Impact of Artificial Intelligence in Investment and Decision Making

Abstract

This study examines the impact of Artificial Intelligence (AI) on investment and financial decision-making. With the growing adoption of machine learning, predictive analytics, and natural language processing in financial markets, AI has transformed how investors analyse data, forecast trends, manage portfolios, and assess risk. Drawing on a systematic review of 30 research articles selected using the PRISMA framework, this paper explores five core dimensions: decision quality and accuracy, investor confidence and trust, risk management, portfolio optimisation, and ethical challenges. Findings confirm that AI significantly enhances decision accuracy in data-rich environments, strengthens risk management, and improves forecasting precision across asset classes. However, challenges including algorithmic opacity, cognitive bias amplification, systemic herding risk, and unresolved regulatory liability remain critical concerns. The study concludes that the optimal model is a hybrid human-AI approach where algorithmic tools augment but do not replace human judgment, ethical oversight, and contextual reasoning. Practical recommendations are provided for individual investors, financial institutions, regulators, and future researchers.

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