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ZENODO
Journal . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
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AN EMPIRICAL ANALYSIS OF AI-DRIVEN FINANCIAL DECISION-MAKING AMONG GENERATION Z

Authors: Ms. Kajal Chheda;

AN EMPIRICAL ANALYSIS OF AI-DRIVEN FINANCIAL DECISION-MAKING AMONG GENERATION Z

Abstract

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.

Keywords

Generation Z, AI-driven financial tools, financial behavior, risk perception, financial literacy

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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average