Re-thinking the Competitive Landscape of Artificial Intelligence

dc.contributor.authorAlsheibani, Sulaiman
dc.contributor.authorMessom, Chris
dc.contributor.authorCheung , Yen
dc.date.accessioned2020-01-04T08:24:03Z
dc.date.available2020-01-04T08:24:03Z
dc.date.issued2020-01-07
dc.description.abstractIn 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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.718
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64460
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPromises and Perils of Artificial Intelligence and Machine Learning: Disruption, Adoption, Dehumanisation, Governance, Risk and Compliance
dc.subjectadoption
dc.subjectal adoption organizations
dc.subjectartificial intelligence
dc.titleRe-thinking the Competitive Landscape of Artificial Intelligence
dc.typeConference Paper
dc.type.dcmiText

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