Bridging The QA Gap: A Lean Project Management Framework for Migrating to AI-Powered Testing

dc.contributor.authorPillai, Chippy
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2026-06-18T07:47:06Z
dc.date.issued2026-05-11
dc.description.abstractSoftware has come to play a major role in the operations of most contemporary organisations, in particular in those areas where reliability and accuracy are main issues. With the growth in the complexity of software, the traditional Quality Assurance (QA) practices, particularly script-based automation has been found to struggle with overheads in maintenance, limited scalabilityand inefficiencies. Meanwhile, the potential alternative can be AI-powered testing tools, which offer both adaptive features and better efficiencies. But the way toward the legacy QA automation to AI-powered test tools has not been paved easily and is fraught with both technical and organisational issues. This paper attempts to explore how a transition like this can be effectively handled in a systematic way. The research problem is addressed by developing a Lean QA Migration Framework (LQMF), which is grounded in Lean thinking and supported by concepts related to organisational change and technology adoption. The research is justified based on DesignScience Research approach, with an empirical case study. Semi-structured interviews with practitioners in the industry and thematic analysis facilitated by NVivo have been used to collectand analyze the data respectively. The results suggest that the source of inefficiencies in current QA processes are usually located along repetitive maintenance activities and lack of process visibility. It is also noted that organisational barriers to the adoption of AI are mainly the ones associated with resistance to change and with issues related to trustworthiness and reliability. Moreover, AI testing tools areobserved to be more used as augmentation mechanisms, and not fully autonomous solutions, in practice. These insights suggest that the proposed framework can offer a stepwise method through which organisations can detect inefficiencies within their processes, the tools to use, and the adoption to undertake in a controlled manner. The conclusion drawn is that the crucial element in the successful transformation of QA does not solely rely on technological facilities but also the systematic procedures as well as organisational preparedness.
dc.description.notificationfi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format|
dc.format.contentfi=kokoteksti|en=fulltext|
dc.format.extent90
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/20967
dc.identifier.urnURN:NBN:fi-fe2026051142680
dc.language.isoeng
dc.rightsCC BY 4.0
dc.subject.degreeprogrammeMaster’s Programme in Industrial Engineering and Management
dc.subject.disciplineStrategic Project Management
dc.subject.ysotesting
dc.subject.ysolean thinking
dc.subject.ysoautomation
dc.subject.ysosoftware engineering
dc.subject.ysoartificial intelligence
dc.subject.ysotechnology
dc.subject.ysoagile methods
dc.subject.ysoproject leadership
dc.subject.ysoquality assurance
dc.subject.ysoproject management
dc.subject.ysoadoption
dc.titleBridging The QA Gap: A Lean Project Management Framework for Migrating to AI-Powered Testing
dc.type.ontasotfi=Pro gradu -tutkielma|en=Master's thesis|sv=Pro gradu -avhandling|

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