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.Pubblicazioni consigliate
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