A3. AI/ML models learn and adapt to changing network behaviors through iterative processes. Initially, they are trained on historical network data, identifying patterns and relationships. As networks evolve, these models continuously analyze real-time data, comparing it to their learned patterns. Through feedback loops, they adjust their algorithms, fine-tuning predictions and actions. This ongoing adaptation enables AI/ML to anticipate shifts, detect anomalies, and optimize network responses, ensuring optimal performance even in dynamic and evolving environments.