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Updated: Oct 29, 2026

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Google Generative-AI-Leader Exam Syllabus Topics:

TopicDetails
Topic 1
  • Techniques to Improve Generative AI Model Output: This section of the exam measures the skills of AI Engineers and focuses on improving model reliability and performance. It introduces best practices to address common foundation model limitations such as bias, hallucinations, and data dependency, using methods like retrieval-augmented generation, prompt engineering, and human-in-the-loop systems. Candidates are also tested on different prompting techniques, grounding approaches, and the ability to configure model settings such as temperature and token count to optimize results.
Topic 2
  • Fundamentals of Generative AI: This section of the exam measures the skills of AI Engineers and focuses on the foundational concepts of generative AI. It covers the basics of artificial intelligence, natural language processing, machine learning approaches, and the role of foundation models. Candidates are expected to understand the machine learning lifecycle, data quality, and the use of structured and unstructured data. The section also evaluates knowledge of business use cases such as text, image, code, and video generation, along with the ability to identify when and how to select the right model for specific organizational needs.
Topic 3
  • Google Cloud’s Generative AI Offerings: This section of the exam measures the skills of Cloud Architects and highlights Google Cloud’s strengths in generative AI. It emphasizes Google’s AI-first approach, enterprise-ready platform, and open ecosystem. Candidates will learn about Google’s AI infrastructure, including TPUs, GPUs, and data centers, and how the platform provides secure, scalable, and privacy-conscious solutions. The section also explores prebuilt AI tools such as Gemini, Workspace integrations, and Agentspace, while demonstrating how these offerings enhance customer experience and empower developers to build with Vertex AI, RAG capabilities, and agent tooling.
Topic 4
  • Business Strategies for a Successful Generative AI Solution: This section of the exam measures the skills of Cloud Architects and evaluates the ability to design, implement, and manage enterprise-level generative AI solutions. It covers the decision-making process for selecting the right solution, integrating AI into an organization, and measuring business impact. A strong emphasis is placed on secure AI practices, highlighting Google’s Secure AI Framework and cloud security tools, as well as the importance of responsible AI, including fairness, transparency, privacy, and accountability.

Reference: https://cloud.google.com/developers/generative-ai-leader

Google Generative-AI-Leader Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Generative AI Leader
Exam Number:Generative-AI-Leader
Certificate Validity Period:2 years
Real Exam Qty:50-60
Exam Duration:90 minutes
Exam Price:$99 USD
Related Certifications:Google Cloud Professional Machine Learning Engineer
Google Cloud Digital Leader
Available Languages:English
Exam Format:Multiple select, Multiple choice
Recommended Training:Google Cloud Skills Boost - Generative AI learning paths
Exam Registration:Google Cloud Certification Portal
Sample Questions:Google Generative-AI-Leader Sample Questions
Exam Way:Online proctored exam
Pre Condition:No strict prerequisites; basic understanding of cloud computing and AI concepts recommended
Official Syllabus URL:https://cloud.google.com/learn/certification/generative-ai-leader

Google Cloud Certified - Generative AI Leader Sample Questions:

Question #1

An organization needs an AI tool to analyze and summarize lengthy customer feedback text transcripts. You need to choose a Google foundation model with a large context window. What foundation model should the organization choose?

  • A. Gemini
  • B. CodeGemma
  • C. Chirp
  • D. Imagen
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #2

What is a key advantage of using Google's custom-designed TPUs?

  • A. TPUs increase the storage capacity and data retrieval speeds within Google Cloud data centers.
  • B. TPUs are specialized AI processors that excel at parallel processing for machine learning workloads.
  • C. TPUs are primarily designed to improve the general processing speed of virtual machines in the cloud.
  • D. TPUs are lightweight processors intended for deployment on edge devices.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

A company uses a generative AI model to create campaign messaging. However, the newly trained version of the model is more creative but less aligned with the brand voice than the previous version. The marketing team must decide which model to use and potentially revert to the prior model if the new one consistently underperforms in brand alignment. What Google-recommended model management practice should they use?

  • A. Drift monitoring
  • B. Fine-tuning
  • C. Human-in-the-loop (HITL) review
  • D. Model versioning
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #4

A sales manager wants to responsibly use generative AI (gen AI) to increase efficiency with their existing tasks. They want to allow the sales team to focus on building customer relationships and closing deals. How should the sales team use gen AI?

  • A. To analyze customer interactions on social media and automatically generate sales pitches tailored to their public profiles.
  • B. To automate creative content like blog posts and social media updates to attract new leads.
  • C. To draft emails and provide real-time insights about customer needs.
  • D. To replace the sales team's CRM system with a more intuitive and user-friendly interface.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #5

A financial services company receives a high volume of loan applications daily submitted as scanned documents and PDFs with varying layouts. The manual process of extracting key information is time-consuming and prone to errors. This causes delays in loan processing and impacts customer satisfaction. The company wants to automate the extraction of this critical data to improve efficiency and accuracy. Which Google Cloud tool should they use?

  • A. Document AI API
  • B. Dataflow
  • C. Natural Language API
  • D. Vision AI
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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