hardMultiple Choice
Generative AI Leader Practice Question: A legal firm wants to automate contract analysis
A legal firm wants to automate contract analysis. They need to extract key clauses (e.g., termination, indemnification) from scanned PDFs. The team expects high accuracy and must maintain data privacy. Which combination of services is most suitable?
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 Document AI for OCR and Vertex AI with a custom fine-tuned model for clause extraction
Document AI performs OCR and extracts text from scanned PDFs; Vertex AI with a custom fine-tuned model provides high accuracy for clause extraction while keeping data within the customer's project.
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 AutoML Tables to train a classification model on text features
Why it's wrong here
AutoML Tables classifies structured tabular data, so it cannot parse unstructured scanned PDF text or extract clause spans. It is tempting because it trains custom models without code, and would suit predicting a label from spreadsheet columns such as customer churn. Here, Document Intelligence plus Azure OpenAI achieves clause extraction while keeping data private.
- ✓
Use Document AI for OCR and Vertex AI with a custom fine-tuned model for clause extraction
Why this is correct
Document AI performs OCR on scanned PDFs, converting them to structured text, while Vertex AI trains a fine-tuned model on the firm's clause examples for accurate extraction. Processing stays within the firm's Google Cloud project, satisfying the data privacy constraint.
- ✗
Use Gemini API directly with a prompt to analyze PDFs
Why it's wrong here
The Gemini API accepts native PDF input, but scanned documents require OCR before clause extraction, which a raw prompt does not provide. It is tempting because the API handles text-based PDFs well and suits rapid prototyping where documents are already machine-readable and privacy constraints are minimal.
- ✗
Use AppSheet to create a form for manual entry and then use BigQuery ML
Why it's wrong here
AppSheet forms and BigQuery ML handle manual data capture and model training, not clause extraction from scanned PDFs, and manual entry breaks the automation requirement. It is tempting because both services are low-code and privacy-friendly, but document understanding needs Azure AI Document Intelligence with a language model.
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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.