This study conducts a systematic literature review to explore the integration of artificial intelligence into financial decision-making, particularly in the context of investment strategies. Drawing from 52 peer-reviewed journal articles published between 2018 and 2024, the review identifies key application areas of AI in finance, including portfolio optimization, risk management, algorithmic trading, robo-advisory services, and sentiment analysis. The findings highlight the strategic benefits of AI, such as enhanced decision accuracy, operational efficiency, and increased financial inclusivity. However, the study also underscores significant challenges, including lack of model explainability, algorithmic bias, data privacy concerns, and regulatory uncertainty. These dual dimensions emphasize the need for ethical governance, transparent model design, and interdisciplinary collaboration to maximize the benefits of AI in investment contexts. The study concludes by outlining future research directions, particularly the integration of ESG factors, adaptation to emerging markets, and long-term impact assessments of AI-driven strategies.
Sugiarto et al. (Mon,) studied this question.
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