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Generative AI Leader Practice Question: Deploying a GenAI application that must meet SOC…
A company is deploying a GenAI application that must meet SOC 2 compliance. Which three Google Cloud offerings can be used in a compliant manner? (Choose three.)
⚠ Common exam trap
Google often tests the misconception that any free-tier or consumer-grade Google AI tool (like Colab or AI Studio) can be used for compliance, when in fact only enterprise-grade services within a properly configured Google Cloud environment meet SOC 2 requirements.
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
✓
Vertex AI
Vertex AI (C) is a fully managed, enterprise-grade Google Cloud service covered by SOC 2 attestation, with data residency, CMEK, VPC Service Controls, and IAM controls that let a GenAI workload run compliantly. Document AI (D) is likewise a Google Cloud enterprise service included in Google's SOC 2 report scope, so processing documents through its processors satisfies the compliance requirement. BigQuery ML (E) runs inside BigQuery, which is a SOC 2-attested Google Cloud service, allowing model training and inference on governed data with Cloud IAM, audit logging, and CMEK. Colab consumer (A) and the free tier of Google AI Studio (B) are consumer-oriented offerings whose terms and controls do not provide the SOC 2 enterprise assurances required for this deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Colab (consumer version)
Why it's wrong here
The consumer Colab version runs on personal Google accounts without the enterprise data-processing commitments, audit logging or administrative controls SOC 2 attestation requires. It is tempting because Colab provides free hosted notebooks for prototyping GenAI models, which suits individual experimentation rather than a compliance-scoped production workload.
- ✗
Google AI Studio (free tier)
Why it's wrong here
The free tier of Google AI Studio lacks the enterprise terms, data residency guarantees and auditability that SOC 2 evidence collection demands. It is tempting because AI Studio offers quick prompt prototyping against Gemini models, which is fine for evaluation, but not for processing regulated production data.
- ✓
Vertex AI
Why this is correct
Vertex AI operates under Google Cloud's SOC 2 attested controls, covering data handling, access management and audit logging for GenAI workloads. It satisfies the stem's compliance requirement by providing the certified platform on which models are trained, deployed and governed.
- ✓
Document AI
Why this is correct
Document AI is covered by Google Cloud's SOC 2 attestation, so document processing and extraction workloads inherit those audited controls. It meets the stem's compliance constraint by processing sensitive documents within a certified service boundary.
- ✓
BigQuery ML
Why this is correct
BigQuery ML runs model training and prediction inside BigQuery, which is covered by Google Cloud's SOC 2 attestation. It satisfies the stem's compliance requirement by keeping data and model operations within an audited service boundary.
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JA
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.