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Business & Information Systems Engineering

Synthesizing AI Failure Research: A Scoping Review

  • 27-10-2025
  • Research Paper
Authors
Chenxi Li
Yixun Lin
Xinyi Tu
Jing Elaine Chen
Ziqi Zhao
Published in
Business & Information Systems Engineering

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Abstract

This scoping review delves into the critical issue of AI failures, identifying three primary categories: technical, interactional, and ethical. The study introduces a Subtypes-Causes-Mitigation (SCM) Framework to systematically analyze and address these failures. It explores the root causes of AI failures, such as technical deficiencies, human-AI interaction dynamics, and ethical concerns, and proposes mitigation strategies for each category. The review also highlights the fragmentation in current research and calls for a more integrated approach to understanding and managing AI failures. By mapping the intellectual landscape of AI failure research, the study provides a roadmap for future research and offers practical implications for system architects, user-experience designers, and policymakers. The conclusion underscores the need for a more systematic and context-aware understanding of AI failures to enhance AI reliability and accountability in real-world deployments.
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Title
Synthesizing AI Failure Research: A Scoping Review
Authors
Chenxi Li
Yixun Lin
Xinyi Tu
Jing Elaine Chen
Ziqi Zhao
Publication date
27-10-2025
Publisher
Springer Fachmedien Wiesbaden
Published in
Business & Information Systems Engineering
Print ISSN: 2363-7005
Electronic ISSN: 1867-0202
DOI
https://doi.org/10.1007/s12599-025-00970-2
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