Dynamical systems in AI refer to mathematical frameworks that model how a system's state evolves over time based on specific, fixed rules. They are used to analyze complex, time-dependent behaviors in areas like reinforcement learning, neural networks, and control systems, helping to predict future states and understand stability, chaos, or patterns within dynamic processes.