Decoding AI readiness: An in-depth analysis of key dimensions in multinational corporations

Ali Nazari Tehrani, Subhasis Ray, Sanjit K. Roy, Richard L. Gruner, Francesco Appio

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Article number102948
JournalTechnovation
Volume131
Early online date1 Jan 2024
DOIs
Publication statusPublished - Mar 2024

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