Economic Bulletin of the National Mining University

 

IssuesSectionsAuthorsKeywords

Article

Issue:2023 №3 (83)
Section:Marketing
UDK:030
DOI:https://doi.org/10.33271/ebdut/83.107
Article language:English
Pages:107-111
Title:Business models and opportunities of artifical intelligence
Author:Mshvidobadze T. I., Gori State University
Annotation:Methods. The theoretical and methodological approaches presented in the publications of foreign authors on the problems of artificial intelligence and its use in business processes served as the information base of the research. The methods included analysis of case studies and surveys, expert interviews, as well as a systematic approach and modeling. Results. The article examines the impact of artificial intelligence on business operations. The capabilities of artificial intelligence to solve economic problems of business structures are characterized and the challenges faced by companies that use it in the course of their business activities are demonstrated. Research results show that artificial intelligence has the potential to significantly improve business operations, in particular, increase labor productivity, save resources and improve the process of management decision-making. The introduction of artificial intelligence through the coordination of digital data has been shown to help incrementally improve business. Novelty. The benefit of the use of artificial intelligence (AI) and machine learning (ML) technology in the innovation and dynamics of the business model of the corporate digital platform is highlighted. Practical value. Enterprises that effectively use artificial intelligence can revolutionize exciting new digital business models and practices that empower them to transform the global economic business landscape. 
Keywords:Artificial intelligence, Business model, Opportunities, Machine learning (ML) algorithms, Hologram technology
File of the article:EV20233_107-111.pdf
Literature:
  • 1. Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence. Harvard Business Review, 95(1), pp. 54-62;
  • 2. Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-powered organization. Harvard Business Review, 97(4), pp. 62-73;
  • 3. Alhashmi, S. F., Salloum, S. A., & Abdallah, S. (2019, October). Critical success factors for implementing artificial intelligence (AI) projects in Dubai government United Arab Emirates (UAE) health sector: Applying the extended technology acceptance model (TAM). In International Conference on Advanced Intelligent Systems and Informatics, (pp. 393-405). Springer;
  • 4. González-González, I., & Jiménez-Zarco, A. I. (2014). The MOOC phenomenon: The current situation and an alternative business model. In eLearn Center Research Paper Series, (pp. 26-33);
  • 5. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2017). Artificial intelligence: The next digital frontier?. McKinsey Global Institute, p.19;
  • 6. Armour, J., & Sako, M. (2020). AI-enabled business models in legal services: from traditional law firms to next-generation law companies? Journal of Professions and Organization, 7(1), pp. 27-46;
  • 7. Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-powered organization. Harvard Business Review, 97(4), pp. 62-73.
  • 8. Ferrario, A., Loi, M. & Viganò, E (2020). In AI We Trust Incrementally: a Multi-layer Model of Trust to Analyze Human-Artificial Intelligence Interactions. Philos. Technol. 33, pp. 523-539. https://doi.org/10.1007/s13347-019-00378-3.
  • 9. Morley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2019). From what to how. An overview of AI ethics tools, methods and research to translate principles into practices. P.76. https://doi.org/10.2139/ssrn.3830348
  • 10. León, M. C., Nieto-Hipólito, J. I., Garibaldi- Beltrán, J., Amaya-Parra, G., Luque-Morales, P., Magaña- Espinoza, P., & Aguilar-Velazco, J. (2016). Designing a model of a digital ecosystem for healthcare and wellness using the business model canvas. Journal of medical systems, 40(6), p.144. https://doi.org/10.1007/s10916-016-0488-3
  • 11. Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumer’s acceptance of artificially intelligence (AI) device use in service delivery. International Journal of Information Management, 49, pp. 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008
  • 12. Ghoreishi, M., & Happonen, A. (2020). New promises AI brings into circular economy accelerated product design: A review on supporting literature. In E3S Web of Conferences, (vol. 158, p.602). EDP Sciences;
  • 13. Samsung White Paper (July 14, 2020):https://research.samsung.com/next-generation- communications ; pp.234.
  • 14. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world: Don't be fooled by the hype. Harvard Business Review, 96(1), pp. 108-116.
  • 15. Gentsch, P. (2019). AI Business: Framework and maturity model. In AI in Marketing, Sales and Service, (pp. 27-78). Palgrave Macmillan. https://doi.org/10.1007/978-3-319-89957-2_316.
  • 16. Chan, L., Morgan, I., Simon, H., Alshabanat, F., Ober, D., Gentry, J., … Cao, R. (2019, June). Survey of AI in cybersecurity for information technology management. In 2019 IEEE Technology & Engineering Management Conference (TEMSCON), (pp. 1-8). IEEE;
  • 17. Daugherty, P. R., & Wilson, H. J. (2018). Human+ machine: Reimagining work in the age of AI. Harvard Business Press, p.278.