Análisis de las aplicaciones de técnicas de inteligencia artificial para mejorar la definición de alcance en proyectos

Abstract

This thesis focused on the evaluation and comparison of the efficiency of artificial intelligence (AI) and traditional methodologies based on human intervention in the software project scope definition process. The main objective was to determine whether the implementation of AI techniques can significantly enhance accuracy and efficiency in defining the scope of software projects compared to traditional methodologies that primarily rely on human intervention. To carry out this study, several projects were selected, and both AI techniques and methodologies applied by people were employed to define their scope. The results revealed that the application of AI achieved an average effectiveness score of 2.9 on an evaluation scale, while methodologies executed by people obtained a slightly higher score of 2.91. Although the difference in scores was not significant, these findings suggest that AI has the potential to be a valuable tool in the software project scope definition process. Furthermore, it was observed that AI proved to be particularly effective in risk identification and handling complex data, while methodologies executed by people still play an essential role in communication and contextual decision-making. This thesis provides a detailed insight into how AI can be integrated into the software project scope definition process and highlights the importance of considering both technical and human aspects in project management. Organizations can leverage these findings to make informed decisions regarding the implementation of AI technologies in their projects and improve scope management efficiently and accurately.