Google Generative-AI-Leader Exam (page: 2)
Google Generative AI Leader
Updated on: 09-Feb-2026

A company is defining their generative AI strategy. They want to follow Google-recommended practices to increase their chances of success.
Which strategy should they use?

  1. Rapid implementation strategy
  2. Bottom-up strategy
  3. Multi-directional strategy
  4. Top-down strategy

Answer(s): D



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?

  1. Cloud Storage
  2. Model Registry
  3. BigQuery
  4. Vertex AI Pipelines

Answer(s): B



A large e-commerce company with a vast and frequently updated product catalog finds that customers struggle to find products on their website, and support agents spend too much time finding detailed product information. The company wants to improve search accuracy and efficiency for both customers and support.
What Google Cloud solution should they use?

  1. Vertex AI Conversation
  2. Vertex AI Natural Language API
  3. Pre-built RAG with Vertex AI Search
  4. Vertex AI Model Garden

Answer(s): C



The office of the CISO wants to use generative AI (gen AI) to help automate tasks like summarizing case information, researching threats, and taking actions like creating detection rules.
What agent should they use?

  1. Security agent
  2. Data agent
  3. Code agent
  4. Customer service agent

Answer(s): A



A company is developing a conversational AI chatbot. They need to ensure the chatbot can engage in human-like conversations and provide accurate information.
What should they do to enhance thechatbot's ability to understand and respond effectively to user prompts?

  1. Use prompt engineering techniques, like few-shot prompting, to provide the chatbot with examples of successful interactions.
  2. Limit the chatbot's training data to prevent it from learning irrelevant information.
  3. Use strict keyword matching to ensure that the chatbot only responds to specific commands.
  4. Lower model temperature setting to produce more consistent and predictable responses.

Answer(s): A



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?

  1. Google Cloud's pre-trained models and low- and no-code AI tools and services.
  2. Google Cloud's collaborative AI community and support forums connect developers with AI experts.
  3. Google Cloud's comprehensive training materials and tutorials to help developers.
  4. Google Cloud's focus on continuous improvement provides access to the latest AI tools, features, and best practices.

Answer(s): A



A social media platform uses a generative AI model to automatically generate summaries of user- submitted posts to provide quick overviews for other users.
While the summaries are generally accurate for factual posts, the model occasionally misinterprets sarcasm, satire, or nuanced opinions, leading to summaries that misrepresent the original intent and potentially cause misunderstandings or offense among users.
What should the platform do to overcome this limitation of the AI- generated summaries?

  1. Implement stricter safety settings to filter out potentially misinterpreted content altogether.
  2. Increase the temperature parameter of the model to encourage more varied and less literal interpretations.
  3. Decrease the output length of the summaries to make them more concise.
  4. Incorporate a human-in-the-loop (HITL) review process to refine the summaries.

Answer(s): D



An organization with a team of live customer service agents wants to improve agent efficiency and customer satisfaction during support interactions. They are looking for a tool that can provide real- time guidance to agents, suggest helpful information, and streamline the support process without fully automating customer conversations.
Which component of Google's Customer Engagement Suite should they use?

  1. Agent Assist
  2. Conversational Agents
  3. Conversational Insights
  4. Google Cloud Contact Center as a Service

Answer(s): A



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