The research shows that AI can serve as a decision-support system that helps managers process financial information, identify patterns, generate predictions, and obtain recommendations while keeping strategic decisions under human control.
This approach is known as Human-Centered Artificial Intelligence. Unlike systems designed primarily for automation, HCAI emphasizes collaboration between people and intelligent technologies. Transparency, explainability, accountability, and continuous human oversight are considered important elements of responsible AI implementation.
AI Is Changing Corporate Financial Management
Artificial intelligence has become an increasingly important technology in financial management. Machine learning, predictive analytics, and generative AI can help companies improve forecasting, automate financial reporting, optimize budgets, and strengthen risk management.
However, greater reliance on AI also creates challenges. Excessive dependence on algorithmic recommendations can raise concerns about transparency, accountability, ethics, and trust. For this reason, combining technological capabilities with human expertise has become increasingly important in financial decision-making.
The issue is particularly relevant in Indonesia, where AI adoption has expanded across sectors such as banking, insurance, and financial technology. Despite the potential benefits, organizations still face challenges involving data readiness, employee capabilities, governance, and ethical AI implementation.
Study Involved 120 Financial Managers and Executives
Margarita Ekadjaja used a quantitative survey involving 120 financial managers and executives from Indonesian companies that had adopted AI-based financial management systems. The respondents included financial managers, chief financial officers, accounting managers, finance directors, and other financial executives involved in financial planning and decision-making.
Participants were selected based on their professional experience and involvement with AI-supported financial systems. They were required to hold managerial positions in finance or accounting, have at least one year of experience using AI-supported financial systems, and actively participate in financial decision-making.
Data were collected through an online structured questionnaire using a five-point scale ranging from strongly disagree to strongly agree. Before the main survey, the questionnaire was reviewed by academics and practitioners and tested with 30 respondents to ensure that the questions were clear and relevant. The final data were analyzed using SmartPLS 4.
Among the respondents, 38.3 percent were aged 35–44, making this the largest age group. In terms of education, 58.3 percent held bachelor's degrees, 37.5 percent held master's degrees, and 4.2 percent held doctoral degrees. Regarding professional experience, 42.5 percent had 6–10 years of experience, while 33.3 percent had more than 10 years.
Human-Centered AI Strengthens Financial Decision Quality
One of the strongest findings is the positive and statistically significant relationship between HCAI adoption and financial decision-making quality. The relationship produced a coefficient of 0.788, with a t-value of 16.524 and a p-value below 0.001.
In the study, financial decision-making quality refers to decisions that are accurate, timely, objective, and aligned with organizational goals. AI can support this process by rapidly processing large amounts of financial information, generating predictive insights, and providing recommendations for managers to evaluate.
The finding suggests that the value of AI does not come solely from automation. Its strategic value can increase when information generated by AI is combined with managerial knowledge, professional experience, and human judgment.
Better Financial Decisions Support Sustainable Performance
The study also found that financial decision-making quality has a positive and significant effect on sustainable corporate performance. The coefficient was 0.531, with a t-value of 7.184 and a p-value below 0.001.
This means companies that make accurate, timely, and evidence-based financial decisions are more likely to allocate resources effectively, manage financial risks proactively, and strengthen strategic planning.
In the study, sustainable corporate performance extends beyond conventional financial results. It refers to a company's ability to achieve long-term success while balancing economic, environmental, and social objectives.
HCAI Also Directly Supports Sustainable Corporate Performance
HCAI adoption was also found to have a direct and significant positive effect on sustainable corporate performance. The coefficient was 0.296, with a t-value of 3.541 and a p-value below 0.001.
The research model further showed that HCAI adoption explained 62.1 percent of the variation in financial decision-making quality. Meanwhile, HCAI adoption and financial decision-making quality together explained 68.7 percent of the variation in sustainable corporate performance.
An important finding emerged from the mediation analysis. Financial decision-making quality significantly mediated the relationship between HCAI adoption and sustainable corporate performance, with an indirect coefficient of 0.418, a t-value of 6.623, and a p-value below 0.001. Because both the direct and indirect effects were significant, the relationship was classified as partial mediation.
In practical terms, human-centered AI can contribute to corporate sustainability through two pathways: directly supporting organizational performance and indirectly improving the quality of financial decisions.
Companies Need to Combine AI With Human Expertise
For businesses, the findings carry an important message: investing in AI should not stop at purchasing technology. Companies also need to strengthen employee capabilities, establish AI governance, ensure that AI systems can provide understandable outputs, and maintain human oversight.
Ekadjaja's findings indicate that AI should function as a decision-support tool. Predictive analytics, real-time financial information, and intelligent recommendations can assist managers in budgeting, investment evaluation, financial planning, and risk management, while strategic responsibility remains with human decision-makers.
For companies undergoing digital transformation, the findings suggest that successful AI adoption depends on the combination of technology, human capabilities, and organizational governance. Workforce development therefore needs to progress alongside the development and implementation of AI systems.
The study also acknowledges several limitations. Because the research used a cross-sectional design, it could not capture changes in AI adoption and corporate performance over time. In addition, the sample consisted of 120 financial managers and executives from Indonesian companies, meaning the findings may not be fully generalizable to other industries or countries.
Author Profile
Margarita Ekadjaja is an academic affiliated with Tarumanagara University, Indonesia. Her research in this article focuses on artificial intelligence, financial management, financial decision-making quality, and sustainable corporate performance. The study highlights the importance of keeping human expertise and managerial oversight at the center of AI-supported financial management.
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