解码人工智能准备情况:深入分析跨国公司的关键维度

IF 11.1 1区 管理学 Q1 ENGINEERING, INDUSTRIAL
Ali N. Tehrani , Subhasis Ray , Sanjit K. Roy , Richard L. Gruner , Francesco P. Appio
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引用次数: 0

摘要

人工智能(AI)随时准备影响业务的方方面面,从优化运营到个性化服务和提升客户价值。然而,由于缺乏必要的基础设施和机制,许多企业在实施人工智能解决方案时举步维艰。简而言之,许多公司还没有为采用人工智能做好充分准备。更糟糕的是,文献并没有对这一问题提供足够的见解。为了帮助解决这个问题,作者在本文中探讨了 "人工智能就绪 "的含义。具体来说,本研究通过对东南亚(主要是印度)52 家跨国公司的中高层管理人员进行深入的半结构化访谈,确定了人工智能就绪程度的各个维度。本研究采用定性数据分析方法,构建了以人工智能就绪程度为重点的基础理论模型。该方法包括对数据进行系统检查和编码,以确定关键主题和模式,从而建立一个全面的理论框架。研究结果表明,人工智能就绪程度可分为八个方面:信息、环境、基础设施、参与者、流程、客户、数据和技术就绪程度。本研究将人工智能就绪度概念化,并确定了其关键维度,为市场营销、管理和信息系统做出了重要贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decoding AI readiness: An in-depth analysis of key dimensions in multinational corporations

Artificial Intelligence (AI) stands ready to impact all aspects of business, from optimizing operations to personalizing services and enhancing customer value. However, many organizations grapple with implementing AI solutions due to a lack of necessary infrastructure and mechanisms. In short, many companies are not adequately prepared to adopt AI. To make matters worse, the literature does not offer sufficient insights into this issue. To help address this issue, in this article, the authors explore what it means to become ‘AI-ready.’ Specifically, this study identifies the various dimensions of AI readiness through in-depth semi-structured interviews with top- and middle-level managers from 52 multinational corporations in Southeast Asia, primarily in India. This study employed a qualitative data analysis approach to construct a grounded theory model focusing on AI readiness. The methodology involved systematic examination and coding of data to identify key themes and patterns, enabling the development of a comprehensive theoretical framework. The findings suggest that AI readiness can be categorized into eight dimensions: informational, environmental, infrastructural, participants, process, customers, data, and technological readiness. This study makes a significant contribution to marketing, management, and information systems by conceptualizing the AI readiness construct and identifying its key dimensions.

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来源期刊
Technovation
Technovation 管理科学-工程:工业
CiteScore
15.10
自引率
11.20%
发文量
208
审稿时长
91 days
期刊介绍: The interdisciplinary journal Technovation covers various aspects of technological innovation, exploring processes, products, and social impacts. It examines innovation in both process and product realms, including social innovations like regulatory frameworks and non-economic benefits. Topics range from emerging trends and capital for development to managing technology-intensive ventures and innovation in organizations of different sizes. It also discusses organizational structures, investment strategies for science and technology enterprises, and the roles of technological innovators. Additionally, it addresses technology transfer between developing countries and innovation across enterprise, political, and economic systems.
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