FURI | Spring 2025

AI in Project Risk Management

Traditional software risk management relies on expensive proprietary software, which makes cost a significant barrier in risk management. High costs can burden budget-limited software startups or have them resort to manual processes, which introduces subjectivity. This research investigates a range of risk management tools, including generative AI models and traditional tools, to identify a cost-effective and objective solution for startups. The project will conduct a cost-benefit comparative analysis of various tools used in the software industry, evaluating the best and most cost-effective method to provide accessible and reliable support in risk management.