AI-Enabled Strategic Transformation and Sustainable Outcomes in Serbian SMEs

Aleksandar M. Damnjanović (), Milan Rašković, Svetozar D. Janković, Boris Jevtić, Volodymyr N. Skoropad, Zoran D. Marković, Violeta Lukić-Vujadinović, Zoran Injac and Srđan Marinković
Additional contact information
Aleksandar M. Damnjanović: Faculty of Business and Law, University Milija Babović, Teodora Drajzera 27, 11040 Belgrade, Serbia
Milan Rašković: Faculty of Business and Law, University Milija Babović, Teodora Drajzera 27, 11040 Belgrade, Serbia
Svetozar D. Janković: School of Computing, Union University, 11000 Belgrade, Serbia
Boris Jevtić: Computing Faculty RAF, University Union, 11000 Belgrade, Serbia
Volodymyr N. Skoropad: Faculty of Business and Law, University Milija Babović, Teodora Drajzera 27, 11040 Belgrade, Serbia
Zoran D. Marković: Faculty of Business and Law, University Milija Babović, Teodora Drajzera 27, 11040 Belgrade, Serbia
Violeta Lukić-Vujadinović: Department for Transportation Engineering, Faculty of Engineering Management and Economics, University Business Academy, 21000 Novi Sad, Serbia
Zoran Injac: Department for Industrial Engineering, Faculty of Engineering Management and Economics, University Business Academy, 21000 Novi Sad, Serbia
Srđan Marinković: University for Business Engineering and Management, Despota Stefana Lazarevića, 7800 Banja Luka, Bosnia and Herzegovina

Sustainability, 2025, vol. 17, issue 19, 1-33

Abstract: Serbian SMEs face mounting pressure to stay competitive, agile, and aligned with sustainability goals amid rapid digital change. This mixed-method study—12 qualitative case studies and a survey of 200 firms—examines how AI adoption supports flexible and adaptive strategic transformation. We examine how organizational context and AI readiness translate into the strategic application of AI and, in turn, sustainable development and strategic performance outcomes among Serbian SMEs. Through the AI-Driven Strategic Transformation Framework (AISTF-SME), three adoption types were identified —Traditionalists, Experimenters, and Strategic Adopters—distinguished by digital maturity, strategic integration, and sustainability orientation. While AI is primarily deployed for operational efficiency, firms with higher AI maturity and tighter strategic alignment report stronger gains in agility, innovation, and customer experience; sustainability-oriented use cases remain limited. Key barriers include shortages of technical talent, financial constraints, and insufficient institutional support. We recommend a multi-stakeholder policy approach emphasizing sector-specific AI readiness programs, better access to funding, and stronger university–industry collaboration. The findings enrich digital transformation and sustainability research and offer practical guidance for accelerating AI adoption in transitional economies.

Keywords: artificial intelligence; digital transformation; small and medium-sized enterprises (SMEs); strategic alignment; structural equation modeling (SEM); mixed methods; sustainability; Serbia; ESG; policy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/19/8672/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/19/8672/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:19:p:8672-:d:1759113

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().