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Impact of AI on Business Sustainability and Efficiency

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 906

Special Issue Editors


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Guest Editor
Swiss School of Business and Management, Geneva, Switzerland
Interests: sustainable entrepreneurship; global hospitality and tourism management; strategic global hospitality and tourism management; IT in hospitality; advanced business modelling; green business; human–environmental sciences
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia
Interests: human resource management; work motivation; teamwork; job satisfaction; organizational commitment; organizational behavior

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Guest Editor
Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia
Interests: environmental analysis; environment; water quality; wastewater treatment; water and wastewater treatment; environmental impact assessment; environmental pollution; water analysis; water treatment; environmental monitoring

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Guest Editor
Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia
Interests: economics of the firm; principles of economics; engineering economics; business
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Swiss School of Business and Management, Geneva, Switzerland
Interests: information security; open source software

Special Issue Information

Dear Colleagues,

This Special Issue titled “Impact of AI on Business Sustainability and Efficiency” in Sustainability (MDPI) aims to bring together cutting-edge research on the ways in which artificial intelligence (AI) can be harnessed to bolster both the sustainability and efficiency of organizations across various sectors. As AI tools and techniques continue to rapidly evolve, businesses are increasingly integrating data-driven insights into strategic decision-making processes, operational workflows, and stakeholder engagement. This Special Issue therefore provides an academic platform for interdisciplinary discussions surrounding how AI-driven solutions can promote long-term economic, environmental, and social value.

We welcome rigorous empirical analyses, methodological advancements, conceptual frameworks, and case studies that explore (but are not limited to) the following:

  • Sustainable operations through AI-enabled resource optimization and waste reduction.
  • The role of AI in fostering inclusive and responsible business practices.
  • Ethical implications of AI deployment on social equity and environmental justice.
  • AI-driven decision support systems for corporate governance and policy compliance.
  • Sector-specific case studies illustrating the best practices in AI-based sustainable innovation.
  • Multi-stakeholder collaborations and partnerships for AI-driven sustainability initiatives.
  • Risk assessment, mitigation strategies, and resilience building in AI adoption.

Relationship to Existing Literature

This Special Issue is grounded in, and builds upon, multiple strands of the literature that collectively shape how AI is perceived and utilized in sustainable business. In the broader sustainability literature, scholars have highlighted the importance of organizational resilience, circular economy principles, and collaborative innovation to address global environmental and social challenges. AI-focused research, meanwhile, has extensively examined algorithmic complexity, big data applications, machine learning insights, and AI governance frameworks. By integrating these two domains, this issue seeks to offer a holistic view of how AI can be a transformative force, driving resource efficiency, ethical decision making, inclusive growth, and long-term competitiveness.

Prior studies have explored the promise of AI in domains such as predictive maintenance, energy management, and supply chain optimization—areas that are crucial to achieving sustainability targets. Nevertheless, significant gaps remain in understanding the nuanced interactions between AI adoption and its societal or ecological impacts. Furthermore, while AI applications may enhance operational efficiency, the net effect on sustainability depends on organizational culture, stakeholder alignment, and robust regulatory frameworks. This Special Issue contributes to bridging these gaps by seeking research that critically examines the opportunities, challenges, and governance mechanisms needed to ensure AI is leveraged responsibly for sustainability outcomes.

Ultimately, “Impact of AI on Business Sustainability and Efficiency” aspires to advance the academic conversation on the convergent pathways of AI innovation and sustainable development. By curating multidisciplinary research, it hopes to inform policymakers, industry leaders, and the academic community on designing AI deployments that deliver tangible positive impacts—environmentally, socially, and economically—in a rapidly transforming business landscape.

Prof. Dr. Minja Bolesnikov
Prof. Dr. Jelena Culibrk
Prof. Dr. Maja Petrovic
Dr. Andrea Ivanisevic
Dr. Mario Silić
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence (AI)
  • business sustainability
  • operational efficiency
  • resource optimization
  • ethical implications
  • corporate governance
  • stakeholder engagement
  • circular economy
  • responsible innovation
  • resilience building

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Published Papers (1 paper)

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Research

22 pages, 739 KiB  
Article
Balancing Efficiency and Sustainability: Multicriteria Decision-Making for Pumping Station Upgrades
by Sara Koprivica, Andrea Ivanišević, Darko Stefanović, Milan Jovin and Maja Petrović
Sustainability 2025, 17(7), 2818; https://doi.org/10.3390/su17072818 - 22 Mar 2025
Viewed by 317
Abstract
This study examines the financial and operational sustainability of modernizing drainage pump station systems in Vojvodina, aiming to improve energy efficiency and adapt to climate change. Various technical and economic modernization scenarios were analyzed to identify the optimal variant (V3.1), which balances investment [...] Read more.
This study examines the financial and operational sustainability of modernizing drainage pump station systems in Vojvodina, aiming to improve energy efficiency and adapt to climate change. Various technical and economic modernization scenarios were analyzed to identify the optimal variant (V3.1), which balances investment costs, operational efficiency, and long-term environmental benefits. The analytical approaches used include multicriteria analysis, the Analytical Hierarchy Process (AHP) model, the TOPSIS technique, and fuzzy logic, providing comprehensive insights into the ranking of the four proposed variants. The results indicate that Variant V3.1, which features local SCADA systems and centralized management, offers an optimal solution for modernization. This model enhances operational reliability, reduces energy costs, and contributes to the sustainable development of the region through more efficient resource utilization. The proposed approach not only meets the specific needs of Vojvodina but also provides a broader framework for assessing similar infrastructure projects in other regions. Full article
(This article belongs to the Special Issue Impact of AI on Business Sustainability and Efficiency)
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