The potential of artificial intelligence in industrial companies’ product–service systems

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.

Authors

Institutions

Publication Details

Journal
Upravlenets
Published
2025-09-09
DOI
https://doi.org/10.29141/2218-5003-2025-16-4-5
Primary Topic
Service and Product Innovation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The potential of artificial intelligence in industrial companies’ product–service systems

Olga Chernova
Upravlenets
Service and Product Innovation
article

The potential of artificial intelligence in industrial companies’ product–service systems

Olga Chernova
article en

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.

UpravlenetsVol. 16(4)
Southern Federal University (RU)
Russian Science Foundation, Southern Federal University
Openalex Percentile: Top 66%
Service and Product Innovation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.