When Security Meets Intelligence: Trust in AI, Blockchain Security, and Investor Behavior

Despite the increasing integration of Artificial Intelligence (AI) into cryptocurrency trading environments, concerns remain regarding security, trust, and investor decision-making. Blockchain infrastructures are often described as trust-minimizing systems; however, AI-based trading tools increase reliance on opaque algorithmic outputs. This research study examines how blockchain security, AI accuracy, and AI experience shape trust in AI and behavioural intention in terms of use of an AI-based trading system. For achieving research outcomes, this research study recruited 215 cryptocurrency investors using a structured survey questionnaire and a model for testing trust, trading intentions, and system perceptions. The findings from this research study suggest that blockchain security and perceived accuracy enhance trust in AI. In contrast, AI experience negatively impacts trust in AI, as experienced users exhibit algorithmic scepticism.  The findings further related that in the prediction of behavioural intention of users, perceived accuracy of AI and structural security have a direct impact on intention, and trust is not a key determining predictor in the research model. Therefore, structural assurance performs a key role in shaping investors' intentions in a financial market.