Most companies in a modern digitalized economy are resorting to artificial intelligence (AI) to assist them in making strategic and financial decisions. Yet these are choices that are deeply rooted in behavioral and psychological factors and this is risk perception and cognitive bias. This article, entitled Entrepreneurial Risk Perception and AI-Driven Financial Decision Making: A Behavioral Finance Perspective, inculcates the theory of behavioral finance with the use of AI to interpret, base, and take action on algorithmic intelligence. This study is based on Prospect Theory, Bounded Rationality, Signaling Theory, Expectancy-Violation Theory, Emotional Contagion, and the Algorithmic Bias-Trust Framework to form an integrative model that risk perception is an intervening cognitive process between entrepreneurial biases and AI adoption. Theoretical synthesis: AI increases the accuracy of prediction and decreases information asymmetry because it combines with cognitive and emotional filters of entrepreneurs. Theoretical implications suggest that the entrepreneurs must combine human intuition and algorithmic intelligence, undergo life long behavioral-finance education, and establish the openness of explainable AI in order to influence the rational, inclusive and ethical decision-making. The paper concludes with a statement that the future of entrepreneurial finance will be defined by the co-evolution of human judgement and machine learning, in the era where technology will help but never replace human knowledge and the sense of morals.