Today, the use of generative AI is already ubiquitous, and industry observers expect this market to grow to more than USD1.3 trillion by 2032. However, gen AI is energy-intensive, causes carbon emissions, and consumes significant amounts of water. Beyond research which often focuses on “pure” IT issues such as GPT designs, we also consider gen AI’s sustainability costs. In doing so, we conduct a survey with experienced Digital Finance leaders with 5–25 years of expertise, ultimately to assess the benefits of gen AI against its sustainability costs. Driving future discussions, we focus on three findings: (1) Only two thirds of the respondents already have ESG costs in mind. (2) Carbon emissions, energy, and water consumption are the most relevant environment criteria. (3) Weighting the categories of efficiency, effectiveness, experience, and environment, the Four “E” Model can be customized to a company’s individual requirements, thus, it can help to identify best gen AI use cases.

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The Four “E” Model—Evaluating Gen AI in a More Balanced Way

  • Jörg H. Mayer,
  • Kira Bender,
  • Markus Esswein,
  • Reiner Quick

摘要

Today, the use of generative AI is already ubiquitous, and industry observers expect this market to grow to more than USD1.3 trillion by 2032. However, gen AI is energy-intensive, causes carbon emissions, and consumes significant amounts of water. Beyond research which often focuses on “pure” IT issues such as GPT designs, we also consider gen AI’s sustainability costs. In doing so, we conduct a survey with experienced Digital Finance leaders with 5–25 years of expertise, ultimately to assess the benefits of gen AI against its sustainability costs. Driving future discussions, we focus on three findings: (1) Only two thirds of the respondents already have ESG costs in mind. (2) Carbon emissions, energy, and water consumption are the most relevant environment criteria. (3) Weighting the categories of efficiency, effectiveness, experience, and environment, the Four “E” Model can be customized to a company’s individual requirements, thus, it can help to identify best gen AI use cases.