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.

人工智能 (AI) 随时准备影响业务的各个方面，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，许多组织都在努力实施人工智能解决方案。简而言之，许多公司没有为采用人工智能做好充分准备。更糟糕的是，文献没有对这个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”意味着什么。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，确定了人工智能准备程度的各个方面。本研究采用定性数据分析方法构建了一个关注人工智能准备情况的扎根理论模型。该方法涉及对数据进行系统检查和编码，以确定关键主题和模式，从而制定全面的理论框架。研究结果表明，人工智能准备度可以分为八个维度：信息准备度、环境准备度、基础设施准备度、参与者准备度、流程准备度、客户准备度、数据准备度和技术准备度。这项研究通过概念化人工智能准备结构并确定其关键维度，对营销、管理和信息系统做出了重大贡献。