The environmental impact Generative AI – and in particular, Large Language Models (LLMs) – is far from negligi- ble. Despite this, LLMs can help companies rethink sustainable practices, especially in small organizations lacking technical and methodological expertise in ecological transition. Our work has a twofold aim: (i) to investigate whether LLMs can effectively support the reengineering of business processes toward greener alternatives, and (ii) to assess whether employing such energy- intensive technologies aligns with sustainability objectives in a meaningful and cost-effective way. To address these questions, we have designed a three-step methodological Framework currently under implementation. The Framework involves the use of LLMs ”as-as-service” for refactoring textual descriptions of business processes. Preliminary results are promising, with GPT-4o and Claude 3.5 demonstrating strong performance on a benchmark of well-known processes provided by Camunda, while the study on the energetic impact of LLMs in organizational settings is still ongoing.

Can Energy Vampires make organizations more sustainable? The case of LLMs and BPM

VERGALLO R.
;
ANDRENUCCI A.;CASCIARO S.;DE GAETANIS M.;ELIA A.;GRAVINA G. L.;MAINETTI L.;MATINO S.
2025-01-01

Abstract

The environmental impact Generative AI – and in particular, Large Language Models (LLMs) – is far from negligi- ble. Despite this, LLMs can help companies rethink sustainable practices, especially in small organizations lacking technical and methodological expertise in ecological transition. Our work has a twofold aim: (i) to investigate whether LLMs can effectively support the reengineering of business processes toward greener alternatives, and (ii) to assess whether employing such energy- intensive technologies aligns with sustainability objectives in a meaningful and cost-effective way. To address these questions, we have designed a three-step methodological Framework currently under implementation. The Framework involves the use of LLMs ”as-as-service” for refactoring textual descriptions of business processes. Preliminary results are promising, with GPT-4o and Claude 3.5 demonstrating strong performance on a benchmark of well-known processes provided by Camunda, while the study on the energetic impact of LLMs in organizational settings is still ongoing.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/558786
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