
This study examines the influence of artificial intelligence (AI) on financial decision-making among Generation Z, defined as individuals born between 1997 and 2012. As a digitally native cohort, Generation Z demonstrates high technological adaptability and early adoption of financial technologies. The study primarily adopts a quantitative research approach supported by existing literature to analyze usage patterns, adoption drivers, perceived benefits, risks, and trust levels associated with AI-driven financial tools. Primary data were collected through a structured survey administered to 178 Generation Z respondents. The findings reveal widespread awareness and moderate usage of AI-based applications such as budgeting tools, investment platforms, and robo-advisors. A majority of respondents reported improvements in financial organization and decision-making efficiency. However, concerns regarding algorithmic bias, lack of transparency, inaccurate recommendations, and data privacy significantly affect trust levels. The study highlights a growing reliance on AI in personal finance while emphasizing the importance of enhanced financial literacy, ethical AI practices, and robust regulatory frameworks to ensure responsible and sustainable adoption of AI-driven financial tools among Generation Z.
Generation Z, AI-driven financial tools, financial behavior, risk perception, financial literacy
Generation Z, AI-driven financial tools, financial behavior, risk perception, financial literacy
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
