Purpose

While artificial intelligence (AI) has shown its promise in assisting human decision, there exist barriers to adopting AI for decision-making. This study aims to identify barriers in the adoption of AI for automated organisational decision-making. AI plays a key role, not only by automating routine tasks but also by moving into the realm of automating decisions traditionally made by knowledge or skilled workers. The study, therefore, selected respondents who experienced the adoption of AI for decision-making.

Design/methodology/approach

The study applied an interpretive paradigm and conducted exploratory research through qualitative interviews with 13 senior managers in South Africa from organisations involved in AI adoption to identify potential barriers to using AI in automated decision-making processes. A thematic analysis was conducted, and AI coding of transcripts was conducted and compared to the manual thematic coding of transcripts with insights into computer vs human-generated coding. A conceptual framework was created based on the findings.

Findings

Barriers to AI adoption in decision-making include human social dynamics, restrictive regulations, creative work environments, lack of trust and transparency, dynamic business environments, loss of power and control, as well as ethical considerations.

Originality/value

The study uniquely applied the adaptive structuration theory (AST) model to AI decision-making adoption, illustrated the dimensions relevant to AI implementations and made recommendations to overcome barriers to AI adoption. The AST offered a deeper understanding of the dynamic interaction between technological and social dimensions.

中文翻译：

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通过使用人工智能采用自动化组织决策的障碍

目的

尽管人工智能 (AI) 在协助人类决策方面展现了其前景，但采用人工智能进行决策仍存在障碍。本研究旨在找出采用人工智能进行自动化组织决策的障碍。人工智能发挥着关键作用，不仅通过自动化日常任务，而且通过进入传统上由知识或技术工人做出的自动化决策领域。因此，该研究选择了经历过采用人工智能进行决策的受访者。

设计/方法论/途径

该研究采用解释范式，通过对南非参与人工智能采用的组织的 13 名高级管理人员进行定性访谈来进行探索性研究，以确定在自动化决策过程中使用人工智能的潜在障碍。进行了主题分析，并对转录本进行了人工智能编码，并将其与转录本的手动主题编码进行了比较，深入了解了计算机与人类生成的编码。根据调查结果创建了一个概念框架。

发现

在决策中采用人工智能的障碍包括人类社会动态、限制性法规、创造性的工作环境、缺乏信任和透明度、动态的商业环境、权力和控制的丧失以及道德考虑。

原创性/价值

该研究独特地将自适应结构理论（AST）模型应用于人工智能决策采用，阐明了与人工智能实施相关的维度，并提出了克服人工智能采用障碍的建议。AST 提供了对技术和社会维度之间动态相互作用的更深入的理解。