Application Effect of AI Real Time Rendering Technology in Sports Live Streaming and Z Generation Market Prospect Analysis Based on Big Data
- DOI
- 10.2991/978-94-6239-640-1_24How to use a DOI?
- Keywords
- AI Real-Time Rendering Technology; Z-Generation; Sports Live Streaming; Immersive Viewing Experience; Influencing Factors; Market Prospect; Big Data Analysis
- Abstract
AI real-time rendering technology is reshaping the viewing ecosystem of sports live streaming and has become a core innovation to attract Generation Z users. The research finds that technical immersion, interactive participation and content personalization are the core driving factors, while usage threshold and content adaptability are the main constraints. The technology has broad application prospects in professional event broadcasting, folk sports promotion and sports IP derivative development. Moreover, policy support and industrial chain improvement will further accelerate its commercialization. This study provides empirical reference for the in-depth integration of AI real-time rendering technology and the sports live streaming industry, and also offers decision-making basis for industry participants to formulate Generation Z-oriented market strategies.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Peibing Cheng PY - 2026 DA - 2026/04/20 TI - Application Effect of AI Real Time Rendering Technology in Sports Live Streaming and Z Generation Market Prospect Analysis Based on Big Data BT - Proceedings of the 2026 5th International Conference on Big Data Economy and Digital Management (BDEDM 2026) PB - Atlantis Press SP - 256 EP - 264 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-640-1_24 DO - 10.2991/978-94-6239-640-1_24 ID - Cheng2026 ER -