Agentic AI Definition

Agentic AI refers to AI systems designed to autonomously pursue complex goals and workflows with limited direct human supervision. It exhibits autonomous decision-making, planning, and adaptive execution to complete multi-step processes. 

At its core, agentic AI aims to operate more like a human employee — understanding context and instructions in natural language, setting appropriate goals, reasoning through subtasks, and adapting decisions and actions based on changing conditions. Learn more about Agentic AI.

Key capabilities include autonomy, reasoning, adaptable planning, language understanding, and workflow optimization. All of these capabilities allow agentic AI to operate autonomously, proactively, and intelligently when tackling complex objectives across dynamic environments.

Agentic AI represents a seismic shift from conventional narrow AI that is programmed for specific tasks. By leveraging large language models, massive training datasets, scalable computing power, and connectivity, agentic AI can set its own goals, plan optimized workflows, make nuanced decisions, and adapt to changing circumstances. This enhanced autonomy and contextual reasoning unlocks new frontiers for reliably automating complex, end-to-end enterprise workflows with reduced human oversight.

The limitations of conventional AI mean enterprises still require heavy human oversight, hindering true automation of sophisticated processes. Agentic AI promises to radically reshape how work gets done by enabling AI assistants to independently handle responsibilities previously reserved for employees. This is to say that agentic AI could drive immense efficiency gains by automating complex workflows, freeing human workers to focus on higher-value tasks. Agentic AI also enables more optimized, dynamic operations that can adjust in real-time. For leading companies, deploying agentic AI could completely redefine roles, workflows, and human-AI collaboration models.