ARTIFICIAL INTELLIGENCE INCIDENT FORECASTING

The fact that systems in cybersecurity, healthcare, finance and critical infrastructure have grown so complex and are so related has made predicting incidents in advance a main part of risk management. Artificial Intelligence (AI) has emerged as a transformative technology in this context, offering sophisticated tools and methodologies to predict, detect, and mitigate potential incidents before they escalate into critical failures. It investigates Artificial Intelligence Incident Forecasting by looking at its theoretical basis, important technologies and practical usages. The field reviews current machine learning models, techniques for finding anomalies and predictive methods meant to notice and predict things like system outages, security breaches, crises in public health and natural disasters. It also points to a number of events where the use of AI in forecasting strengthened resilience and stopped crisis from occurring. Data quality issues, how models are explained and ethical matters are also identified and addressed by fairness in predictive technologies. A detailed examination demonstrates how AI could greatly change incident management and suggests points to keep in mind for more work and use of AI in this upcoming field.