Significance of Behavioral Intention to Adopt Articficial Intelligence in Investment Strategies

Abstract

Artificial Intelligence (AI) is revolutionizing the investment management industry, promising enhanced decision-making, improved efficiency, and optimized portfolio management. Despite this, the adoption of AI in finance services is hindered by concerns of trust, ethics, and the risks they might pose. The primary constructs of interest include perceived trust (PT), ethical concern (E), perceived usefulness (PU), social norms (SN) and behavioural intention (BI) regarding how so-called artificial AI tools are adopted by investors in the investment management process, which this study explores. The quantitative approach was employed using “Partial Least Squares Structural Equation Modeling” (PLS-SEM) to collect data from 200 respondents with experience in AI-driven AI-driven investment tools. The most substantial finding is that the impact of perceived usefulness on behavioural intention was positively correlated but not as strong as the impact on trust and ethics. This research adds to the literature by integrating ethical concerns and social norms into the “technology acceptance model” (TAM) to understand the adoption of AI in the investment sector. Finally, we provide practical implications for financial premises and address AI developers by providing transparent, trustworthy, and ethically sound AI systems for investment management.