Intro · 1:22
Scaling AI without chaos
The goal: an AI strategy that scales without disconnected agents, duplicated effort or governance gaps.
- The risk at scale is disconnected agents, duplication and governance gaps.
- Objectives: follow the AI adoption process and design an operating model for agents.
- Balance speed of delivery with control.
| Risk | Remedy |
|---|---|
| Disconnected agents | Shared strategy |
| Duplicated effort | Central catalog |
| Governance gaps | Operating model |
Do this in your own tools, step by step. Ticks are saved on this device.
What are the three scaling risks?
Disconnected agents, duplicated effort and governance gaps.
What must the operating model balance?
Speed of delivery and control.
0:00 And in this video we'll cover the AI adoption process, how to design a strategy for building agents, when to use single-agent or multi-agent approaches, and how to decide between prebuilt, extended, and custom AI solutions. Let's get started. By the end of this video, you'll be able to do two critical things: first, map the cloud adoption frameworks, AI adoption phases to the AI agent lifecycle, giving you a structured roadmap for bringing AI agents into your organization. Second, design an enterprise-ready operating model for AI agents, one that balances speed of delivery with governance and security.
0:52 These are not just theoretical skills. As an agentic AI architect, we need to connect business strategy to technical execution. Whether you are deploying a simple Software as a Service copilot or orchestrating a fleet of custom agents, the frameworks we cover here will help you make
Get the other 9 chapters, the exam and your certificate for LinkedIn, plus all 700+ AI courses.