Artificial Intelligence (AI) is increasingly recognized as a transformative enabler of sustainable development. This paper offers a novel contribution by systematically mapping the landscape of AI-related technologies using Sustainable Development Goals (SDGs) as a reliable functional proxy of sustainable development. We implement an improved Term Frequency-Inverse Document Frequency (TF-IDF) weighted Word2Vec model, combined with a bigram-based filtering strategy, to capture the nuanced contribution of AI patents to SDGs thematic areas. Our results reveal both the breadth and depth of AI’s impact, confirming its status of a general-purpose technology capable of driving cross-sectoral systemic transformations. By uncovering the interconnections between AI and sustainable development, this study contributes to the theoretical debate about digital and sustainable transitions and delivers practical insights for managers and policymakers, aiming to effectively manage these paradigm shifts. Finally, our work proposes a data-driven framework for tracking the evolution of sustainable-oriented AI evolutions while guiding policy design in support of Agenda (2030) goals.

Exploring the role of artificial intelligence in addressing sustainable development. A semantic analysis of AI patents

Alessandra Costa
Primo
;
Antonio Crupi;Fabrizio Cesaroni;Tindara Abbate
2025-01-01

Abstract

Artificial Intelligence (AI) is increasingly recognized as a transformative enabler of sustainable development. This paper offers a novel contribution by systematically mapping the landscape of AI-related technologies using Sustainable Development Goals (SDGs) as a reliable functional proxy of sustainable development. We implement an improved Term Frequency-Inverse Document Frequency (TF-IDF) weighted Word2Vec model, combined with a bigram-based filtering strategy, to capture the nuanced contribution of AI patents to SDGs thematic areas. Our results reveal both the breadth and depth of AI’s impact, confirming its status of a general-purpose technology capable of driving cross-sectoral systemic transformations. By uncovering the interconnections between AI and sustainable development, this study contributes to the theoretical debate about digital and sustainable transitions and delivers practical insights for managers and policymakers, aiming to effectively manage these paradigm shifts. Finally, our work proposes a data-driven framework for tracking the evolution of sustainable-oriented AI evolutions while guiding policy design in support of Agenda (2030) goals.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3338389
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact