The Impact of AI on Increasing the Software Project Productivity in Pakistan and Finland
| dc.contributor.author | Ansari, Aliza | |
| dc.contributor.faculty | fi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations| | |
| dc.contributor.organization | fi=Vaasan yliopisto|en=University of Vaasa| | |
| dc.date.accessioned | 2026-06-08T13:30:31Z | |
| dc.date.issued | 2026-05-13 | |
| dc.description.abstract | This study analyses how the use of Artificial Intelligence affects performance and productivity across different regional contexts, using a quantitative survey questionnaire distributed to 28 software professionals currently employed at software companies in Finland (n=8), and Pakistan (n=20). By deploying a structured Likert-scale questionnaire, the survey measured three important variables: code quality, professional confidence in using AI, and perceived productivity. The research findings demonstrate that there is a positive association of AI adoption with perceived productivity across both national contexts. The respondents from Pakistan showed thorough optimism, affirming that AI increases the software project productivity, and the majority of them reported speedy task completion, whereas the Finnish respondents, even though they are more senior, held reservations and heterogeneous views, especially on code quality. However, Pakistani IT professionals exhibited a positive organizational support for AI use. Ethical considerations around AI outputs and governance frameworks also shape the confidence levels of experienced Finnish developers. The findings reveal that novel enthusiasm does not linearly correspond to technological maturity. Achieving the maximum potential of AI in software development processes requires comprehension beyond tools alone, containing formal training, governance mechanisms, and a professional organizational culture that critically evaluates AI outputs. The interaction of human and technological factors is ultimately central to how AI reshapes software productivity across diverse national contexts. Spearman correlation analysis was also employed across eight factor pairs to study the inter-variable relationships between ordinal and binary measures. | |
| dc.description.notification | fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format| | |
| dc.format.content | fi=kokoteksti|en=fulltext| | |
| dc.format.extent | 107 | |
| dc.identifier.uri | https://osuva.uwasa.fi/handle/11111/20741 | |
| dc.identifier.urn | URN:NBN:fi-fe2026051345075 | |
| dc.language.iso | eng | |
| dc.rights | CC BY 4.0 | |
| dc.subject.degreeprogramme | Master’s Programme in Industrial Engineering and Management | |
| dc.subject.discipline | Strategic Project Management | |
| dc.subject.yso | artificial intelligence | |
| dc.subject.yso | software development | |
| dc.title | The Impact of AI on Increasing the Software Project Productivity in Pakistan and Finland | |
| dc.type.ontasot | fi=Pro gradu -tutkielma|en=Master's thesis|sv=Pro gradu -avhandling| |
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