Abstract

This paper explores the integration of Artificial Intelligence (AI) into corporate finance decision-making, particularly in high-risk environments, with the aim of enhancing decision accuracy, speed, and risk management. The study presents an AI-augmented decision-making model designed to assist corporate finance executives in navigating volatile markets, unpredictable economic conditions, and complex risk landscapes. The research highlights how AI, through machine learning algorithms and predictive analytics, can analyze large datasets, forecast potential risks, and optimize financial strategies in real-time. Simulated high-risk scenarios demonstrate that the AI model outperforms traditional decision-making methods by improving risk-adjusted returns and reducing financial exposure to market volatility. While the model provides significant advantages in terms of decision-making efficiency, challenges such as data quality, algorithm complexity, and model interpretability remain. This paper provides actionable recommendations for integrating AI into corporate finance processes, emphasizing the need for executive training, data quality management, and system compatibility. The study also suggests avenues for future research, including refining AI algorithms, exploring industry-specific applications, and expanding the model to encompass diverse risk factors. Overall, the research demonstrates the transformative potential of AI in enhancing corporate finance decision-making and offers a framework for its successful implementation.