Economics of artificial intelligence: How AI is changing business models and the risks associated with it: An analytical study
Keywords:
Artificial Intelligence, Business Models, Economic Implications, AI-as-a-Service, Labor MarketsAbstract
This study explores the transformative impact of artificial intelligence (AI) on contemporary business models from an economic perspective. I argue that AI serves as a catalyst for significant economic change, reshaping industries by automating processes, creating new economic paradigms, and presenting unique challenges that necessitate strategic responses from businesses, policymakers, and economists. My findings reveal a threefold analysis: first, the transformation of traditional business models towards data-centric approaches; second, the emergence of new business models like AI-as-a-Service (AIaaS) that innovate service delivery; and third, the broader economic implications and challenges, including labor market shifts and regulatory concerns. Ultimately, this work underscores the importance of understanding AI's multifaceted impact on the economy and advocates for proactive measures to harness its potential while addressing its associated risks.
References
Acemoglu, D., & Restrepo, P. (2018). Artificial intelligence, automation, and work. In The economics of artificial intelligence: An agenda (pp. 197-236). University of Chicago Press.
Aghion, P., Jones, B. F., & Jones, C. I. (2017). Artificial intelligence and economic growth (Vol. 23928). Cambridge, MA: National Bureau of Economic Research.
Agrawal, A., Gans, J., & Goldfarb, A. (2019). Economic policy for artificial intelligence. Innovation policy and the economy, 19(1), 139-159.
Agrawal, A., Gans, J., & Goldfarb, A. (Eds.). (2019). The economics of artificial intelligence: an agenda. University of Chicago Press.
Akerkar, R. (2019). Artificial intelligence for business. Springer.
Bresciani, S., Huarng, K. H., Malhotra, A., & Ferraris, A. (2021). Digital transformation as a springboard for product, process and business model innovation. Journal of Business Research, 128, 204-210.
Brynjolfsson, E., Rock, D., & Syverson, C. (2019). Artificial intelligence and the modern productivity paradox. The economics of artificial intelligence: An agenda, 23, 23-57.
Burström, T., Parida, V., Lahti, T., & Wincent, J. (2021). AI-enabled business-model innovation and transformation in industrial ecosystems: A framework, model and outline for further research. Journal of Business Research, 127, 85-95.
Damioli, G., Van Roy, V., & Vertesy, D. (2021). The impact of artificial intelligence on labor productivity. Eurasian Business Review, 11, 1-25.
Di Vaio, A., Boccia, F., Landriani, L., & Palladino, R. (2020). Artificial intelligence in the agri-food system: Rethinking sustainable business models in the COVID-19 scenario. Sustainability, 12(12), 4851.
Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research, 121, 283-314.
Dirican, C. (2015). The impacts of robotics, artificial intelligence on business and economics. Procedia-Social and Behavioral Sciences, 195, 564-573.
Ehret, M., & Wirtz, J. (2017). Unlocking value from machines: business models and the industrial internet of things. Journal of Marketing Management, 33(1-2), 111-130.
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24(5), 1709-1734.
Ernst, E., Merola, R., & Samaan, D. (2019). Economics of artificial intelligence: Implications for the future of work. IZA Journal of Labor Policy, 9(1).
Garbuio, M., & Lin, N. (2019). Artificial intelligence as a growth engine for health care startups: Emerging business models. California Management Review, 61(2), 59-83.
Hamid, O. H. (2022, May). From model-centric to data-centric AI: A paradigm shift or rather a complementary approach?. In 2022 8th International Conference on Information Technology Trends (ITT) (pp. 196-199). IEEE.
Intelligence, A. (2016). Automation, and the Economy. Executive office of the President, 18-19.
Karunakaran, M., Krishnan, B., Shanthi, D., Raja, J. B., & Durai, B. S. K. Unleashing the Power of Industry 4.0: A Harmonious Blend of Data-Centric and Model-Centric AI. In Data-Centric Artificial Intelligence for Multidisciplinary Applications (pp. 40-54). Chapman and Hall/CRC.
Kotarba, M. (2018). Digital transformation of business models. Foundations of management, 10(1), 123-142.
Langley, D. J., van Doorn, J., Ng, I. C., Stieglitz, S., Lazovik, A., & Boonstra, A. (2021). The Internet of Everything: Smart things and their impact on business models. Journal of Business Research, 122, 853-863.
Marwala, T., & Hurwitz, E. (2017). Artificial intelligence and economic theory: skynet in the market (Vol. 1). Cham: Springer International Publishing.
Patil, S. D., Mahajan, R. A., & Sakhare, N. Advancements in Data-Centric AI Foundations, Ethics, and Emerging Technology. In Data-Centric Artificial Intelligence for Multidisciplinary Applications (pp. 3-26). Chapman and Hall/CRC.
Rachinger, M., Rauter, R., Müller, C., Vorraber, W., & Schirgi, E. (2019). Digitalization and its influence on business model innovation. Journal of manufacturing technology management, 30(8), 1143-1160.
Rana, N. P., Chatterjee, S., Dwivedi, Y. K., & Akter, S. (2022). Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems, 31(3), 364-387.
Ranta, V., Aarikka-Stenroos, L., & Väisänen, J. M. (2021). Digital technologies catalyzing business model innovation for circular economy—Multiple case study. Resources, conservation and recycling, 164, 105155.
Reim, W., Åström, J., & Eriksson, O. (2020). Implementation of artificial intelligence (AI): a roadmap for business model innovation. Ai, 1(2), 11.
Semenov, A., Yepifanova, I., & Kajanová, J. Data-Centric Business and Applications.
Sestino, A., & De Mauro, A. (2022). Leveraging artificial intelligence in business: Implications, applications and methods. Technology Analysis & Strategic Management, 34(1), 16-29.
Singh, P. (2023). Systematic review of data-centric approaches in artificial intelligence and machine learning. Data Science and Management, 6(3), 144-157.
Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2019). Impact of artificial intelligence on businesses: from research, innovation, market deployment to future shifts in business models. arXiv preprint arXiv:1905.02092.
Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2020). Artificial intelligence in business: from research and innovation to market deployment. Procedia Computer Science, 167, 2200-2210.
Stanciu, A., Titu, A. M., & Deac-Şuteu, D. V. (2021, July). Driving digital transformation of knowledge-based organizations through artificial intelligence enabled data centric, consumption based, As-a-service models. In 2021 13th international conference on electronics, computers and artificial intelligence (ECAI) (pp. 1-8). IEEE.
Tschang, F. T., & Almirall, E. (2021). Artificial intelligence as augmenting automation: Implications for employment. Academy of Management Perspectives, 35(4), 642-659.
Varian, H. R. (2018). Artificial intelligence, economics, and industrial organization (Vol. 24839). Cambridge, MA, USA:: National Bureau of Economic Research.
Wamba-Taguimdje, S. L., Wamba, S. F., Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business process management journal, 26(7), 1893-1924.
Wright, S. A., & Schultz, A. E. (2018). The rising tide of artificial intelligence and business automation: Developing an ethical framework. Business Horizons, 61(6), 823-832.
Published
How to Cite
Issue
Section
Copyright (c) 2023 Ben Moussa Bachir, Zeghdi Adel, Necir Ahmed

This work is licensed under a Creative Commons Attribution 4.0 International License.
Allows users to: distribute and copy the article; create extracts, abstracts, and other revised versions, adaptations or derivative works of or from an article (such as a translation); include in a collective work (such as an anthology); and text or data mine the article. These uses are permitted even for commercial purposes, provided the user: gives appropriate credit to the author(s) (with a link to the formal publication through the relevant URL ID); includes a link to the license; indicates if changes were made; and does not represent the author(s) as endorsing the adaptation of the article or modify the article in such a way as to damage the authors' honor or reputation. CC BY



