Challenges using AI systems in the professions: the need for Hierarchical Team-based Intelligent Systems (HTIS)

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Authors: Vicky Arnold, Phil Collier, Stewart A. Leech, Steve G. Sutton
Cited by: 1
References: 25

Abstract

Artificial intelligence (AI) is a significant challenge for the professions (e.g. auditing, consulting, engineering and law) as techniques hold great promise for improving effectiveness and efficiency of engagement performance, but techniques also pose challenges based on current technologies. Our research focuses on using AI embedded Hierarchical Team Intelligent Systems (HTIS). Engagements are completed traditionally with teams including novices (staff/seniors) and experienced/experts (partners/managers), but contemporary AI systems are designed for individual use. We propose a strategy for implementing AI in teams addressing several critical issues: novices with limited knowledge needing to input quality data, evidence that novices become less skilled when using AI, concerns over unexplainable AI and how to allow partners/managers to understand how decisions are formulated, and complexities over documenting AI inputs and decisions. Design recommendations provide potential solutions for these concerns, and behavioural testing with professionals supports the robustness of the various solution components in our design.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Intelligent Tutoring Systems and Adaptive Learning Clinical Reasoning and Diagnostic Skills

Publication details

Journal / source
Journal of Decision System
Publisher
Informa UK Limited
Volume
35
Issue
1
Pages
2666611–2666611
Publication date
2 January 2026
Language
EN