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AI and Machine Learning in Industrial Asset Management: Insights from CIAM Meetings

dc.contributor.authorFrick, Jan
dc.date.accessioned2023-08-23T10:55:38Z
dc.date.available2023-08-23T10:55:38Z
dc.date.created2023-08-09T09:59:22Z
dc.date.issued2023
dc.identifier.citationFrick, J. (2023) AI and Machine Learning in Industrial Asset Management: Insights from CIAM Meetings. SunText Reviews of Economics & Business, 4(3)en_US
dc.identifier.issn2766-4775
dc.identifier.urihttps://hdl.handle.net/11250/3085415
dc.description.abstractThis paper investigates the influence of Artificial Intelligence (AI) and Machine Learning (ML) in Industrial Asset Management as reflected in the discussions from various Cluster for Industrial Asset Management (CIAM) meetings. (CIAM 2023) Utilizing an interpretive case study approach, it sheds light on the transformative potential of these technologies, identifies challenges encountered during implementation, and presents future predictions for AI and ML deployment in the field.en_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectmaskinlæringen_US
dc.subjectartificial intelligence (AI)en_US
dc.subjectkunstig intelligensen_US
dc.titleAI and Machine Learning in Industrial Asset Management: Insights from CIAM Meetingsen_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2023 Frick J.en_US
dc.subject.nsiVDP::Samfunnsvitenskap: 200::Økonomi: 210::Bedriftsøkonomi: 213en_US
dc.subject.nsiVDP::Teknologi: 500en_US
dc.source.volume4en_US
dc.source.journalSunText Review of Economics & Businessen_US
dc.source.issue3en_US
dc.identifier.doi10.51737/2766-4775.2023.089
dc.identifier.cristin2165794
cristin.ispublishedtrue
cristin.fulltextoriginal


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