IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-96-8015-3_8.html
   My bibliography  Save this book chapter

Balancing Act: AI’s Role in Reconciling Economic Growth and Environmental Sustainability

In: Generative AI for a Net-Zero Economy

Author

Listed:
  • Erich Schlesinger

    (Wyższa Szkoła Biznesu – National Louis University)

  • Uyên Nguyễn Cao Thục

    (Duy Tan University)

  • Subhankar Das

    (Duy Tan University)

Abstract

In this Anthropocene age, the growing conflict between economic growth and sustainability can no longer be neglected, and brainstorming solutions is essential. This chapter discusses artificial intelligence (AI) not just as a technology but as a paradigm shift enabling solutions to multiple challenges by mapping the dual imperatives of resource efficiency and multipurpose modelling for environmental prediction, accelerating circular economies. Via interdisciplinary analysis and design—encompassing ecological economics, case studies, and ethical frameworks—the study illustrates AI’s promise to delink economic growth from environmental degradation, as demonstrated through smart energy grids, precision agriculture, and waste management applications. However, the technology’s ethical risks—energy-intensive infrastructure, algorithmic bias, and inequitable access—highlight the urgent need for green and equitable governance models. Aligning AI with sustainability principles of transparency, equity, and planetary boundaries will empower stakeholders to build AI-driven, sustainable, and inclusive growth. The results support redesigning collaborative frameworks to prioritise Green AI innovations and policy organisation, while advancing for global equity to convert the theoretical potential of Green AI into implementable pathways for a regenerative future.

Suggested Citation

  • Erich Schlesinger & Uyên Nguyễn Cao Thục & Subhankar Das, 2025. "Balancing Act: AI’s Role in Reconciling Economic Growth and Environmental Sustainability," Springer Books, in: Subhra R. Mondal & Lukas Vartiak & Subhankar Das (ed.), Generative AI for a Net-Zero Economy, pages 129-143, Springer.
  • Handle: RePEc:spr:sprchp:978-981-96-8015-3_8
    DOI: 10.1007/978-981-96-8015-3_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-981-96-8015-3_8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.