Free Generative-AI-Leader: Google Cloud Certified - Generative AI Leader Exam Questions and Answers

Last updated: September 19, 2026

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Google

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1000+

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First 10, with answers

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130 mins · 70%

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Multiple choice

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1. Question #1

   A data science team needs a centralized and organized location to store its various model versions, track their metadata, and easily deploy them to the respective applications. What Google Cloud service should they use?

   • A. Cloud Storage
   • B. Model Registry
   • C. BigQuery
   • D. Vertex AI Pipelines
   Reveal Answer

2. Question #2

   A company wants to choose a generative AI (gen AI) use case that will be successful and have the most impact. What key factor should they determine first according to Google Cloud-recommended practices?

   • A. The availability of pre-trained models that are offered on various cloud computing platforms.
   • B. The frequency of updates to the underlying foundation models used by different gen AI platforms.
   • C. The specific business problems the company aims to solve and the desired outcomes.
   • D. The number of employees who will be trained to use the new gen AI tools.
   Reveal Answer

3. Question #3

   An organization wants granular control over who can use and see their generative AI models and related resources on Google Cloud. Which Google Cloud security offering is specifically for this purpose?

   • A. Identity and Access Management
   • B. Secure-by-design infrastructure
   • C. Security Command Center
   • D. Workload monitoring tools
   Reveal Answer

4. Question #4

   A company wants to use an AI agent to automate some tasks. They want everyone to understand the different functions of an AI agent. What is the function of an AI agent in the context of gen AI?

   • A. To provide the computational resources needed to train and run gen AI models.
   • B. To store and manage large datasets used for training and running gen AI models.
   • C. To provide a user-friendly interface for interacting with gen AI models.
   • D. To analyze situations, use multiple tools, and make informed decisions without requiring constant human input.
   Reveal Answer

5. Question #5

   A company wants to use generative AI to create a chatbot that can answer customer questions about their products and services. They need to ensure that the chatbot only uses information from the company's official documentation. What should the company do?

   • A. Use role prompting.
   • B. Adjust the temperature parameter.
   • C. Use prompt chaining.
   • D. Use grounding.
   Reveal Answer

6. Question #6

   A development team is configuring a generative AI model for a customer-facing application and wants to ensure the generated content is appropriate and harmless. What is the primary function of the safety settings parameter in a generative AI model?

   • A. To limit the maximum text length that the model generates by ensuring concise responses.
   • B. To determine the number of tokens the model can process at once by influencing the complexity and length of inputs and outputs.
   • C. To filter out potentially harmful or inappropriate content from the model's output based on the desired level of filtering.
   • D. To control the creativity and randomness of the model's output by adjusting the diversity of word choices.
   Reveal Answer

7. Question #7

   A large multinational corporation with geographically dispersed teams struggles with knowledge silos and inconsistent access to crucial internal information. What is a key business benefit of using Google Agentspace in this scenario?

   • A. Improved IT infrastructure management across offices.
   • B. Seamless knowledge sharing and collaboration across internal systems.
   • C. Enhanced data encryption and compliance for internal communications.
   • D. Automation of employee performance reviews using AI.
   Reveal Answer

8. Question #8

   A company's large learning model (LLM) is producing hallucinations that are a result of the Knowledge cutoff. How does retrieval-augmented generation (RAG) overcome this limitation?

   • A. RAG fine-tunes the LLM on specific customer query patterns to improve the speed andefficiency of response generation.
   • B. RAG enhances the creative writing capabilities of the LLM to generate more engaging and informative responses.
   • C. RAG enables the LLM to retrieve relevant and up-to-date information from knowledge sources.
   • D. RAG uses human oversight to ensure accuracy before presenting information to the customer.
   Reveal Answer

9. Question #9

   A company's development team is eager to start building generative AI solutions with Google Cloud, but has limited experience in AI development. They need to launch their gen AI solution quickly. What Google Cloud benefit would help the company achieve their goal?

   • A. Google Cloud's pre-trained models and low- and no-code AI tools and services.
   • B. Google Cloud's collaborative AI community and support forums connect developers with AI experts.
   • C. Google Cloud's comprehensive training materials and tutorials to help developers.
   • D. Google Cloud's focus on continuous improvement provides access to the latest AI tools, features, and best practices.
   Reveal Answer

10. Question #10

    A software development team wants to use generative AI (gen AI) to code faster so they can launch their software prototype quicker. What should the team do?

    • A. Use gen AI to refactor and optimize existing code.
    • B. Use gen AI to suggest code snippets and complete functions.
    • C. Use gen AI to automatically generate comprehensive documentation for their code.
    • D. Use gen AI to identify potential bugs and security vulnerabilities in their code.
    Reveal Answer