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. • AI patents show strong alignment with key Sustainable Development Goals. • Weighted TF-IDF Word2Vec + HDBSCAN enables semantic mapping of AI patents to SDG. • AI acts as a general-purpose tech driving sustainability across industries. • 94.7 % of AI patents linked to a single SDG. • Data-driven framework guides SDG-aligned AI policy and innovation paths.
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Costa et al. (2025) studied this question.
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