DIGITAL ENERGY IN THE AI ECONOMY: IMPROVEMENT OF THE QUALITY OF SERVICES WITH THE HELP OF MANAGEMENT INFORMATION SYSTEMS
In this paper, we studied the main functional directions of using AI technologies in the sphere of improvement of the quality of services based on management information systems of digital energy subjects.We demonstrated that AI technologies, compared to traditional software, allow achieving advantages in the speed of collection, processing, categorization, and analysis of databases and planning of the functioning of energy distribution networks.Also, these technologies allow solving issues connected with the problem of non-technical energy losses without excessive expenditures of time and labour, which are peculiar to non-automatized management of energy consumption control.We determined the issue of consumers' social perception of the use of digitalization and intellectualization in the sphere of possible violation of data confidentiality.Despite the existence of this problem, most consumers are oriented towards comfort from the uninterrupted supply of electric energy and, thus, are ready to use technologies.The goal of this research was to identify the features of digital energy in the conditions of the AI economy, which is connected with the improvement of the quality of services based on management information systems.The scientific novelty of this research lies in the systematization of functional capabilities of the integration of AI technologies in management information systems of energy distribution networks.
Authors
- Ilona Avlasenko (ORCID: https://orcid.org/0000-0002-3575-6989)
- Elima A. Israilova (ORCID: https://orcid.org/0000-0003-3844-2034)
- Oksana Savelyeva (ORCID: https://orcid.org/0000-0002-2897-1015)
- Shakhlo T. Ergasheva
- Atai E. Erkinbekov
Publication Details
- Journal
- Proceedings on Engineering Sciences
- Published
- 2025-06-30
- DOI
- https://doi.org/10.24874/pes07.02b.002
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00