Generative AI Leader Fundamentals of Generative AI Practice Question
A financial services firm is deploying a generative AI model to answer customer questions about investment products. They need to ensure that the model's responses comply with regulatory requirements and do not provide personalized financial advice. Which approach should they take?
⚠ Common exam trap
The trap here is assuming that fine-tuning is necessary for compliance, when in fact a well-designed system prompt can enforce behavioral constraints more directly and flexibly.
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
✓
Use a system prompt that instructs the model to avoid giving personalized advice and to include disclaimers.
Using a system prompt is an effective way to set guardrails for the model's behavior. By explicitly instructing the model to avoid personalized financial advice and to include necessary disclaimers, the firm can help ensure compliance with regulations. This approach is flexible and can be updated as regulations change, unlike fine-tuning which requires retraining.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use a system prompt that instructs the model to avoid giving personalized advice and to include disclaimers.
Why this is correct
A system prompt sets the overall behavior and constraints for the model. By instructing the model to avoid personalized advice and include disclaimers, the firm can enforce compliance at the prompt level. This is a flexible and immediate way to guide the model's responses without modifying the model itself.
- ✗
Fine-tune the model on a dataset of compliant financial conversations.
Why it's wrong here
Fine-tuning can teach the model to mimic compliant responses, but it does not guarantee that the model will never provide personalized advice in novel situations. It is also time-consuming and may not cover all regulatory nuances. A system prompt provides more direct and updatable control.
- ✗
Deploy the model with a high temperature to encourage diverse responses.
Why it's wrong here
High temperature increases randomness and creativity, which is the opposite of what is needed for compliance. It would make the model more likely to generate unpredictable and potentially non-compliant responses. For regulatory compliance, deterministic and controlled outputs are preferred.
- ✗
Limit the model's responses to a predefined set of FAQs.
Why it's wrong here
Limiting responses to FAQs can ensure compliance but severely restricts the model's usefulness for answering a wide range of customer questions. It is not a scalable solution and may frustrate customers. A system prompt allows the model to handle diverse queries while still enforcing compliance guidelines.
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Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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