Subject. The study investigates elements of business models of companies in the sphere of educational technologies. Objectives. The purpose is to determine how artificial intelligence affects product innovation, business processes, efficiency, customer relationships, and strategic development in the context of business models. Methods. The study draws on general scientific methods of cognition. Results. Using the Likert scale questionnaire, we collected quantitative data from managers of companies operating in the sphere under consideration. The results show the significant impact of artificial intelligence on data processing, educational process effectiveness, content creation speed, and changing roles and competencies. The findings emphasize the role of artificial intelligence in educational process optimization, automation of administrative tasks, and predictive analytics for making informed decisions. However, the impact of this technology on revenue streams and scalability remains minimal. It is essential to develop artificial intelligence-based tools, given ethical aspects, data confidentiality, and compliance with educational standards. Conclusions. The study provides insight into strategic changes in educational technologies due to the integration of artificial intelligence, and contributes to a broader discussion about the role of technologies in education.
Keywords: artificial intelligence, business model, educational technologies, innovation in education, digital transformation
References:
Zawacki-Richter O., Marín V.I, Bond M., Gouverneur F. Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 2019, vol. 16, no. 39, pp. 1–27. URL: Link
Bozkurt A. Educational Technology Research Patterns in the Realm of the Digital Knowledge Age. Journal of Interactive Media in Education, 2020, vol. 2020, iss. 1, pp. 1–17. URL: Link
Regan P.M., Khwaja E.N. Mapping the political economy of education technology: A networks perspective. Policy Futures in Education, 2019, vol. 17, iss. 8, pp. 1000–1023. URL: Link
Jaehun Lee, Taewon Suh, Roy D., Baucus M. Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence. Journal of Open Innovation: Technology, Market, and Complexity, 2019, vol. 5, iss. 3. URL: Link
Acemoglu D., Restrepo P. The wrong kind of AI? Artificial intelligence and the future of labour demand. Cambridge Journal of Regions, Economy and Society, 2019, vol. 13, iss. 1, pp. 25–35. URL: Link
Kinkel S., Baumgartner M., Cherubini E. Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies. Technovation, 2021, vol. 110, no. 102375. URL: Link
Renz A., Hilbig R. Prerequisites for artificial intelligence in further education: Identification of drivers, barriers, and business models of educational technology companies. International Journal of Educational Technology in Higher Education, 2020, vol. 17, no. 14. URL: Link
Briggs B. Managing Relationships. In: The Strategic Treasurer: A Partnership for Corporate Growth. Ed. by C.A. Jeffery. John Wiley & Sons, Inc., 2012. URL: Link
Snijders I., Wijnia L., Rikers R.M.J.P., Loyens S.M.M. Building bridges in higher education: Student-faculty relationship quality, student engagement, and student loyalty. International Journal of Educational Research, 2020, vol. 100, no. 101538. URL: Link
Taddeo M., Floridi L. How AI can be a force for good. Science, 2018, vol. 361, no. 6404, pp. 751–752. URL: Link
Holmes W., Porayska-Pomsta K., Holstein K. et al. Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 2022, vol. 32, pp. 504–526. URL: Link
Prentice C., Nguyen M. Engaging and retaining customers with AI and employee service. Journal of Retailing and Consumer Services, 2020, vol. 56, no. 102186. URL: Link
Iwendi C., Bashir A., Peshkar A. et al. COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm. Frontiers in Public Health, 2020, vol. 8. URL: Link
Kumar V., Rajan B., Venkatesan R., Lecinski J. Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing. California Management Review, 2019, vol. 61, iss. 4, pp. 135–155. URL: Link
Van Gog T., Paas F. Instructional Efficiency: Revisiting the Original Construct in Educational Research. Educational Psychologist, 2008, vol. 43, iss. 1, pp. 16–26. URL: Link
Simmons J., Alexander L. The Determinants of School Achievement in Developing Countries: A Review of the Research. Economic Development and Cultural Change, 1978, vol. 26, no. 2, pp. 341–357. URL: Link
Rana N.P., Chatterjee S., Dwivedi Y.K., Akter S. Understanding dark side of artificial intelligence (AI) integrated business analytics: Assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems, 2021, vol. 31, iss. 3, pp. 364–387. URL: Link
Yongbin Zhang, Ronghua Liang, Ziyuan Shi, Huiling Ma. The Design and Implementation of a Process-Driven Higher Educational Administrative System. IERI Procedia, 2012, vol. 2, pp. 176–182. URL: Link
Sjödin D., Parida V., Palmié M., Wincent J. How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 2021, vol. 134, pp. 574–587. URL: Link
Soni N., Sharma E.K., Singh N., Kapoor A. Impact of Artificial Intelligence on Businesses: From Research, Innovation, Market Deployment to Future Shifts in Business Models. ArXiv, 2019. URL: Link
Pecanin E., Spalevic P., Mekic E., Jovic S., Milovanovic I. E-learning engineers based on constructive and multidisciplinary approach. Computer Applications in Engineering Education, 2019, vol. 27, iss. 6, pp. 1544–1554. URL: Link
Xinyun Hu, Yelland N. Changing Learning Ecologies in Early Childhood Teacher Education: From Technology to STEM Learning. Beijing International Review of Education, 2019. URL: Link
Segarra G. The advanced information technology innovation roadmap. Computers in Industry, 1999, vol. 40, iss. 2-3, pp. 185–195. URL: Link00023-8
Ming-Hui Huang, Rust R.T. Artificial Intelligence in Service. Journal of Service Research, 2018, vol. 21, iss. 2, pp. 155–172. URL: Link
Yinying Wang. When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale. Studies in Educational Evaluation, 2020, vol. 69, no. 100872. URL: Link
Van Hoorebeek M., Marson J. Teaching and Technology Transfer as Alternative Revenue Streams: A Primer on the Potential Legal Implications for UK Universities. International Journal of Educational Management, 2005, vol. 19, no. 1, pp. 36–47. URL: Link
Monger R.F. AI Applications: What's Their Competitive Potential? Information Systems Management, 1988, vol. 5, iss. 3, pp. 19–25. URL: Link
Yingzi Xu, Chih-Hui Shieh, Van Esch P., I-Ling Ling. AI Customer Service: Task Complexity, Problem-Solving Ability, and Usage Intention. Australasian Marketing Journal, 2020, vol. 28, iss. 4, pp. 189–199. URL: Link
Li Gao, Gang Li, Fusheng Tsai et al. The impact of artificial intelligence stimuli on customer engagement and value co-creation: The moderating role of customer ability readiness. Journal of Research in Interactive Marketing, 2022, vol. 17, iss. 2, pp. 317–333. URL: Link
Guangming Cao, Yanqing Duan, Edwards J.S., Dwivedi Y.K. Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation, 2021, vol. 106, no. 102312. URL: Link
Howard S.K., Thompson K. Seeing the system: Dynamics and complexity of technology integration in secondary schools. Education and Information Technologies, 2016, vol. 21, pp. 1877–1894. URL: Link
Mishra S., Tripathi A. AI business model: An integrative business approach. Journal of Innovation and Entrepreneurship, 2021, vol. 10, iss. 18, pp. 1–21. URL: Link
