Let me explain: a comparative field study on how experts enact authority over clients when facing AI decisions

Mayer, Anne‐Sophie, Elmira van den Broek and Tomislav Karacic

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: With organizations increasingly relying on predictive artificial intelligence (AI) technologies for decision‐making, experts lose the authority to overrule AI‐generated decisions yet remain responsible for presenting them to clients. As experts depend on clients’ recognition and approval of decisions, this shift presents a critical disruption to their authority. To investigate how experts respond to this challenge, we adopt a relational perspective that foregrounds the role of audiences in reconfiguring authority. Drawing on a comparative field study, we show how experts sought to reconstruct their authority by engaging in different activities to make clients understand and accept AI decisions, which we call ‘explaining practices’. These practices were shaped by two relational conditions: (1) whether clients recognized the expertise of human experts as unique; and (2) whether interactions between experts and clients provided rich opportunities for learning about clients’ evolving needs. When experts were able to learn about and tailor their explanations to those needs, clients could better make sense of AI decisions and were more willing to accept them, thereby reinforcing expert authority. By contrast, experts who failed to do so left clients with decisions they could not understand or endorse, undermining their authority. This study thereby offers new insights into the complex interplay between expert–client relationships, expert authority, and explaining practices.

Keywords: artificial intelligence; AI decision‐making; expert–client relationship; expert authority; relational perspective; comparative field study; explaining practices (search for similar items in EconPapers)
JEL-codes: L81 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2025-11-08
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Published in Journal of Management Studies, 8, November, 2025. ISSN: 0022-2380

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