Artificial intelligence (AI) drives in financial agents have become a critical component of contemporary business decisions and risk-management framework transformer. The current study examines the potential to use AI agents, such as robo-advisors, algorithmic trading bots, predictive analytics systems, and others, to make a quantitative contribution to the profits and risk management of corporate organizations. It is founded on a secondary quantitative study, which generalizes the outcome of the research of twenty-two secondary and institutional studies published during the period of 2019-2025. The experience shows real efficiency improvements (10-15 percent), accuracy of decision-making (8-11 percent), and risk reduction (up to 12 percent) and the limited nature of governance shortcomings that are yet to be resolved. Results indicate that AI enhances the accuracy of analysis results and operational consistency but requires outstanding standards of ethical controls and disclosure to minimize the emerging compliance and algorithm-bias risks. The analysis concludes that the best solution to the future of sustainable financial innovation is the combination of human strategic control and the computing capabilities of AI, a hybrid intelligence model.
Aslam et al. (Tue,) studied this question.
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