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dc.contributor.authorNguyen-Duc, Anh
dc.contributor.authorSundbø, Ingrid
dc.contributor.authorNascimento, Elizamary
dc.contributor.authorConte, Tayana
dc.contributor.authorAhmed, Iftekhar
dc.contributor.authorAbrahamsson, Pekka
dc.date.accessioned2021-01-26T12:37:49Z
dc.date.available2021-01-26T12:37:49Z
dc.date.issued2020
dc.identifier.citationNguyen-Duc, A., Sundbø, I., Nascimento, E., Conte, T., Ahmed, I., & Abrahamsson, P. (2020). A Multiple Case Study of Artificial Intelligent System Development in Industry. In <i>EASE '20 : Proceedings of the 24th International Conference on Evaluation and Assessment in Software Engineering</i> (pp. 1-10). ACM. <a href="https://doi.org/10.1145/3383219.3383220" target="_blank">https://doi.org/10.1145/3383219.3383220</a>
dc.identifier.otherCONVID_35320237
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/73819
dc.description.abstractThere is a rapidly increasing amount of Artificial Intelligence (AI) systems developed in recent years, with much expectation on its capacity of innovation and business value generation. However, the promised value of AI systems in specific business contexts might not be understood, and further integrated into the development processes. We wanted to understand how software engineering processes and practices can be applied to develop AI systems in a fast-faced, business-driven manner. As the first step, we explored contextual factors of AI development and the connections between AI developments to business opportunities. We conducted 12 semi-structured interviews in seven companies in Brazil, Norway and Southeast Asia. Our investigation revealed different types of AI systems and different AI development approaches. However, it is common that business opportunities involving with AI systems are not validated and there is lack of business-driven metrics that guide the development of AI systems. The findings have implications for future research on business-driven AI development and supporting tools and practices.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofEASE '20 : Proceedings of the 24th International Conference on Evaluation and Assessment in Software Engineering
dc.rightsIn Copyright
dc.subject.otherartificial intelligent system
dc.subject.othersoftware development
dc.subject.othersoftware engineering
dc.subject.otherbusiness opportunity
dc.subject.otherPivot
dc.subject.otherAI business pattern
dc.subject.otherSEMAT
dc.titleA Multiple Case Study of Artificial Intelligent System Development in Industry
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-202101261279
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietojärjestelmätiedefi
dc.contributor.oppiaineInformation Systems Scienceen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.relation.isbn978-1-4503-7731-7
dc.description.reviewstatuspeerReviewed
dc.format.pagerange1-10
dc.type.versionacceptedVersion
dc.rights.copyright© 2020 The Authors
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational Conference on Evaluation and Assessment in Software Engineering
dc.subject.ysotekoäly
dc.subject.ysoohjelmistokehitys
dc.subject.ysoohjelmistoliiketoiminta
dc.subject.ysoohjelmistotuotanto
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p2616
jyx.subject.urihttp://www.yso.fi/onto/yso/p21530
jyx.subject.urihttp://www.yso.fi/onto/yso/p21307
jyx.subject.urihttp://www.yso.fi/onto/yso/p17097
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1145/3383219.3383220
jyx.fundinginformationIn this paper, Conte's work is funded by CNPq (423149/2016-4, 311494/2017-0, and 204081/2018-1/PDE).


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