AI is entering a new phase, one defined by agents that can reason, plan, and act across complex workflows. For business leaders, this means the next competitive edge won’t come from using AI tools, but from orchestrating systems of AI agents that work together toward business outcomes.

Andrew Ng’s brand new course, Agentic AI, offers a timely roadmap for this transition. It bridges the gap between today’s LLM-powered chat interfaces and tomorrow’s autonomous multi-agent systems.

The timing aligns perfectly with OpenAI’s recent AgentKit launch and the rise of tools like Replit Agents and Anthropic Projects. As companies build with these frameworks, leaders must know how to integrate them responsibly and strategically. Agentic AI gives you the conceptual foundation to lead those conversations.

From Automation to Autonomy

Traditional AI automates individual tasks. Agentic AI shifts the focus to goal-directed autonomy—systems that can decompose problems, use tools, and collaborate with both humans and other agents.

For leaders, this evolution changes how you think about workflows, responsibility, and innovation.

The Leadership Imperative

Andrew Ng explains how organizations can move beyond “AI projects” to AI architectures—deployments that are adaptive, modular, and continuously improving.

If you lead marketing, operations, or product teams, this course helps you:

1. Understand what’s different about agentic systems versus traditional AI.

2. Identify where agent-based architectures can reduce cycle time or decision friction.

3. Prepare teams for agent evaluation and governance, including trace grading and feedback loops.

Check out Andrew Ng's new AI Agents course here.