GAIL syllabus

4 domains and 64 topics, updated November 2026

The Generative AI Leader exam is a business-level test of what generative AI can do, which Google Cloud products fit which need, how to improve model output, and how to run AI initiatives securely and responsibly. It needs no coding. This outline follows the four sections of the official exam guide. Tick topics off as you cover them. Your ticks are saved in this browser.

This outline follows the official GAIL exam guide (PDF). Check it for the exact wording.

Fundamentals of generative AI

30%

Core gen AI vocabulary, machine learning basics, data, the layers of the AI landscape and Google's foundation models. About 30% of the exam.

Core concepts
Machine learning lifecycle
Choosing a foundation model
Business use cases
Data for gen AI
Layers of the gen AI landscape
Google's foundation models

Google Cloud’s generative AI offerings

35%

Google Cloud's strengths and products for gen AI: prebuilt apps, customer experience, the developer platform, RAG and agent tooling. The largest domain, about 35%.

Google Cloud's strengths
Prebuilt gen AI for work
Customer experience offerings
Building with Agent Platform
Tooling for agents

Techniques to improve model output

20%

Limitations of foundation models and the techniques that fix them: grounding, RAG, prompting, tuning, oversight and sampling settings. About 20% of the exam.

Foundation model limitations
Monitoring and evaluation
Prompt engineering
Grounding
Sampling parameters and settings

Business strategies for generative AI

15%

Choosing, rolling out and measuring gen AI, plus secure and responsible AI. About 15% of the exam.

Implementing a gen AI solution
Secure AI
Responsible AI