Artificial intelligence in business: Challenges and development prospects (foresight 2024)

Aim. The work aimed to identify the main challenges and prospects for the implementation of artificial intelligence (hereinafter referred to as AI) in management processes, taking into account technological, social and economic factors influencing the efficiency and sustainability of business. Objectives. The work seeks to study the key trends in the integration of AI into business; to assess the impact of AI on decision-making, process automation, and human capital development; to identify potential risks, including cybersecurity and ethical issues; to propose a strategic roadmap for the implementation of AI to improve the competitiveness of enterprises. Methods. The authors used foresight analysis to identify and predict the development of key trends. The empirical analysis was based on the data obtained during the foresight session held on September 16, 2024, at the Southern Federal University. The work employed the methods of expert survey, scenario analysis, and semantic modeling. Results. Four key factors determining the success of AI implementation were identified, namely technology and innovation, human capital, financing and partnership, risks and ethical aspects. It was revealed that the dynamics of growth in the number of patents and commercial solutions in the field of AI indicate the strategic importance of the technology for business. Key challenges were highlighted, namely the need to invest in personnel training, the establishment of ethical standards, and strengthening of regulatory framework. A roadmap for the implementation of AI in management processes has been developed, including the stages of preparation, pilot implementation, scaling, and optimization. Conclusions. The study of the processes of implementing AI in business demonstrates the significant potential of the technology for improving the efficiency of management and the competitiveness of enterprises. However, successful integration requires an integrated approach that includes the development of human capital, regulation of legal aspects and consideration of ethical risks.

Authors

Institutions

Publication Details

Journal
Economics and Management
Published
2025-03-25
DOI
https://doi.org/10.35854/1998-1627-2025-2-179-195
Citations
2
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
4.45
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence in business: Challenges and development prospects (foresight 2024)

Anton D. Murzin, S. V. Savin
2 citations
Economics and Management
Innovation and Knowledge Management
4.45
article

Artificial intelligence in business: Challenges and development prospects (foresight 2024)

Anton D. Murzin, S. V. Savin
article en
2 citations

Abstract

Aim. The work aimed to identify the main challenges and prospects for the implementation of artificial intelligence (hereinafter referred to as AI) in management processes, taking into account technological, social and economic factors influencing the efficiency and sustainability of business. Objectives. The work seeks to study the key trends in the integration of AI into business; to assess the impact of AI on decision-making, process automation, and human capital development; to identify potential risks, including cybersecurity and ethical issues; to propose a strategic roadmap for the implementation of AI to improve the competitiveness of enterprises. Methods. The authors used foresight analysis to identify and predict the development of key trends. The empirical analysis was based on the data obtained during the foresight session held on September 16, 2024, at the Southern Federal University. The work employed the methods of expert survey, scenario analysis, and semantic modeling. Results. Four key factors determining the success of AI implementation were identified, namely technology and innovation, human capital, financing and partnership, risks and ethical aspects. It was revealed that the dynamics of growth in the number of patents and commercial solutions in the field of AI indicate the strategic importance of the technology for business. Key challenges were highlighted, namely the need to invest in personnel training, the establishment of ethical standards, and strengthening of regulatory framework. A roadmap for the implementation of AI in management processes has been developed, including the stages of preparation, pilot implementation, scaling, and optimization. Conclusions. The study of the processes of implementing AI in business demonstrates the significant potential of the technology for improving the efficiency of management and the competitiveness of enterprises. However, successful integration requires an integrated approach that includes the development of human capital, regulation of legal aspects and consideration of ethical risks.

Economics and ManagementVol. 31(2)
Southern Federal University (RU), Institute of Service and Entrepreneurship of DGTU (RU), Don State Technical University (RU)
Openalex Percentile: Top 7%
Innovation and Knowledge Management
4.45
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.