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Making AI-Enhanced Videos: Analyzing Generative AI Use Cases in YouTube Content Creation

Torin Anderson, Shuo Niu

TL;DR

The paper analyzes 274 YouTube how-to videos to map GenAI use cases across the video production lifecycle, proposing a four-phase framework (planning, production, editing, uploading) and validating it with 2,829 annotated clips. Using YouTube Data API data collection, manual relevance checks, and thematic analysis with inter-annotator agreement (Cohen’s kappa ranging from ~0.51 to ~0.64), it identifies concrete tasks—such as scripting in planning; prompt refinement, image/video generation, and AI voiceovers in production; lip-syncing, restyling, upscaling, and translation in editing; and subtitles and title generation in uploading. Key findings show predominant reliance on image/video prompts in production (up to 60.9%), substantial use of AI voiceovers (33.9%), and meaningful editing automation, with narrower use of certain tasks like clipping, effects, or speech correction. The study discusses implications for design of GenAI tools, emphasizing prompt creation as a critical skill, concerns around originality and authenticity of multimodal AI content, and the need for visibility and transparency guidelines to sustain creator autonomy and audience trust.

Abstract

Generative AI (GenAI) tools enhance social media video creation by streamlining tasks such as scriptwriting, visual and audio generation, and editing. These tools enable the creation of new content, including text, images, audio, and video, with platforms like ChatGPT and MidJourney becoming increasingly popular among YouTube creators. Despite their growing adoption, knowledge of their specific use cases across the video production process remains limited. This study analyzes 274 YouTube how-to videos to explore GenAI's role in planning, production, editing, and uploading. The findings reveal that YouTubers use GenAI to identify topics, generate scripts, create prompts, and produce visual and audio materials. Additionally, GenAI supports editing tasks like upscaling visuals and reformatting content while also suggesting titles and subtitles. Based on these findings, we discuss future directions for incorporating GenAI to support various video creation tasks.

Making AI-Enhanced Videos: Analyzing Generative AI Use Cases in YouTube Content Creation

TL;DR

The paper analyzes 274 YouTube how-to videos to map GenAI use cases across the video production lifecycle, proposing a four-phase framework (planning, production, editing, uploading) and validating it with 2,829 annotated clips. Using YouTube Data API data collection, manual relevance checks, and thematic analysis with inter-annotator agreement (Cohen’s kappa ranging from ~0.51 to ~0.64), it identifies concrete tasks—such as scripting in planning; prompt refinement, image/video generation, and AI voiceovers in production; lip-syncing, restyling, upscaling, and translation in editing; and subtitles and title generation in uploading. Key findings show predominant reliance on image/video prompts in production (up to 60.9%), substantial use of AI voiceovers (33.9%), and meaningful editing automation, with narrower use of certain tasks like clipping, effects, or speech correction. The study discusses implications for design of GenAI tools, emphasizing prompt creation as a critical skill, concerns around originality and authenticity of multimodal AI content, and the need for visibility and transparency guidelines to sustain creator autonomy and audience trust.

Abstract

Generative AI (GenAI) tools enhance social media video creation by streamlining tasks such as scriptwriting, visual and audio generation, and editing. These tools enable the creation of new content, including text, images, audio, and video, with platforms like ChatGPT and MidJourney becoming increasingly popular among YouTube creators. Despite their growing adoption, knowledge of their specific use cases across the video production process remains limited. This study analyzes 274 YouTube how-to videos to explore GenAI's role in planning, production, editing, and uploading. The findings reveal that YouTubers use GenAI to identify topics, generate scripts, create prompts, and produce visual and audio materials. Additionally, GenAI supports editing tasks like upscaling visuals and reformatting content while also suggesting titles and subtitles. Based on these findings, we discuss future directions for incorporating GenAI to support various video creation tasks.

Paper Structure

This paper contains 13 sections, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. Method
  3. Result
  4. Planning Phase
  5. Production Phase
  6. Editing Phase.
  7. Uploading Phase
  8. Discussion
  9. A Support or Hindrance to Ideation and Creativity
  10. Prompt Creation as a Critical Skill
  11. Originality and Authenticity of Multimodal AI Content
  12. Visibility and Transparency of GenAI-Generated Content
  13. Future Work

Figures (6)

  • Figure 1: A conceptual framework illustrating GenAI use at different phases of video creation.
  • Figure 2: The distribution of videos mentioning each GenAI tool use case across the four stages of video creation.
  • Figure 3: Videos with GenAI applications during the Planning phase.
  • Figure 4: Videos with GenAI applications during the Production phase.
  • Figure 5: Videos with GenAI applications during the Editing phase.
  • ...and 1 more figures