Evaluating the Impact of Digital Technologies on Business Financial Management: A Survey-Based Evidence

There is limited understanding of how AI affects the financial management perfor-mance of businesses when it comes to technology integration, cost, and cybersecurity. This study investigates the impact of digital technology applications, with a particular emphasis on artificial intelligence (AI) integration on financial management operations. This research aims to develop a cause-and-effect framework linking AI integration, operational efficiency, the cost of digital integration, and cybersecurity. Studies to date show the cost of investing in digital technology is high. Even though investment is a key factor in integrating AI into business processes, specifically in business financial management, it seems to be a hindrance for some businesses. Moreover, there is a lack of a concrete practical framework on which businesses could gain more clarity in terms of strategic decision-making when it comes to investments in digital infrastructure by considering the negative effects too. This research has deployed a quantitative research design based on a conceptual framework developed through a comprehensive literature review. Using quantitative research design, we collected data from 247 professionals across various industries through a Likert scale survey. The findings reveal that integration of AI in business financial management enhances operational efficiency and improves data management capabilities in general. However, this integration can also lead to increased costs and increased cyber threats. Although the conceptual model is empirically supported, the scope of the study is limited and it may coerce the generalizability of the findings. Variations in industry characteristics, firm size, organizational culture, managerial experience, leadership style, regulatory environments, and levels of digital maturity may influence the relationships among the four main study variables. Although this research shows that the control variables do not have a significant impact on the relationship between the main variables, future research may expand this framework by including other influencing parameters or moderators in order to improve the model comprehensiveness.