Agentic AI

Agentic AI is a type of artificial intelligence that goes beyond following fixed rules or responding to prompts. It uses multiple AI agents, often powered by large language models, to plan, act, learn, and improve on its own [1][5]. These agents can break down big goals into smaller tasks, collaborate with other tools, and adapt their strategies based on new information. For example, agentic AI can optimize business processes, manage customer support, or automate software development by making decisions and taking actions without constant human oversight.

• Acts with autonomy and initiative
• Adapts to changing conditions
• Handles multi-step, complex workflows

Understanding agentic AI is crucial because it enables automation of complex, dynamic tasks that traditional AI or rule-based systems cannot handle. This technology helps organizations become more efficient, adaptable, and competitive by allowing AI to make decisions and act independently in real-world scenarios.

Agentic AI works by coordinating several AI agents to achieve broader objectives. In practice, it can automate tasks like scheduling, customer service, or marketing campaigns. For instance, an agentic AI system might deploy marketing materials, track their performance, and adjust strategies automatically . These systems use techniques like machine learning, natural language processing, and reinforcement learning to learn from their environment and improve over time . Businesses can integrate agentic AI into their operations to streamline workflows, reduce manual effort, and respond quickly to new challenges.

A retail company uses agentic AI to manage its inventory. The system monitors sales data, predicts demand, and automatically orders new stock when needed. If a supplier is delayed, the AI finds alternatives and updates delivery schedules, all without human intervention. This ensures shelves are stocked and customers are satisfied, demonstrating agentic AI’s ability to handle complex, real-time business challenges.