Chapter 2 of 4 · Google Cloud Generative AI Leader
Google Cloud's gen AI offerings
Google Cloud's AI strengths, Gemini apps, customer experience tools, Agent Platform, RAG and agent tooling.
- 6topics
- 24 minfast track
- 3diagrams and exhibits
- 35%of the exam
Topics in this chapter
Take them in order, or jump to the one you need.
- 1Google Cloud's Strengths in Gen AIGoogle Cloud's gen AI strengths: an AI-first approach, an enterprise-ready platform, an integrated ecosystem, an open approach…4 min
- 2Data Control and Democratized AI DevelopmentHow Google Cloud's AI platform keeps customers in control of their data, and how low-code and no-code tools, pre-trained models…4 min
- 3Gemini App, Gemini Enterprise and Gemini for Google WorkspaceFunctionality, use cases and business value of the Gemini app and Gemini Advanced with Gems, Gemini Enterprise, and Gemini for…Diagram4 min
- 4Agent Search and Customer Engagement SuiteHow Agent Search, Google Search grounding and the Customer Engagement Suite, from Conversational Agents to Agent Assist, improve…Diagram4 min
- 5Building with Agent Platform and RAGHow developers build with Gemini Enterprise Agent Platform: Model Garden, Agent Search, AutoML, prebuilt RAG and RAG APIs, and…Diagram4 min
- 6Agent Tooling, Agent Studio and Google AI StudioHow gen AI agents use extensions, functions, data stores and plugins, which Google Cloud APIs act as tools, and Agent Studio…4 min
About this chapter
What this chapter covers
This is the largest section of the exam, worth about 35 percent. It covers Google Cloud's strengths in gen AI (AI-first approach, enterprise-ready platform, ecosystem, openness, AI-optimized infrastructure, data control and democratized development), prebuilt offerings for AI-powered work (the Gemini app, Gemini Enterprise, Gemini for Google Workspace), offerings that improve the customer experience (Agent Search, Google Search grounding, Customer Engagement Suite), how developers build with AI (Agent Platform, Model Garden, AutoML, RAG offerings, custom agents) and tooling for gen AI agents (extensions, functions, data stores, plugins, Google Cloud APIs, Agent Studio and Google AI Studio).
The core skill is matching a business need to the right offering, and knowing when to buy a prebuilt solution and when to build.
How the topics fit together
- Google Cloud's strengths in gen AI covers AI-first innovation, the enterprise-ready platform, ecosystem, openness and infrastructure.
- Data control and democratized AI covers how the platform keeps customers in control and opens AI to more people.
- Gemini app, Gemini Enterprise and Gemini for Google Workspace covers the prebuilt offerings for employees.
- Agent Search and Customer Engagement Suite covers customer-facing search and contact center offerings.
- Building with Agent Platform and RAG covers Model Garden, AutoML, RAG offerings and custom agents.
- Agent tooling, Agent Studio and Google AI Studio covers how agents use tools and which studio to choose.
Ask "who is the user?" Employees point to the Gemini app, Gemini Enterprise or Workspace. Customers point to Agent Search or the Customer Engagement Suite. Developers point to Agent Platform.
How to use these pages
Each topic page has the same shape, so you can skim for what you need.
- What it is: the idea in plain words.
- How it works: the mechanism, with examples and tables.
- What to remember for the exam: the facts to memorise and how questions are phrased.
- Common mistakes: the classic traps.
- Check yourself: three questions to test your understanding.
Ready for more practice?
The full Google Cloud Generative AI Leader question bank has 512 questions, with timed practice exams and an explanation for every answer.
This study guide is independent and is not affiliated with, endorsed by, or sponsored by Google Cloud. Vendor names, certification names and exam codes are trademarks of their respective owners and are used for identification only.