Is It Worth the Hype? Influence of Artificial Intelligence Efforts on Key Financial Company Metrics
DOI:
https://doi.org/10.12775/CJFA.2023.010Keywords
Artificial Intelligence, company performance, company valueAbstract
Artificial Intelligence poses a consortium of multiple digital technologies able to perform tasks which were thought about that they can only be done by humans. To do so, it applies complex learning and decision-making processes based on analysis of structured and unstructured data. Currently, AI is assumed to have massive benefits in the areas of efficiency and performance of companies, although the impact on financial key performance indicators (KPI) is still unexplored. The underlying thesis of this research is that the financial impact of AI can already be seen in practice. The research question is whether there is an impact of company-driven AI efforts on financial KPI, like the return on assets (ROA) and the market capitalization.
To obtain the intended results, a theoretical and empirical analysis was chosen as particular approach. Firstly, the existing scientific research is examined regarding already measurable financial impacts of digital technologies. In a second step, a regression model for panel data will be applied on a dataset containing financial data of the forty biggest German companies and their respective AI effort per year as a binary variable over a time period of seven years.
As a result, a financial influence of AI cannot be verified yet on a statistically significant level. Despite of this, an increasing number of AI efforts over the last years can be confirmed.
References
Akter, S., Michael, K., Uddin, M.R., McCarthy, G., & Rahman, M. (2022). Transforming business using digital innovations: The application of AI, blockchain, cloud and data analytics. Annals of Operations Research, 308(1), 7-39. https://doi.org/10.1007/s10479-020-03620-w.
Ammanath, B., Hupfer, S., & Jarvis, D. (2020). Deloitte’s State of AI in the Enterprise, 3rd Edition, https://www2.deloitte.com/cn/en/pages/about-deloitte/articles/state-of-ai-in-the-enterprise-3rd-edition.html (accessed 30.05.2023).
Anwar, M., Khan, S.Z., & Shah, S.Z.A. (2018). Big Data Capabilities and Firm's Performance: A Mediating Role of Competitive Advantage. Journal of Information & Knowledge Management, 17(4), 1-28. https://doi.org/10.1142/S0219649218500454.
Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450.
Bharadwaj, A.S., Bharadwaj, S.G., & Konsynski, B.R. (1999). Information Technology Effects on Firm Performance as Measured by Tobin’s q. Management Science, 45(7), 1008-1024. https://doi.org/10.1287/mnsc.45.7.1008.
Breusch, T.S., & Pagan, A.R. (1979). A Simple Test for Heteroscedasticity and Random Coefficient Variation. Econometrica, 47(5), 1287-1294. https://doi.org/10.2307/1911963.
Brynjolfsson, E., & Hitt, L. (1996). Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending. Management Science, 42(4), 541-558.
Brynjolfsson, E., Rock, D., & Syverson, C. (2017). Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics. NBER Working Paper No. 24001.
Chen, W., & Srinivasan, S. (2019). Going Digital: Implications for Firm Value and Performance. Harvard Business School Working Paper 19-117.
Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial Intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383.
Greene, W.H. (2002). Econometric Analysis. New Jersey: Prentice Hall International.
Karahanna, E., & Preston, D.S. (2013). The Effect of Social Capital of the Relationship Between the CIO and Top Management Team on Firm Performance. Journal of Management Information Systems, 30(1), 15-56.
Liang, K.-Y., & Zeger, S.L. (1986). Longitudinal Data Analysis Using Generalized Linear Models. Biometrika, 73(1), 13-22. https://doi.org/10.2307/2336267.
Tambe, P. (2014). Big Data Investment, Skills, and Firm Value. Management Science, 60(6), 1452-1469.
O’Reilly, C.A., Caldwell, D.F., Chatman J.A., & Doerr, B. (2014). The Promise and Problems of Organizational Culture. Group & Organization Management, 39(6), 595-625. https://doi.org/10.1177/10596011145507.
Reim, W., Åström, J., & Eriksson, O. (2020). Implementation of Artificial Intelligence (AI): A Roadmap for Business Model Innovation. AI, 1, 180-191. https://doi.org/10.3390/ai1020011.
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.
Wang, P. (2019). On Defining Artificial Intelligence. Journal of Artificial General Intelligence, 10(2), 1-37. https://doi.org/10.2478/jagi-2019-0002.
Zeileis, A. (2004). Econometric Computing with HC and HAC Covariance Matrix Estimators. Journal of Statistical Software, 11(10), 1-21. https://dx.doi.org/10.18637/jss.v011.i10.
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