The Hidden Carbon Cost of Short-Form Video AI: Examining the Sustainability Paradox in Social Media Marketing
ショート動画AIの隠れた炭素コスト：ソーシャルメディアマーケティングにおける持続可能性のパラドックス (AI 翻訳)
Krisztina Finta, Csaba Dezső Dér, Klaudia Gabriella Horváth, Edward Jay Mansarate Quinto
🤖 gxceed AI 要約
日本語
本研究は、AI駆動のショート動画マーケティングにおける持続可能性のパラドックスを調査。生成ツールの急速な採用がネットゼロ目標と相反することを示し、動画生成が画像生成の約30倍のエネルギーを消費することを明らかにした。さらに、新たな指標C-CPM（Carbon Per Mille）を提案し、EU CSRDのスコープ3開示要件に応える。
English
This study investigates the sustainability paradox in AI-driven short-form video marketing, revealing that video generation consumes ~30x more energy than image creation. It models that a mid-sized team producing 2,500 AI videos annually emits up to 325.5 kg CO₂. The paper introduces the Carbon Per Mille (C-CPM) indicator to address Scope 3 reporting gaps under the EU CSRD and proposes algorithmic greenwashing as a conceptual lens.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSSBJのスコープ3開示対応が進む中、AIツール利用に伴う間接排出の計測は未整備。本論文のC-CPM指標は、広告・マーケティング業界のカーボンアカウンティング実務に示唆を与える。
In the global GX context
As the EU CSRD expands Scope 3 disclosure requirements, this paper addresses a blind spot: the carbon footprint of AI-generated video content. It offers a practical metric (C-CPM) for firms to integrate carbon-aware strategies into marketing operations, relevant for global corporate sustainability reporting.
👥 読者別の含意
🔬研究者:Provides initial carbon modeling for AI video generation and introduces algorithmic greenwashing as a framework for further study.
🏢実務担当者:Marketing and sustainability teams can use the C-CPM indicator to measure and reduce hidden Scope 3 emissions from AI video production.
🏛政策担当者:Highlights the need for AI-specific sustainability metrics in reporting frameworks like CSRD and potential regulation of AI energy use.
📄 Abstract（原文）
This study investigates the sustainability paradox inherent in AI-driven short-form video marketing, where the rapid adoption of generative tools (e.g., Runway, Pika, Sora) increasingly conflicts with corporate Net Zero commitments. Drawing on a systematic literature review (2019-2026) at the intersection of AI ethics, environmental science, and marketing, alongside scenario-based carbon modeling, the analysis demonstrates that video generation consumes approximately 30 times more energy than image creation. Estimates indicate that a mid-sized marketing team generating 2,500 AI videos annually can emit up to 325.5 kg CO₂ - a hidden environmental cost largely obscured by decentralized "shadow AI" practices and the lack of AI-specific sustainability metrics in current KPIs. To address this reporting gap, particularly in light of expanding Scope 3 disclosure requirements under the EU CSRD, the paper introduces the Carbon Per Mille (C-CPM) indicator. By proposing algorithmic greenwashing as a conceptual lens, this research provides an initial academic assessment of the carbon footprint of AI video generation and advocates for the integration of carbon-aware operational strategies.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.18690/um.epf.7.2026.38first seen 2026-07-26 04:54:47
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