Artificial Intelligence Technologies for Small and Micro Enterprises: Application Recommendations for Improving Operational Efficiency
- Authors: Ignatova V.A.1, Kuzmin G.N.1
-
Affiliations:
- MIREA – Russian Technological University
- Issue: Vol 11, No 5 (2024)
- Pages: 64-77
- Section: MANAGEMENT IN ORGANIZATIONAL SYSTEMS
- URL: https://journals.eco-vector.com/2313-223X/article/view/657480
- DOI: https://doi.org/10.33693/2313-223X-2024-11-5-64-77
- EDN: https://elibrary.ru/BSDLKF
- ID: 657480
Cite item
Open Access
Access granted
Abstract
This article explores the potential application of artificial intelligence (AI) technologies to enhance the operational efficiency of small and micro-enterprises (SMEs) in Russia. The aim of the study is to generalize experience and develop recommendations. Considering the limited resources and specificity of SME activities, the authors examine the challenges faced by these enterprises, as well as the broader technological context. Utilizing computer technologies and data analysis, the authors extracted descriptions of SME representatives’ experiences from the russian professional social network TenChat. The extracted algorithmic themes were expertly transformed into directions for the application of AI technology and formed the basis for the development of practical recommendations. The study formulated conclusions on possible directions for the application of AI technologies, including marketing and customer service, automation and optimization of routine tasks, data analysis, and process optimization. The developed recommendations include strategic decisions, AI reactivity, team management, operational activity provisioning, and data management. The results of the study are of interest to entrepreneurs, SME managers, and researchers seeking to enhance business efficiency through AI technologies.
Full Text
About the authors
Victoria A. Ignatova
MIREA – Russian Technological University
Author for correspondence.
Email: vignatovaa@yandex.ru
lecturer, Department of Industrial Programming; Institute for Advanced Technologies and Industrial Programming
Russian Federation, MoscowGleb N. Kuzmin
MIREA – Russian Technological University
Email: kuzmin_g@mirea.ru
ORCID iD: 0000-0001-5398-577X
SPIN-code: 3701-4512
Scopus Author ID: 57198490261
ResearcherId: E-2859-2015
senior lecturer, Department of Industrial Programming; Institute for Advanced Technologies and Industrial Programming
Russian Federation, MoscowReferences
- Barinova V.A., Zemtsov S.P., Tsareva Yu.V. In search of entrepreneurship in Russia. Part I. What Prevents Small and Medium Businesses from Developing. Moscow: Delo, 2023.
- Nevmyvako V.P. Digital economy and Industry 4.0: New challenges for small and medium businesses. Problems of Market Economy. 2021. No. 1. Pp. 96–109. (In Rus.)
- Khudaiberdiev O.A. Industry 4.0 as an innovative environment of opportunities for small entrepreneurship. Bulletin of the Plekhanov Russian University of Economics. 2023. No. 4. Pp. 194–201. (In Rus.)
- DaSilva C.M., Trkman P. Business model: What it is and what it is not. Long Range Planning. 2014. Vol. 47. No. 6. Pp. 379–389.
- Osterwalder A. et al. Value proposition design: How to create products and services customers want. John Wiley & Sons, 2015.
- Novakova O.N. Problems of improving the efficiency of enterprise operations. Symbol of Science. 2016. No. 9-1. Pp. 127–130. (In Rus.)
- Strekalova N.D. Business model concept: methodology of systems analysis. Bulletin of the Russian State Pedagogical University named after A.I. Herzen. 2009. No. 92. Pp. 95–105. (In Rus.)
- Zenevich D.A. Operational efficiency and reserves for its improvement. In: Engineering economics. Collection of materials of the 79th student scientific and technical conference, section “Engineering economics”. Minsk: BNTU, 2023. Pp. 98–101.
- Martianova A.I. И. Internet trade as a factor in small business development. Scientific Electronic Journal “Academic Journalism”. 2023. No. 9-2. Pp. 81–85. (In Rus.)
- Novoseltseva G.B., Rasskazova N.V. Prospects for small business in the digital economy. Issues of Innovative Economics. 2020. No. 10 (1). Pp. 521–532. (In Rus.)
- Gladilina I.P., Litvenko I.Yu., Kiryukhina E.O. Modern management technologies and Industry 4.0. Financial Markets and Banks. 2021. No. 12. Pp. 21–23. (In Rus.)
- Vaswani A., Shazeer N., Parmar N. et al. Attention is all you need. In: Advances in neural information processing systems. 2017. P. 30.
- Bang Y., Cahyawijaya S., Lee N. et al. A multitask, multilingual, multimodal evaluation of chatGpt on reasoning, hallucination, and interactivity. arXiv preprint arXiv:2302.04023, 2023.
- Sridhara G., Mazumdar S. ChatGpt: A study on its utility for ubiquitous software engineering tasks. arXiv preprint arXiv:2305.16837, 2023.
- Tishchenko S.A., Shakhmuradyan M.A. Machine learning methods in small business: Content and management. Bulletin of the Plekhanov Russian University of Economics. 2019. No. 6 (108). (In Rus.)
- Mezentsev D.A. Применение искусственного интеллекта в управлении малым и средним бизнесом // Экономические и социально-гуманитарные исследования. 2023. № 3 (39). С. 102–107.
- Popova E.V. Application of artificial intelligence in small and medium business management. Economic and Social-Humanitarian Studies. 2023. No. 3 (39). Pp. 102–107. (In Rus.)
- Khan, A.A., Laghari, A.A., Li, P. et al. The collaborative role of blockchain, artificial intelligence, and industrial internet of things in digitalization of small and medium-size enterprises. Sci Rep. 2023. No. 13. P. 1656.
Supplementary files
