Chief Editor
  • Prof. Christina Nikolova, PhD
Editorial Board
  • Prof. Christina Nikolova, PhD - UNWE
  • Prof. Elka Todorova, DSc. - UNWE
  • Prof. Maya Lambovska, DSc. - UNWE
  • Assoc. Prof. Todor Nedev, PhD - UNWE
  • Assoc. Prof. Dorina Kabakchieva, PhD - UNWE
  • Assoc. Prof. Paskal Zhelev, PhD - UNWE
Scientific Secretary
  • Assoc. Prof. Aleksandar Valkov, PhD - UNWE
Coordinator
  • Assist. Prof. Veselina Lyubomirova, PhD - UNWE
International Editorial Board
  • Damian Stantchev, PhD
    Edinburgh NAPIER University, UK

  • Ivaylo Vassilev, PhD
    University of Southampton,UK

  • Prof. Irina Kuzmina-Merlino, PhD
    Transport and Telecommunication Institute, Riga

  • Milan Zdravkovic
    University of Niš, Serbia

  • Prof. Niculae Mihaita, PhD
    Bucharest Academy of Economic Studies, Romania

  • Prof. Ricardo Jardim-Gonçalves, PhD
    UNINOVA institute, New University of Lisbon, Portugal

  • Prof. Ing. Jaroslav Belás, PhD
    Tomas Bata University in Zlín, Czech Republic

  • Prof. John Rijsman, PhD
    Tilburg University

  • Prof. Ing. Zdenek Dvorák, PhD
    University of Zilina, Slovak Republic

  • Prof. Zoran Cekerevac, PhD
    “Union – Nikola Tesla” University in Belgrade, Serbia

Artificial Intelligence for Sustainable Business Practices: A Case-Based Perspective on Generative and Predictive Technologies In B2B Operations
YEARBOOK OF UNWE
year 2025
Issue 1

Artificial Intelligence for Sustainable Business Practices: A Case-Based Perspective on Generative and Predictive Technologies In B2B Operations

Abstract

This article explores how artificial intelligence (AI), especially its predictive and generative forms, can contribute to sustainable development within B2B operations, with a special focus on Sustainable Development Goal 12 (SDG 12): Responsible Consumption and Production. Using a qualitative conceptual approach based on case studies, online sources and their connection to validated research in the field, the article examines the integration of AI technologies in two industry leaders – Maersk and Siemens. The findings illustrate how predictive AI, as the first type of algorithms considered, supports real-time decision-making and operational forecasting, while generative algorithms, on the other hand, promote innovation in logistics and industrial design. Based on the data, it is proven that AI-based technologies help reduce waste, improve resource efficiency and keep circular economy models sustainable. The study provides an initial foundation that can be further validated through empirical research and methodological frameworks, offering a valuable starting point for researchers and practitioners seeking to align AI applications with sustainability within the SDG12 framework in B2B environments.

JEL: Q55, Q56, L86

Keywords

artificial intelligence, SDG 12, sustainable business, business operations
Download YB.2025.1.06.pdf
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ISSN (print): 1312-5486
ISSN (online): 2534-8949