In artificial intelligence, executive function refers to the architectural components and algorithms that enable an autonomous agent to consciously manage its own cognitive processes to achieve complex, multi-step goals. It works by implementing a control loop that continuously performs meta-cognition (thinking about its own thinking), task decomposition, action selection, and performance monitoring. This involves maintaining active goals in a working memory buffer, shielding them from interference, and dynamically allocating computational resources (a simulated form of mental effort) to planning, execution, and error correction sub-processes. The core mechanism is often a Supervisory Attentional System (SAS)-like module that overrides automatic, stimulus-driven responses to engage in controlled, goal-directed problem-solving.