Optimizing IT Governance and Project Management in Software Development through AI Integration and COBIT 2019 Framework

In the modern business environment, efficient time management and robust IT governance are crucial due to rapid technological advancements. Effective governance and resource management are imperative for organizations aiming to optimize performance. This research uses AI techniques and the COBIT 2019 framework to optimize IT governance in software development projects. Quantitative methods are employed to analyze factors causing scheduling delays in projects using machine learning algorithms, focusing on identifying factors that impact project timelines. Data from a previous study on software cost estimation involves 120 projects from 42 organizations. Data preprocessing techniques are applied to handle missing data and scale features. Feature engineering is conducted to identify critical factors affecting project completion times. We evaluate various machine learning models for robust analysis of project delay factors, and we find that CatBoost provides reliable project duration predictions. Model performance was evaluated using MAE, RMSE, R2, and MAPE. Integrating AI with COBIT 2019 enhances project duration estimation accuracy and strengthens IT governance. This combined approach improves project efficiency and aligns IT initiatives with organizational goals.