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Forecasting Artificial General Intelligence for Sustainable Development Goals: A Data-Driven Analysis of Research Trends

Author

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  • Raghu Raman

    (Amrita School of Business, Amritapuri Campus, Amrita Vishwa Vidyapeetham, Amritapuri 690525, India)

  • Akshay Iyer

    (Department of Microbiology and Immunology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA)

  • Prema Nedungadi

    (Amrita School of Computing, Amritapuri Campus, Amrita Vishwa Vidyapeetham, Amritapuri 690525, India)

Abstract

Artificial general intelligence (AGI) is often depicted as a transformative breakthrough, yet debates persist on whether current advancements truly represent general intelligence or remain limited to domain-specific applications. This study empirically maps AGI-related research across subject areas, geographies, and United Nations Sustainable Development Goals (SDGs) via machine learning-based analysis. The findings reveal that while the AGI discourse remains anchored in computing and engineering, it has diversified significantly into human-centered domains such as healthcare (SDG 3), education (SDG 4), clean energy (SDG 7), industrial innovation (SDG 9), and public governance (SDG 16). Geographically, research remains concentrated in the United States, China, and Europe, but emerging contributions from countries such as India, Pakistan, and Costa Rica suggest a gradual democratization of AGI exploration. Thematic expansion into legal systems, governance, and environmental sustainability points to AGI’s growing relevance for systemic societal challenges, even if true AGI remains aspirational. Funding patterns show strong private and public sector interest in general-purpose AI systems, whereas institutional collaborations are increasingly global and interdisciplinary. However, challenges persist in cross-sectoral data interoperability, infrastructure readiness, equitable funding distribution, and regulatory oversight. Addressing these issues requires anticipatory governance, international cooperation, and capacity-building strategies to ensure that the evolving AGI landscape aligns with inclusive, sustainable, and socially responsible futures.

Suggested Citation

  • Raghu Raman & Akshay Iyer & Prema Nedungadi, 2025. "Forecasting Artificial General Intelligence for Sustainable Development Goals: A Data-Driven Analysis of Research Trends," Sustainability, MDPI, vol. 17(16), pages 1-29, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7347-:d:1724650
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    References listed on IDEAS

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