- A
Cloud Functions
Why wrong: Cloud Functions requires manual integration with AI services and more coding, not the easiest managed option.
- B
Compute Engine with custom containers
Why wrong: Compute Engine requires full infrastructure management, contrary to the minimal management requirement.
- C
Google Chat API
Why wrong: Google Chat API is for chat apps, not for building summarization pipelines.
- D
Vertex AI Agent Builder
Vertex AI Agent Builder offers a managed, serverless environment to build generative AI pipelines, ideal for summarization.
Question 9 of 997
Generative AI Leader Applying Generative AI in Business Practice Question
This Generative AI Leader practice question tests your understanding of applying generative ai in business. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to add a GenAI-powered meeting summarization feature to their internal app. They have existing meeting transcript data in Cloud Storage. Which Google Cloud service should they use to build the summarization pipeline with minimal infrastructure management?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Vertex AI Agent Builder
Vertex AI Agent Builder is the correct choice because it provides a managed, serverless platform specifically designed for building GenAI-powered applications like meeting summarization. It integrates directly with existing data sources (e.g., Cloud Storage transcripts), offers pre-built models for summarization, and handles infrastructure scaling, security, and monitoring automatically, minimizing operational overhead.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud Functions
Why it's wrong here
Cloud Functions requires manual integration with AI services and more coding, not the easiest managed option.
- ✗
Compute Engine with custom containers
Why it's wrong here
Compute Engine requires full infrastructure management, contrary to the minimal management requirement.
- ✗
Google Chat API
Why it's wrong here
Google Chat API is for chat apps, not for building summarization pipelines.
- ✓
Vertex AI Agent Builder
Why this is correct
Vertex AI Agent Builder offers a managed, serverless environment to build generative AI pipelines, ideal for summarization.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google often tests the misconception that any serverless compute (like Cloud Functions) can easily handle AI workloads, but the trap here is that Cloud Functions lacks native GenAI integration and would require significant custom code and external API calls, whereas Vertex AI Agent Builder is purpose-built for such tasks with minimal management.
Detailed technical explanation
How to think about this question
Vertex AI Agent Builder leverages the underlying Vertex AI platform, which uses foundation models like PaLM 2 or Gemini for text generation, and supports Retrieval-Augmented Generation (RAG) to ground summaries in the specific meeting transcript data. Under the hood, it can automatically chunk and index transcripts from Cloud Storage using Vertex AI Search, then apply a summarization prompt via a managed endpoint, handling model versioning and scaling without manual intervention. In a real-world scenario, this allows a company to deploy a summarization feature that respects access controls and meets latency requirements without building custom ML pipelines.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
What to study next
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FAQ
Questions learners often ask
What does this Generative AI Leader question test?
Applying Generative AI in Business — This question tests Applying Generative AI in Business — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Vertex AI Agent Builder — Vertex AI Agent Builder is the correct choice because it provides a managed, serverless platform specifically designed for building GenAI-powered applications like meeting summarization. It integrates directly with existing data sources (e.g., Cloud Storage transcripts), offers pre-built models for summarization, and handles infrastructure scaling, security, and monitoring automatically, minimizing operational overhead.
What should I do if I get this Generative AI Leader question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
This Generative AI Leader practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Generative AI Leader exam.
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