns, such as unverifiable income claims, content appropriation, synthetic engagement, and ambiguities surrounding authorship.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Game Theory and Economic Paradigms: Mechanism Design
• Humans and AI: Game Design — Procedural Content Generation & Storytelling

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content

Abstract

Generative Artificial Intelligence (GenAI) is reshaping creative labor by enabling the rapid production of text, images, and videos. On YouTube, creators are developing new ways to leverage these tools and share knowledge about how to pursue income through such strategies. However, little is known about what GenAI knowledge has been collectively constructed around monetizing GenAI as a community practice of acting both with and against algorithmically mediated platforms. We analyze 377 YouTube videos in which creators publicly promote workflows, revenue claims, and monetization strategies for GenAI-enabled content. Our analysis identifies ten shared use cases that frame AI-supported income opportunities, and examines how this GenAI knowledge repository embodies a collective effort to leverage platform infrastructures for monetization -- including advertising, direct sales, affiliate marketing, and revenue-sharing models. We further surface structural tensions in AI-mediated creative labor, including unverifiable income claims, content misappropriation, synthetic engagement practices, and shifting authorship norms. We conceptualize creators'collective understanding and adoption of GenAI in the context of monetizing creative labor, with implications for the design of creator-centered GenAI technologies and responsible platform policy.

Problem

• Generative AI
• Monetization
• Creative Labor
• YouTube
• Collective Knowledge

Innovation

• Generative AI
• creator economy
• monetization strategies
• collective knowledge
• platform labor