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Cited by 420

The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.

Artificial intelligence ‐ driven sustainable development: Examining organizational, technical, and processing approaches to achieving global goals

Open access
Kulkov, Ignat, Kulkova, Julia, Rohrbeck, Rene, Menvielle, Loick, Kaartemo, Valtteri, Makkonen, Hannu·2024·Sustainable Development
DOI 10.1002/sd.2773
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Abstract

This study presents a comprehensive literature review using a systematic approach to explore the role of artificial intelligence (AI) in promoting sustainable development in line with the United Nations Sustainable Development Goals (SDGs). The systematic review approach was applied to collect and analyze topics, and the literature search was conducted in two stages, encompassing 57 articles that met the research requirements. Our analysis reveals that AI's contribution to sustainability is concentrated within three key areas: organizational, technical, and processing aspects. The organizational aspect focuses on the integration of AI in companies and industries, addressing barriers to implementation and the relationship between companies, partners, and customers. The technical aspect highlights the development of AI algorithms that can address global challenges and contribute to the growth of stability and development in society. The processing aspect emphasizes the internal transformation of companies, their business models, and strategies in response to AI integration. Our proposed conceptual model outlines the essential elements organizations must consider when incorporating AI into their sustainability efforts, such as strategic alignment, infrastructure development, change management, and continuous improvement. By addressing these critical aspects, organizations can harness the potential of AI to drive positive social, environmental, and economic outcomes, ultimately contributing to the achievement of the SDGs. The model serves as a comprehensive framework for organizations seeking to leverage AI for sustainable development, but it should be adapted to individual contexts to ensure its relevance and effectiveness.

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Metadata

Authors
Kulkov, I., Kulkova, J., Rohrbeck, R., Menvielle, L., Kaartemo, V., & Makkonen, H.
Venue
Sustainable Development
Publisher
Wiley
Published
2023-10-06
Volume
32
Issue
3
Pages
2253-2267
ISSN
  • 0968-0802 (ISSN-L)
  • 1099-1719
DOI
10.1002/sd.2773
OpenAlex
W4387397415
Cited by
420
References
67
FWCI
36.98
Type
journal article
Language
en
Open access
hybrid

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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