ШТУЧНИЙ ІНТЕЛЕКТ У ФІНАНСОВОМУ СЕКТОРІ: ВІД «МАШИНИ ПРОГНОЗУВАННЯ» ДО АГЕНТНИХ СИСТЕМ, ARTIFICIAL INTELLIGENCE IN THE FINANCIAL SECTOR: FROM "PREDICTION MACHINE" TO AGENTIC SYSTEMS

<jats:p>This article examines the transformative impact of artificial intelligence on the financial system in Ukraine nowadays during the war. The study approaches AI as a general-purpose technology that lowers the cost of prediction and gradually reorganises how financial institutions structure their operations. What distinguishes AI from conventional production inputs is its near-zero cost of replication – which means that financial institutions can scale efficiency without proportional increases in resources, fundamentally altering the economics of the sector. The article analyses the core functions of intelligent systems, covering the automation of routine processes, analytics of large and unstructured data sets, predictive modelling, and risk management. Particular attention is given to the emergence of agentic AI – a new generation of systems capable of independently pursuing goals, planning sequences of actions, and completing complex tasks with minimal human involvement. So, this represents a qualitative shift in the nature of automation itself, and it is precisely agentic systems that open the prospect of fully autonomous management of entire business processes within financial institutions. Additinaly, the study maps the practical application of AI across different segments of the financial market: in banking, through the personalisation of services and credit assessments based on non-traditional data sources; in investment management, through algorithmic trading and market sentiment analysis; in insurance, through faster claims settlement and more effective fraud detection. The Ukrainian experience is highlighted through the cases of PrivatBank and Monobank, whose AI-driven digital banking models have earned international recognition. However, the macroeconomic risks of automation are also addressed, including labour-market disruption and systemic instability from correlated algorithmic behaviour. The article concludes by arguing for a robust regulatory framework aligned with the EU AI Act to ensure responsible deployment of algorithmic systems in finance.</jats:p>