Artificial intelligence: Financial management under pressure of transformative technology

Artificial intelligence: Financial management under pressure of transformative technology

Článek WoS

The paper examines the growing role of artificial intelligence (AI) in corporate financial management and its transformative impact on organizational decision-making and financial performance. The authors highlight that the integration of AI technologies—such as machine learning, big data analytics, and robotic process automation—enables companies to improve financial forecasting, automate routine administrative tasks, and enhance risk management processes. By analysing large volumes of historical and real-time data, AI systems support more accurate predictions of revenues, costs, and cash flows, thereby strengthening strategic planning and improving the responsiveness of firms to changing market conditions. At the same time, AI-driven automation increases operational efficiency, reduces human errors, and allows employees to focus on higher-value analytical and strategic activities. The study also emphasizes the growing importance of AI-based decision support systems, which assist managers in optimizing resource allocation, identifying cost-saving opportunities, and evaluating alternative strategic scenarios. However, the adoption of AI in financial management is accompanied by significant challenges, including data quality and integration issues, limited transparency and explainability of algorithms, and ethical and regulatory concerns related to privacy, bias, and accountability. The authors argue that future research should focus on improving explainable AI models, developing advanced data architectures, and integrating AI solutions with sustainability and corporate responsibility objectives. Effective implementation of AI in financial management requires not only technological development but also strategic organizational adaptation that balances innovation with ethical and regulatory requirements.

The paper examines the growing role of artificial intelligence (AI) in corporate financial management and its transformative impact on organizational decision-making and financial performance. The authors highlight that the integration of AI technologies—such as machine learning, big data analytics, and robotic process automation—enables companies to improve financial forecasting, automate routine administrative tasks, and enhance risk management processes. By analysing large volumes of historical and real-time data, AI systems support more accurate predictions of revenues, costs, and cash flows, thereby strengthening strategic planning and improving the responsiveness of firms to changing market conditions. At the same time, AI-driven automation increases operational efficiency, reduces human errors, and allows employees to focus on higher-value analytical and strategic activities. The study also emphasizes the growing importance of AI-based decision support systems, which assist managers in optimizing resource allocation, identifying cost-saving opportunities, and evaluating alternative strategic scenarios. However, the adoption of AI in financial management is accompanied by significant challenges, including data quality and integration issues, limited transparency and explainability of algorithms, and ethical and regulatory concerns related to privacy, bias, and accountability. The authors argue that future research should focus on improving explainable AI models, developing advanced data architectures, and integrating AI solutions with sustainability and corporate responsibility objectives. Effective implementation of AI in financial management requires not only technological development but also strategic organizational adaptation that balances innovation with ethical and regulatory requirements.

Artificial intelligence; Financial management; Machine learning; Decision support systems; Corporate financial performance

Artificial intelligence; Financial management; Machine learning; Decision support systems; Corporate financial performance

BALCERZAK, A.; VALASKOVA, K.

2026

01.12.2024

Inst Economic Research-Poland

Equilibrium

19

4

Polská republika

1127

1137

11

https://economic-policy.pl/index.php/eq/article/view/3394/2395