New Research Note in Business & Information Systems Engineering: Beware of AI Explanations!

In a recent research note published in the journal Business & Information Systems Engineering (BISE), we examine AI explainability as a socio-technical design problem. The article is a community project that emerged from the Dagstuhl Seminar 24292, “Leveraging AI for Management Decision-Making.”

The quality of explanations depends on clarifying stakeholder goals, context, and alignment with human mental models, and by synthesizing socio-technical causes and corresponding limitations, the article offers a structured framework that shifts the focus from the mere generation of explanations to when and how explanations are meaningful and value-adding in real-world organizational AI systems.

The paper is available via open access at SpringerNatureLink. BISE has an Impact Factor of 12.2 (2025) and is one of the top-tier journals in the field of information systems.