Question 950 of 997
Applying Generative AI in BusinessmediumMultiple ChoiceObjective-mapped

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 legal department wants to automate contract analysis using GenAI. They need to identify risky clauses and extract key dates. Which Google Cloud service is best suited for this task?

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 enables the creation of custom generative AI agents that can analyze contract text, identify risky clauses, and extract key dates using large language models (LLMs) and retrieval-augmented generation (RAG). It provides a no-code/low-code environment to build agents that leverage enterprise data, making it ideal for automating contract analysis without extensive ML expertise.

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.

  • Document AI

    Why it's wrong here

    Document AI focuses on OCR and document processing, not generative analysis.

  • Vertex AI Agent Builder

    Why this is correct

    Agent Builder allows creating an agent that can ingest contracts, use an LLM for analysis, and extract structured data like clauses and dates.

    Related concept

    Read the scenario before looking for a memorised answer.

  • BigQuery

    Why it's wrong here

    BigQuery is a data warehouse, not designed for document analysis.

  • Model Garden

    Why it's wrong here

    Model Garden provides access to models but does not offer the workflow building needed for contract analysis.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Document AI's structured extraction capabilities with generative AI's ability to perform nuanced risk analysis, leading them to choose Document AI without recognizing that Vertex AI Agent Builder, a Google Cloud service, provides the necessary generative and agentic capabilities for this specific use case.

Detailed technical explanation

How to think about this question

Vertex AI Agent Builder uses a combination of grounding with enterprise data sources (e.g., Cloud Storage, BigQuery, or Vertex AI Search) and LLMs to perform tasks like clause classification and entity extraction. Under the hood, it leverages a conversational agent framework that can invoke custom tools or APIs, enabling the extraction of dates and risk flags via prompt engineering or fine-tuned models. In a real-world scenario, the agent could be configured to flag clauses like 'indemnification' or 'force majeure' and extract dates such as 'effective date' or 'termination date' by using a combination of few-shot prompting and structured output schemas.

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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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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 enables the creation of custom generative AI agents that can analyze contract text, identify risky clauses, and extract key dates using large language models (LLMs) and retrieval-augmented generation (RAG). It provides a no-code/low-code environment to build agents that leverage enterprise data, making it ideal for automating contract analysis without extensive ML expertise.

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.

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Last reviewed: Jul 4, 2026

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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.