Authors:

Olga A. Chernova, Dr. Sc. (Econ.), Associate Professor, Professor of Information Economics Dept. Southern Federal University

Abstract:

Industrial enterprises are increasingly integrating digital innovations to enhance their product-service systems (PSSs); however, the adoption of artificial intelligence (AI) is hindered by a lack of awareness of its potential benefits. The purpose of the paper is to identify prospective applications of AI technologies in PSSs of industrial enterprises to create new value propositions. This study is based on the concepts of product-service systems and artificial intelligence. Research methods are content analysis, structural and logical analysis, methods of descriptive statistics, and SWOT analysis. The evidence base covers official data from the RF Federal State Statistics Service (Rosstat) and government agencies for 2023–2024. The research findings show that the role of various types of AI technology in PSSs differs according to the business model being implemented, which produces a varying effect on value creation. Virtual assistants and chatbots are found to be the most common in industrial PSSs. The paper systematizes the tasks performed by individual AI technologies in different PSS business models and highlights AI functionality in PSSs when creating value. SWOT analysis was used to reveal the strengths and weaknesses of AI technologies in product-service systems. The work contributes to research on digitalization of business processes in industry by going beyond the conventional understanding of AI as a “black box” and finding additional opportunities for the use of AI in PSSs of industrial companies. The findings can be utilized to map out a strategy for introducing digital innovations in industry and identifying the potential for enhancing the intelligence of product-service offerings.

Keywords: product-service system (PSS); industrial enterprise; artificial intelligence; PSS business model; digital innovation; competitiveness.

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For citation: Chernova O.A. (2025). The potential of artificial intelligence in industrial companies’ product–service systems. Upravlenets/ The Manager, vol. 16, no. 4, pp. 70–86. DOI: 10.29141/2218-5003-2025-16-4-5. EDN: SMVADV.