A market research on challenges influencing artificial intelligence adoption
Abstract
Although there are many theoretical references regarding the adoption of artificial intelligence, its practical challenges remain unknown. This article uses a market research aiming to identify the critical success factors to prepare for the artificial intelligence implementation, indicating the most appropriate strategies to adddress them. The results allow us to conclude that there are several challenges, the main ones being the lack of data infrastructure and trained people, and the lack of a better understanding of applications. Artificial intelligence, as well as other disruptive technologies, makes room for rethinking business models, not only improving existing processes, but also making it possible to see new opportunities. It is interesting to point out that, much more than a simple innovative project to improve processes and business, a succesful artificial intelligence implementation enables the creation of a new culture of interaction, experimentation, automation, analysis and prediction.
Keyword : artificial intelligence, adoption, SWOT analysis, GUT method
How to Cite
Schmiegelow, F., & Melo, F. C. L. (2023). A market research on challenges influencing artificial intelligence adoption. Business: Theory and Practice, 24(1), 250–257. https://doi.org/10.3846/btp.2023.17655
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Venkatesh, V. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Awa, H., Ukoha, O., & Igwe, S. (2017). Revisiting technology-organization-environment (T-O-E) theory for enriched applicability. The Bottom Line, 30(1), 2–22. https://doi.org/10.1108/BL-12-2016-0044
Baker, J. (2012). The technology–organization–environment framework. Integrated Series in Information Systems, 28. https://doi.org/10.1007/978-1-4419-6108-2_12
Benzaghta, M., Elwalda, A., Mousa, M., Erkan, I., & Rahman, M. (2021). SWOT analysis applications: An integrative literature review. Journal of Global Business Insights, 6(1), 55–73. https://doi.org/10.5038/2640-6489.6.1.1148
Borucka, B. (2018). SWOT & So What?: Make sense of your plans. Exertus Group.
Chalmers, D., MacKenzie, N., & CarterView, S. (2020). Artificial intelligence and entrepreneurship: Implications for venture creation in the fourth industrial revolution. Entrepreneurship Theory and Practice, 45(5). https://doi.org/10.1177/1042258720934581
Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press. https://doi.org/10.12987/9780300252392
Davis, F. (1989). User acceptance of information systems: The technology acceptance model (TAM). University of Michigan, School of Business Administration, Division of Research.
Daychoum, M. (2016). 40+16 Ferramentas e Técnicas de Gerenciamento. Brasport.
Fei, W., Zhang, Z., & Deng, Q. (2021). Universal pictures’ SWOT analysis and 4Ps & 4Cs marketing strategies in the post-COVID-19 era. In The Proceedings of the 2021 International Conference on Public Relations and Social Sciences. Atlantic Press. https://doi.org/10.2991/assehr.k.211020.205
Giannoccaro, I. (2013). Behavioral issues in operations management: New trends in design, management, and methodologies. Springer. https://doi.org/10.1007/978-1-4471-4878-4
Gudivada, V., Pankanti, S., & Zhang, Y. (2019). Cognitive computing systems: Their potential and the future. Computer, 52(5), 13–18. https://doi.org/10.1109/MC.2019.2904940
Hadwer, M., Tavana, M., Gillis, D., & Rezania, D. (2021). A systematic review of organizational factors impacting cloud-based technology adoption using technology-organization-environment framework. Internet of Things, 15. https://doi.org/10.1016/j.iot.2021.100407
Halverson, J., Maiti, A., & Stoner, K. (2021). Neural networks and quantum field theory. Machine Learning: Science and Technology, 2(3). https://doi.org/10.1088/2632-2153/abeca3
Lee, J. (2021). Diffusion of innovations. In Collection: Business 2021. Encyclopedia of sport management (pp. 137–138). Elgaronline. https://doi.org/10.4337/9781800883284.diffusion.of.innovations
Lee, K., & Qiufan, C. (2021). AI 2041: Ten visions for our future. Crown.
Mello, J., Pinto, J., Mello, B., & Ribeiro, A. (2022). SWOT analysis and GUT matrix for business management and problem solving: An application in a Brazilian case-study. Cuadernos de Gestión, 22(1), 81–93. https://doi.org/10.5295/cdg.211472jv
Meske, C., Bunde, E., Schneider, J., & Gersch, M. (2022). Explainable artificial intelligence: Objectives, stakeholders, and future research opportunities. Information Systems Management, 39(1), 53–63. https://doi.org/10.1080/10580530.2020.1849465
Minh, D., Wang, H., Li, Y., & Nguyen, T. (2022). Explainable artificial intelligence: A comprehensive review. Artificial Intelligence Review, 55, 3503–3568. https://doi.org/10.1007/s10462-021-10088-y
Moradi, M., & Nia, E. (2020). The impact of organizational factors based on technology-organization-environment (TOE) framework on practical levels and characteristics of audit analysis and internal audit performance. European Journal of Business and Management Research, 5(3). https://doi.org/10.24018/ejbmr.2020.5.3.265
Mueller, J. P., & Massaron, L. (2018). Artificial intelligence for dummies. For Dummies.
Paul, B., Marwala, T., & Doorsamy, W. (2020). The disruptive fourth industrial revolution: Technology, society and beyond. Springer.
Rogers, M. (1995). Diffusion of innovations. The Free Press.
Tamilmani, K., Rana, N., Wamba, S., & Dwivedi, R. (2021). The extended unified theory of acceptance and use of technology (UTAUT2): A systematic literature review and theory evaluation. International Journal of Information Management, 57. https://doi.org/10.1016/j.ijinfomgt.2020.102269
Tang, K., Chang, C., & Hwang, G. (2021). Trends in artificial intelligence-supported e-learning: A systematic review and co-citation network analysis (1998–2019). Interactive Learning Environments. https://doi.org/10.1080/10494820.2021.1875001
Tornatzky, L., Fleischer, M., & Chakrabarti, A. (1990). Processes of technological innovation. Lexington Books.
Venkatesh, V. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540