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dc.contributor.authorLundblad, Linnea
dc.contributor.authorOlsson, Tilda
dc.date.accessioned2022-10-28T13:05:51Z
dc.date.available2022-10-28T13:05:51Z
dc.date.issued2022-10-28
dc.identifier.urihttps://hdl.handle.net/2077/74027
dc.description.abstractArtificial Intelligence (AI) is still largely unexplored within information systems research, and most published work remains non-academic (Collins et al., 2021). While there exists some research related to the challenges incumbent organizations have to scale AI, there is little insight to why some succeed. The paper applies a multidimensional framework called the Artificial Intelligence Innovation Maturity Index (AIMI) (Yams et al. (2020) to analyze six AI deployments in European organizations. The purpose of the study was to identify success factors and assess organizations’ maturity to integrate AI for business model innovation. The study conducts a qualitative approach where 7 respondents were interviewed regarding an implemented AI use case. The paper contributes with practical advice to managers of what to consider when leading and investing in AI. The findings indicate that the primary investment focus is dependent on the organization's AI maturity level and considers a short term and long term purpose. The paper contributes to research formation related to applied artificial intelligence, digital transformation, maturity models and business model innovation.en_US
dc.language.isoengen_US
dc.relation.ispartofseries2022:053en_US
dc.subjectartificial intelligenceen_US
dc.subjectdata-drivenen_US
dc.subjectbusiness model innovationen_US
dc.subjectdigital transformationen_US
dc.subjectdigital maturityen_US
dc.subjectAI maturityen_US
dc.titleAI Integration Scaling AI for business model innovationen_US
dc.typeTexteng
dc.setspec.uppsokTechnology
dc.type.uppsokH2
dc.contributor.departmentInstitutionen för tillämpad informationsteknologiswe
dc.contributor.departmentDepartment of Applied Information Technologyeng
dc.type.degreeMaster theseseng


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