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dc.rights.licenseKūrybinių bendrijų licencija / Creative Commons licenceen_US
dc.contributor.authorBarta, Gergő
dc.contributor.authorGörcsi, Gergely
dc.date.accessioned2024-11-21T13:52:42Z
dc.date.available2024-11-21T13:52:42Z
dc.date.issued2019
dc.identifier.isbn9786094761614en_US
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/155831
dc.description.abstractPurpose – the number of projects and amount of investment into Artificial Intelligence (AI) based business process automation is increasing. To utilize the power of AI, business organizations shall achieve a certain level of digital maturity that enables of handling the risks arising from AI. AI brings new risk factors to their life that has to be reduced to an acceptable level. If risk mitigation procedures are not in place, then AI might cause a greater headache than a market advantage resulting in expensive implementation with no business benefit. Research methodology – the objective is to analyze what risk factors can AI bring with itself to the life of corporations by analyzing general IT risk assessment processes and the stages of AI development. Findings – We observed that current IT risk assessment methodologies don’t detail possible risk scenarios regarding intelligent applications and don’t extend their threat catalogs to help organizations consider threats related to AI. Research limitations – the research work details possible risks for general AI development that might differ across industries, business cases, specific algorithms etc. Practical implications – the research contributes to organizations to assess possible risks arising from the use of AI. Originality/Value – since AI based automation is the result of recent research work, analyzing risk management aspects of its use can be considered as a new field for further research.en_US
dc.format.extent10 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/155623en_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.source.urihttp://cibmee.vgtu.lt/index.php/verslas/2019/paper/view/498en_US
dc.subjectArtificial Intelligenceen_US
dc.subjectMachine Learningen_US
dc.subjectIT risk assessmenten_US
dc.subjectrisk managementen_US
dc.subjectbusiness automationen_US
dc.titleAssessing and managing business risks for Artificial Intelligence based business process automationen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accessRightsLaisvai prieinamas / Openly availableen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.alternativeDigitalization of business processes: trends, challenges, solutionsen_US
dcterms.issued2019-05-10
dcterms.licenseCC BYen_US
dcterms.references35en_US
dc.description.versionTaip / Yesen_US
dc.contributor.institutionSzent István Universityen_US
dcterms.sourcetitleInternational Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering ‘2019“en_US
dc.identifier.eisbn9786094761621en_US
dc.identifier.eissn2538-8711en_US
dc.publisher.nameVilnius Gediminas Technical Universityen_US
dc.publisher.nameVilniaus Gedimino technikos universitetasen_US
dc.publisher.countryLithuaniaen_US
dc.publisher.countryLietuvaen_US
dc.publisher.cityVilniusen_US
dc.identifier.doihttps://doi.org/10.3846/cibmee.2019.084en_US


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Kūrybinių bendrijų licencija / Creative Commons licence
Except where otherwise noted, this item's license is described as Kūrybinių bendrijų licencija / Creative Commons licence