Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions
A financial institution wants to deploy a generative AI solution for contract analysis. They need to ensure compliance with regulations. Which approach is best?
⚠ Common exam trap
Google Cloud often tests the misconception that retrieval-augmented generation (RAG) alone is sufficient for domain-specific compliance, when in fact it requires fine-tuning or strict validation to prevent misinterpretation of retrieved legal texts.
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
✓
Fine-tune a model on a curated dataset of past contracts and implement human-in-the-loop review
Best because fine-tuning on a curated dataset of past contracts ensures the model learns domain-specific language and compliance patterns, while human-in-the-loop review provides a critical safety net for regulatory adherence. This combination directly addresses the need for accuracy and accountability in contract analysis, where errors can have legal consequences.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy a large open-source model fine-tuned on public legal documents
Why it's wrong here
Public legal documents may not cover the institution's specific contracts, and fine-tuning alone lacks human oversight.
- ✗
Use a general-purpose pre-trained model with no modifications to minimize risk
Why it's wrong here
Without fine-tuning, the model may produce legally unsound outputs that fail compliance checks.
- ✓
Fine-tune a model on a curated dataset of past contracts and implement human-in-the-loop review
Why this is correct
Fine-tuning on relevant data improves accuracy, and human review catches any regulatory violations before finalization.
- ✗
Implement retrieval-augmented generation (RAG) with the company's legal document database
Why it's wrong here
RAG helps but still relies on the base model's generation, which could misinterpret retrieved information.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.