When Advice Isn’t Trusted: Privacy, Transparency, and Accountability Risks Driving AI Mistrust and Consumer Resistance in Financial Advisory Services

Pichit Sungkarungsri and Supaporn Kiattisin ()
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Pichit Sungkarungsri: Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand
Supaporn Kiattisin: Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand

Sustainability, 2026, vol. 18, issue 3, 1-41

Abstract: The application of AI in financial planning services has the potential to enhance universal access to financial services. However, AI still faces common consumer mistrust and resistance, hindering the long-term sustainability of AI-powered financial planning. This research aims to explain why consumers resist AI in financial planning and the mechanisms that lead to this resistance and negative customer behavior. This research developed a conceptual model by integrating the S-O-B-C framework with Innovation Resistance Theory, AI ethical risks, and social influence that influence AI mistrust and intention to resist, which lead to negative outcomes such as negative word-of-mouth and customer disloyalty in the context of digital financial planning services in Thailand. The research collected data from a sample of 420 persons and the data was analyzed using PLS-SEM. The research identified social influence and the risks associated with AI transparency and accountability as primary factors contributing to AI mistrust, whereas privacy risk serves as a more fundamental catalyst for resistance. This resistance contributes to negative word-of-mouth and leads to customer disloyalty. It emphasizes that developing sustainable AI financial advisors must go beyond technically secure design to transparent, accountable, and socially legitimate governance to maintain long-term relationships with customers in the digital financial system.

Keywords: artificial intelligence; AI financial advisory services; AI mistrust; innovation resistance; social influence; negative word of mouth; customer disloyalty; innovation resistance theory; Stimulus–Organism–Behavior–Consequence; S-O-B-C (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2026
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