Navigating Artificial Intelligence for Sustainability in Organizations: Untangling Organizational, Technical, and Sustainable Characteristics through a Taxonomy

Authors

Tobias Plank, FIM Research Center for Information Management & University of Bayreuth & Technical University of MunichFollow
Daniel Leuthe, FIM Research Center for Information Management & Technical University of Applied Sciences Augsburg & Branch Business & Information Systems Engineering of the Fraunhofer FIT
Tim Meyer-Hollatz, FIM Research Center for Information Management & University of Bayreuth & Branch Business & Information Systems Engineering of the Fraunhofer FIT
Anna M. Oberländer, FIM Research Center for Information Management & University of Bayreuth & Branch Business & Information Systems Engineering of the Fraunhofer FIT

Author ORCID Identifier

Tobias Plank: https://orcid.org/0009-0008-5792-346X

Daniel Leuthe: https://orcid.org/0000-0001-8498-6951

Tim Meyer-Hollatz: https://orcid.org/0000-0002-0779-7038

Anna Maria Oberländer: https://orcid.org/0000-0002-1366-7141

Abstract

While the transformative potentials of artificial intelligence (AI) for achieving the United Nations’ Sustainable Development Goals (SDGs) are increasingly being acknowledged, the organizational adoption of AI lags behind. With ample research on AI for sustainability (AI4S), the field’s current fragmentation hinders cumulative theorizing and orchestrated research in academia and limits practitioners’ ability to assess which AI4S use cases align with their capabilities and strategic objectives. This study addresses the gap in understanding how AI4S unfolds in organizational contexts. While the research has provided insights into technical and sustainability dimensions, we have lacked a comprehensive framework that integrates organizational adoption. We conduct a systematic literature review of 158 AI4S use cases, categorizing them into a taxonomy with 3 meta-dimensions: technological, organizational, and sustainability, 10 dimensions, and 47 characteristics. Through this analysis, we identify seven novel archetypes of AI4S, each illustrating distinct pathways for organizational innovation that align with sustainable development objectives. These archetypes offer a structured framework for researchers to investigate adoption patterns across industries and guide practitioners in designing AI4S initiatives, thereby empowering organizational stakeholders to harness AI’s full potentials to help achieve the UN SDGs.

Recommended Citation

Plank, T., Leuthe, D., Meyer-Hollatz, T., & Oberländer, A. M. (In press). Navigating Artificial Intelligence for Sustainability in Organizations: Untangling Organizational, Technical, and Sustainable Characteristics through a Taxonomy. Communications of the Association for Information Systems, 58, pp-pp. Retrieved from https://aisel.aisnet.org/cais/vol58/iss1/33