Artificial intelligence is playing a growing role in consumer financial services, yet many users lack the expertise to judge AI-generated advice and therefore rely on the explanations provided. The present study investigates how explanation quality, advisor type, and decision risk jointly shape users’ evaluation and adoption of financial recommendations. Building on the Information Adoption Model and explainable AI literature, we propose a framework where information quality, information usefulness, perceived trust, and perceived risk influence intentions to follow advice. Conducting a controlled online experiment, we also examine how these relationships may differ across advisor types (human, low-explainability AI, high-explainability AI) and decision risk levels (low, high). Results show that the effects of information usefulness, trust, and information quality differ systematically depending on advisor type, explanation clarity, and decision risk level. Our findings demonstrate that information adoption arises from the interaction of informational, relational, and contextual factors, extending the Information Adoption Model and offering insights for designing more effective AI–human financial advisory systems.
- The Role of Explainability In AI-Driven Financial Decision Making
- Athina Ioannou (Corresponding Author) - University of Surrey, Surrey Business SchoolM.Mahdi Tavalaei (Author) - University of Surrey, Surrey Business SchoolDorthea Vatn (Author) - Norwegian University of Science and TechnologyPatrick Mikalef (Author) - Norwegian University of Science and Technology
- Information Systems Frontiers, Vol.28(Special Issue: Innovative Applications and Ethical Implications of AI in the data sharing and financial analysis: Emerging Trends and Future Directions)
- Springer
- 10/04/2026
- 22/03/2026
- 991115194502346
- © The Author(s) 2026. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Surrey Business School
- English
- Journal article
- Data is available upon request from authors.