Understanding users' behavioral intention to use artificial intelligence for personal financial management: an innovation diffusion theory approach

The purpose of this study is to investigate the factors that influence users' behavioral intentions to adopt Artificial Intelligence for personal financial management using an Innovation Diffusion Theory (IDT) framework. An analysis of empirical data collected from 246 users is conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings reveal that users' intentions to embrace AI in financial management are influenced by a variety of factors, including relative advantage, compatibility, and observability. As a result of this study, we offer insights into the intricate interplay of factors affecting the adoption of artificial intelligence in personal finance.