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Re-thinking the Competitive Landscape of Artificial Intelligence

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Title:Re-thinking the Competitive Landscape of Artificial Intelligence
Authors:Alsheibani, Sulaiman
Messom, Chris
Cheung , Yen
Keywords:Promises and Perils of Artificial Intelligence and Machine Learning: Disruption, Adoption, Dehumanisation, Governance, Risk and Compliance
adoption
al adoption organizations
artificial intelligence
Date Issued:07 Jan 2020
Abstract:In recent years, Artificial Intelligence (AI) has emerged from its traditional domain of computer science research to be a management reality. This can be seen in the remarkable increase in the adoption of AI technology in organisations resulting in increased revenue, reduced costs and improved business efficiency [19]. Despite this trend, there are still many organisations that are facing the decision whether to adopt AI. Thus, to evaluate the adoption of AI at organizational-level we draw on two-grounded theories: Technology-Organisations-Environment (TOE) framework and Diffusion of Innovation theory (DOI) to identify factors that influence the adoption of AI. Survey data collected from 208 large, medium-sized and small organisations in Australia is used to test the proposed framework. We offer a method of how examining AI over a set of organizations. Besides offering a number of important recommendations for AI adoption future directions for research in this area are also included in this paper.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/64460
ISBN:978-0-9981331-3-3
DOI:10.24251/HICSS.2020.718
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Promises and Perils of Artificial Intelligence and Machine Learning: Disruption, Adoption, Dehumanisation, Governance, Risk and Compliance


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