Agentic AI Systems

Agentic systems mark the beginning of a new era in computing—one where software doesn’t just follow instructions, but actively learns, adapts, and takes initiative. These systems help businesses move faster, get more done, and deliver more personalized experiences at scale. By putting autonomous agents to work across teams, companies can boost productivity, accelerate decision making, and tailor services in real time. This shift from traditional software to agentic systems is driving exponential demand for compute and orchestration, as always-on AI agents become deeply embedded in day-to-day operations.

An agentic AI system is a collection of agents that reason, plan, and act autonomously – while remaining governed and controlled.

An agent is an AI-powered component capable of making decisions, taking actions, and adapting to context in pursuit of a goal. Agentic systems combine multiple agents to solve complex tasks collaboratively—sharing context, delegating work, and responding to dynamic environments.

Unlike traditional AI assistants that follow predefined workflows or respond to user prompts, agentic systems are proactive, goal-driven, and capable of coordinating across tools, data sources, and constraints—while staying aligned with human intent.

Architecturally, agentic AI systems are orchestrated services that maintain conversational context, manage state across interactions, and dynamically adapt to evolving user inputs and environmental interactions. They require seamless coordination between AI models, business rules, data sources, and real-time events — all while preserving long-term memory and intent.