A Framework of AI Strategy

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dc.contributor.authorShi, Yao
dc.contributor.authorGebauer, Judith
dc.contributor.authorJavadi, Elahe
dc.date.accessioned2023-12-26T18:35:58Z
dc.date.available2023-12-26T18:35:58Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2023.027
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.otherdda35c30-de1d-4713-a015-9ab3727ce1c3
dc.identifier.urihttps://hdl.handle.net/10125/106402
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th 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.subjectAI and the Future of Work
dc.subjectai
dc.subjectai strategy
dc.subjectcompetitive advantage
dc.subjectdigital transformation
dc.titleA Framework of AI Strategy
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractBuilding a vibrant strategy for the use of Artificial Intelligence (AI) in business is becoming critical for company success in the AI era. To decode AI strategy, this study aims to address three questions: (1) what is AI strategy? (2) what are the key elements of AI strategy? (3) how can AI strategy be applied and impact a business? We define AI strategy and propose an AI strategy framework consisting of three layers: AI strategic competency, AI use cases, and AI enabling factors. Based on published cases that describe early applications of AI, we identify a bottom-up approach typically used by Small and Medium-sized Enterprises (SMEs) in building AI strategy and a top-down approach typically used by big tech firms and traditional incumbent firms. We also find differences in the core of the AI strategies that are initiated by the three types of enterprises: SMEs: survival oriented; big tech firms: AI ecosystem oriented; traditional incumbent firms: business alignment oriented.
dcterms.extent10 pages
prism.startingpage227

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AI and the Future of Work