- A
Enable Access Transparency logs
Why wrong: Access Transparency logs provide visibility into data access by Google, but do not prevent model improvement. Audit logging of predictions is separate.
- B
Use a shared VPC network
Why wrong: Shared VPC does not address the specific requirements of data usage for model improvement or audit logging.
- C
Use VPC Service Controls to restrict data access
Why wrong: VPC Service Controls are for data exfiltration prevention, not for preventing model improvement.
- D
Enable Customer-Managed Encryption Keys (CMEK) for the AI services
CMEK gives the customer control over encryption keys, an additional security measure, and is often required for compliance.
- E
Disable data logging in the AI services' project-level settings
Disabling data logging ensures customer data is not used to improve Google's models.
Generative AI Leader Google AI Ecosystem and Strategy Practice Question
This Generative AI Leader practice question tests your understanding of google ai ecosystem and strategy. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 healthcare company wants to use Google Cloud AI services for analyzing medical images and patient records. They need to ensure data is not used to improve Google's models and that all model predictions are logged for audit. Which TWO configurations must be implemented? (Choose TWO)
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
Enable Customer-Managed Encryption Keys (CMEK) for the AI services
Option D is correct because Customer-Managed Encryption Keys (CMEK) allow the healthcare company to control the encryption keys used to protect their data at rest in Google Cloud AI services. This ensures that Google cannot access the data for model improvement, as the data remains encrypted under keys managed by the customer. Option E is correct because disabling data logging in the AI services' project-level settings prevents the service from collecting and storing input data or predictions, which is a direct way to ensure data is not used to improve Google's models and that audit requirements are met by controlling what is logged.
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.
- ✗
Enable Access Transparency logs
Why it's wrong here
Access Transparency logs provide visibility into data access by Google, but do not prevent model improvement. Audit logging of predictions is separate.
- ✗
Use a shared VPC network
Why it's wrong here
Shared VPC does not address the specific requirements of data usage for model improvement or audit logging.
- ✗
Use VPC Service Controls to restrict data access
Why it's wrong here
VPC Service Controls are for data exfiltration prevention, not for preventing model improvement.
- ✓
Enable Customer-Managed Encryption Keys (CMEK) for the AI services
Why this is correct
CMEK gives the customer control over encryption keys, an additional security measure, and is often required for compliance.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Disable data logging in the AI services' project-level settings
Why this is correct
Disabling data logging ensures customer data is not used to improve Google's models.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse VPC Service Controls (which prevent data exfiltration) with data usage controls for model training, or they think Access Transparency logs are sufficient for audit logging of predictions, when in fact they only log administrative actions, not model outputs.
Detailed technical explanation
How to think about this question
CMEK integrates with Google Cloud Key Management Service (KMS) to wrap data encryption keys (DEKs) using a customer-managed key encryption key (KEK), ensuring that even Google's AI services cannot decrypt the data without the customer's key. Disabling data logging at the project level for AI services like Vertex AI or Healthcare API prevents the collection of request/response pairs, which is a common requirement for HIPAA compliance and for ensuring that model training does not occur on customer data. In practice, many healthcare organizations combine CMEK with data logging controls to meet both data sovereignty and audit trail requirements, as logging can be redirected to a separate project with restricted access.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
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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Google AI Ecosystem and Strategy — study guide chapter
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FAQ
Questions learners often ask
What does this Generative AI Leader question test?
Google AI Ecosystem and Strategy — This question tests Google AI Ecosystem and Strategy — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable Customer-Managed Encryption Keys (CMEK) for the AI services — Option D is correct because Customer-Managed Encryption Keys (CMEK) allow the healthcare company to control the encryption keys used to protect their data at rest in Google Cloud AI services. This ensures that Google cannot access the data for model improvement, as the data remains encrypted under keys managed by the customer. Option E is correct because disabling data logging in the AI services' project-level settings prevents the service from collecting and storing input data or predictions, which is a direct way to ensure data is not used to improve Google's models and that audit requirements are met by controlling what is logged.
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.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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