Google Generative AI Leader Practice Exam
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Official Name: Google Generative AI Leader
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Start NowAbout the Google Generative AI Leader Certification
The Google Generative AI Leader certification is designed for professionals who guide organizations in adopting generative AI solutions, understanding their business impact, ethical considerations, and responsible implementation. As technology evolves and industry demands grow more complex; this credential validates your ability to apply real-world skills and knowledge using Google tools and frameworks. Earning the certification positions you as a trusted expert, capable of solving high-impact challenges and contributing to secure, scalable, and efficient systems.
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Test Your Knowledge of Google Generative AI Leader
Question #1
A company wants to leverage generative AI for marketing content creation.
What is the most important first step?
A) Assess use cases and set clear goals for generative AI adoption.
B) Immediately deploy a language model to production.
C) Disable human review of outputs.
D) Ignore copyright considerations.
Solution
Correct answers: A – Explanation:
Assessing use cases and goals ensures alignment and success. Immediate deployment, skipping human review, or ignoring copyright risks problems.
Question #2
The team is concerned about generative AI producing biased results.
What should be implemented?
A) Establish a bias monitoring process and use diverse training data.
B) Only use default datasets.
C) Disable output review.
D) Ignore bias reports.
Solution
Correct answers: A – Explanation:
Proactive monitoring and diverse data reduce bias. Defaults/disabling/ignoring allow bias to persist.
Question #3
The business needs to ensure data privacy when using generative AI.
What is the best practice?
A) Apply data anonymization and restrict access to sensitive information.
B) Use raw customer data without controls.
C) Disable privacy settings.
D) Ignore user consent.
Solution
Correct answers: A – Explanation:
Anonymization and access controls protect privacy. Raw/disabling/ignoring is unsafe.
Question #4
The company wants to measure the ROI of generative AI projects.
What should be done?
A) Define KPIs and track performance against business outcomes.
B) Only measure technical metrics.
C) Disable reporting.
D) Ignore business goals.
Solution
Correct answers: A – Explanation:
KPIs/business outcomes measure real impact. Technical-only/disabling/ignoring misses value.
Question #5
The team must monitor AI-generated content for quality.
What is the best approach?
A) Use human-in-the-loop review and automated quality checks.
B) Only rely on automated checks.
C) Disable quality monitoring.
D) Ignore feedback.
Solution
Correct answers: A – Explanation:
Human/automated review ensures quality. Automation-only/disabling/ignoring is insufficient.
Question #6
The business wants to avoid plagiarism in AI-generated outputs.
What is the recommended solution?
A) Use plagiarism detection tools and train models on original content.
B) Only check if customers complain.
C) Disable checks.
D) Ignore copyright.
Solution
Correct answers: A – Explanation:
Plagiarism detection/original data prevents issues. Complaint-only/disabling/ignoring is risky.
Question #7
The company needs to manage prompt engineering at scale.
What is the best practice?
A) Create a prompt library with version control and best practices.
B) Write new prompts for every use manually.
C) Disable prompt documentation.
D) Ignore copyright considerations.
Solution
Correct answers: A – Explanation:
Prompt libraries/versioning ensure consistency. Manual/disabling/ignoring is inefficient.
Question #8
The team must address hallucinations in AI responses.
What is the best mitigation?
A) Implement validation layers and restrict model responses to verified sources.
B) Allow open-ended outputs.
C) Disable validation.
D) Ignore hallucinations.
Solution
Correct answers: A – Explanation:
Assessing use cases and goals ensures alignment and success. Immediate deployment, skipping human review, or ignoring copyright risks problems.
Question #9
The business wants to scale generative AI across departments.
What should be implemented?
A) Build standardized workflows and provide cross-team training.
B) Let each department work independently.
C) Disable collaboration.
D) Ignore workflow documentation.
Solution
Correct answers: A – Explanation:
Standardization/training enable scale. Independent/disabling/ignoring hinders adoption.
Question #10
The company needs to ensure regulatory compliance in generative AI use.
What is the best strategy?
A) Establish compliance reviews and audit trails for AI outputs.
B) Only review after incidents.
C) Disable audits.
D) Ignore regulations.
Solution
Correct answers: A – Explanation:
Reviews/audits/compliance ensure safety. Incident-only/disabling/ignoring is insufficient.
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