The impact of AI on personal finance and wealth management in the U.S.

The integration of Artificial Intelligence (AI) into personal finance and wealth management has fundamentally reshaped financial behaviors and decision-making processes. The primary objective of this study is to evaluate the role of AI in influencing personal financial behaviors and wealth management outcomes. Specifically, it aims to determine how AI adoption, investment, and usage impact personal savings and net worth. This study adopts a quantitative approach, utilizing secondary data from trusted sources such as Our World in Data and the Federal Reserve Bank of St. Louis. The dataset spans from 2010 to 2022, capturing trends over a significant period of AI development and adoption. A multivariate regression model is employed to examine the relationships between the dependent variables, Personal Savings Rate and Change in Net Worth, and independent variables such as AI adoption rate, AI investment, and household debt-to-income ratio. Descriptive statistics, correlation analysis, and stationarity tests are conducted to ensure data reliability and model validity. Diagnostic checks, including heteroskedasticity tests and Durbin-Watson statistics, further validate the robustness of the results.
The study reveals that AI adoption positively influences personal savings by encouraging disciplined financial behaviors, consistent with the findings of prior research. However, its impact on wealth accumulation is less direct, with AI investment showing a surprising negative association with changes in net worth. This indicates inefficiencies in resource allocation or lag effects in the benefits of large-scale AI investments. Traditional economic factors, such as household debt and spending habits, continue to play significant roles in shaping financial outcomes, highlighting the enduring influence of non-technological determinants. The study also underscores the role of macroeconomic variables, such as unemployment, in moderating AI’s impact, with precautionary savings behaviors emerging during periods of economic uncertainty.
Based on the findings, several actionable recommendations emerge. For individuals, the adoption of AI-driven tools that promote financial literacy and track spending can enhance savings and improve overall financial health. Financial institutions should prioritize user-centric designs in AI platforms, ensuring accessibility and functionality for diverse demographics. Policymakers are encouraged to support initiatives that bridge disparities in AI adoption, such as digital literacy programs and affordable access to financial technologies. Moreover, strategic investment in AI tools that address wealth management complexities, such as portfolio optimization and risk assessment, is critical for improving long-term financial outcomes.
Originality
This study contributes to the growing body of literature on AI in finance by offering a dual focus on personal savings and wealth management. Unlike previous studies that often treat these domains independently, this research provides an integrated perspective, highlighting both the synergies and divergences in AI’s impact. The findings on the nuanced relationship between AI investment and financial outcomes offer a fresh lens for evaluating the effectiveness of technological advancements. Furthermore, the study’s emphasis on traditional economic factors alongside AI-related variables underscores its originality in bridging the gap between technological innovation and foundational economic principles. This approach provides a robust framework for future research and practical applications in finance.