a, 2025). This autonomy is underpinned by advanced algorithms that prioritize efficiency and accuracy, making AI agents invaluable in dynamic environments like finance or supply chain management.

Another defining feature is **machine learning adaptation**, which enables AI agents to learn from data and improve their performance over time. By leveraging techniques such as supervised, unsupervised, and reinforcement learning, these agents can refine their predictions and actions. For example, sales and lead 