mlsanityData to 14 Oct 2026

Is the future of AI green? What can innovation diffusion models say about generative AI's environmental impact?

arXiv 2603.21419 ↗First posted 22 Mar 2026cs.AIcited by 0

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Abstract (arXiv)

The rise of generative artificial intelligence (GAI) has led to alarming predictions about its environmental impact. However, these predictions often overlook the fact that the diffusion of innovation is accompanied by the evolution of products and the optimization of their performance, primarily for economic reasons. This can also reduce their environmental impact. By analyzing the GAI ecosystem using the classic A-U innovation diffusion model, we can forecast this industry's structure and how its environmental impact will evolve. While GAI will never be green, its impact may not be as problematic as is sometimes claimed. However, this depends on which business model becomes dominant.

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7 of 17 references.

References · 7

  1. 2019Green AIcited by 627
  2. 2022The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrinkcited by 184
  3. 2023From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inferencecited by 170
  4. 2023Generative AIcited by 120
  5. 2024Small Language Models: Survey, Measurements, and Insightscited by 112
  6. 2025Measuring the environmental impact of delivering AI at Google Scalecited by 32
  7. 2024Algorithmic progress in language modelscited by 31

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  1. 2024Generative AI for Low-Carbon Artificial Intelligence of Things with Large Language Models
  2. 2025Climate Implications of Diffusion-based Generative Visual AI Systems and their Mass Adoption
  3. 2026The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI
  4. 2026Environmental Impact of Generative and Agentic AI: An in-Depth Analysis and Green Solutions
  5. 2026Environmental Footprint of GenAI Research: Insights from the Moshi Foundation Model
  6. 2024Latent Pollution Model: The Hidden Carbon Footprint in 3D Image Synthesis
  7. 2025Geospatial Diffusion for Land Cover Imperviousness Change Forecasting
  8. 2023Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet