Key points are not available for this paper at this time.
Purpose This paper investigates the transformative role of Artificial Intelligence (AI) in personal financial management, focusing on its potential to enhance financial decision-making while highlighting associated ethical, regulatory, and accessibility challenges. Design/methodology/approach A structured literature review methodology was employed, incorporating peer-reviewed academic publications, industry reports, and policy papers published between 2019 and early 2025. The review synthesizes insights across different thematic domains including investment management, digital inclusion, algorithmic bias, and AI explainability. Findings AI significantly enhances personal financial services by automating tasks, customizing investment strategies, and improving financial literacy. However, ethical risks, such as algorithmic bias, automation bias, and data privacy violations, can exacerbate existing inequalities. Transparency, fairness-aware machine learning, and inclusive design are essential for responsible AI integration. Practical implications The findings offer guidance for designing user-centric, ethical, and accessible AI financial services. Recommendations include integrating explainable AI tools, enhancing digital literacy programs, and adopting corporate digital responsibility frameworks. Social implications If designed responsibly, AI can democratize financial services, improve financial wellbeing, and promote inclusion. However, without ethical safeguards, it risks reinforcing systemic biases and excluding vulnerable populations. Bridging the digital divide and ensuring regulatory oversight are vital to ensuring equitable outcomes. Originality/value This study provides a comprehensive synthesis of current debates and emerging practices surrounding AI in personal finance. It highlights a unique intersection of technological innovation and ethical responsibility, contributing to ongoing discourse on sustainable and inclusive digital finance.
Siamand Hesami (Sat,) studied this question.