- A
Select a model with a context window large enough to hold the entire contract
Why wrong: Context size is irrelevant to data privacy; it does not control data retention.
- B
Use a public model endpoint with data encryption in transit
Why wrong: Encryption is necessary but does not prevent the model provider from using the data for training.
- C
Opt out of model logging and data retention in the API settings
Opting out of logging and data retention ensures the provider does not store or train on your data, fulfilling confidentiality.
- D
Use a smaller model to reduce the risk of data memorization
Why wrong: Model size does not guarantee prevention of memorization; proper data governance controls are required.
Question 931 of 997
Generative AI Leader Applying Generative AI in Business Practice Question
This Generative AI Leader practice question tests your understanding of applying generative ai in business. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 company is deploying a GenAI contract analysis system that processes confidential legal documents. They need to ensure that the model does not retain or train on customer data. Which configuration is REQUIRED?
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
✓
Opt out of model logging and data retention in the API settings
Option C is correct because the primary requirement is to prevent the GenAI model from retaining or training on confidential legal documents. Most enterprise GenAI APIs (e.g., OpenAI, Azure OpenAI) provide a data privacy setting that allows customers to opt out of model logging and data retention, ensuring that prompts and responses are not stored or used for model improvement. This configuration directly addresses the compliance need for data confidentiality in contract analysis.
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.
- ✗
Select a model with a context window large enough to hold the entire contract
Why it's wrong here
Context size is irrelevant to data privacy; it does not control data retention.
- ✗
Use a public model endpoint with data encryption in transit
Why it's wrong here
Encryption is necessary but does not prevent the model provider from using the data for training.
- ✓
Opt out of model logging and data retention in the API settings
Why this is correct
Opting out of logging and data retention ensures the provider does not store or train on your data, fulfilling confidentiality.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a smaller model to reduce the risk of data memorization
Why it's wrong here
Model size does not guarantee prevention of memorization; proper data governance controls are required.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse data security measures (encryption, context window, model size) with data privacy controls (opt-out of logging and retention), leading them to select technically valid but irrelevant options for the specific requirement of preventing data retention and training.
Detailed technical explanation
How to think about this question
Under the hood, enterprise GenAI APIs like Azure OpenAI Service offer a 'no training' option via the `data_retention` parameter or a dedicated endpoint (e.g., `POST /openai/deployments/{deployment-id}/completions?api-version=2023-12-01-preview` with `logprobs` disabled). When opted out, the provider must not store prompts or completions beyond the duration needed to generate the response, and must not use them for fine-tuning or model retraining. In a real-world scenario, a legal firm using this configuration can pass entire contracts without violating client confidentiality, even if the model is hosted on a shared infrastructure.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this Generative AI Leader question test?
Applying Generative AI in Business — This question tests Applying Generative AI in Business — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Opt out of model logging and data retention in the API settings — Option C is correct because the primary requirement is to prevent the GenAI model from retaining or training on confidential legal documents. Most enterprise GenAI APIs (e.g., OpenAI, Azure OpenAI) provide a data privacy setting that allows customers to opt out of model logging and data retention, ensuring that prompts and responses are not stored or used for model improvement. This configuration directly addresses the compliance need for data confidentiality in contract analysis.
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.
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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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