Leveraging Artificial Intelligence for Efficient Employee Performance Evaluation of Software Projects

dc.contributor.advisorSeifu Mamo (PhD)
dc.contributor.authorYonatan Tasew
dc.date.accessioned2025-07-25T05:34:28Z
dc.date.available2025-07-25T05:34:28Z
dc.date.issued2024-10
dc.description.abstractPerformance evaluation is a critical process for ensuring employee growth,organizational and project success. Due to the important nature of these evaluations many methods have been proposed over the years to improve theway they are conducted. However, the recent rise of Artificial intelligence and its success across many disciplines can lead us to ponder if AI can beleveraged to fill the shortcomings of traditional evaluation methods. This research explores the potential of integrating Artificial Intelligence (AI) intoperformance evaluation systems to address the challenges of subjectivity and inefficiency. Through a comprehensive survey of software developmentprofessionals, the study investigates perceptions of current evaluation processes, the importance of data-driven insights, and attitudes towards AIintegration in software development teams. The results show that traditional approaches lack in some areas, mainly in perceived biases, evaluationfrequency, and communication problems. The advantages of AI that respondents emphasized included shorter evaluation times, a decline inhuman bias, improved insights for development, and ongoing feedback. On the other hand, potential biases in AI algorithms and worries about AI'scapacity to identify nuance contributions were also mentioned. The study advances our knowledge of how artificial intelligence (AI) mightimprove software development performance reviews, fostering a more impartial, effective, and perceptive procedure. It also describes how ethicalstandards and transparent AI systems are essential to ensuring thorough and impartial assessments. Key words: Performance evaluation, Artificial intelligence , Algorithm,
dc.identifier.urihttps://etd.aau.edu.et/handle/123456789/5679
dc.language.isoen_US
dc.publisherAddis Ababa University
dc.titleLeveraging Artificial Intelligence for Efficient Employee Performance Evaluation of Software Projects
dc.typeThesis

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