Business value appropriation roadmap for artificial intelligence
VINE Journal of Information and Knowledge Management Systems
ISSN: 2059-5891
Article publication date: 6 April 2020
Issue publication date: 31 May 2021
Abstract
Purpose
Artificial intelligence (AI) is deemed to have a significant impact as a value driver for the firms and help them get an operational and competitive advantage. However, there exists a lack of understanding of how to appropriate value from this nascent technology. This paper aims to discuss the approaches toward knowledge and innovation strategies to fill this gap.
Design/methodology/approach
The discussion presents a review of the extant strategy and information systems literature to develop a strategy for organizational learning and value appropriation strategy for AI. A roadmap is drawn from ambidexterity and organizational learning theories.
Findings
This study builds the link between learning and ambidexterity to propose paths for exploration and exploitation of AI. The study presents an ambidextrous approach toward innovation concerning AI and highlights the importance of developing as well as reusing the resources.
Research limitations/implications
This study integrates over three decades of strategy and information systems literature to answer questions about value creation from AI. The study extends the ambidexterity literature with contemporary.
Practical implications
This study could help practitioners in making sense of AI and making use of AI. The roadmap could be used as a guide for the strategy development process.
Originality/value
This study analyzes a time-tested theoretical framework and integrates it with futuristic technology in a way that could reduce the gap between intent and action. It aims to simplify the organizational learning and competency development for an uncertain, confusing and new technology.
Keywords
Citation
Mishra, A.N. and Pani, A.K. (2021), "Business value appropriation roadmap for artificial intelligence", VINE Journal of Information and Knowledge Management Systems, Vol. 51 No. 3, pp. 353-368. https://doi.org/10.1108/VJIKMS-07-2019-0107
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited