Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions
A regional insurance provider wants to launch a generative AI claims assistant. The executive sponsor insists the solution be built on a foundation model the company can host inside its own Google Cloud project, with no dependence on a vendor's externally managed endpoint. Which decision does the sponsor need to make first?
⚠ Common exam trap
The trap here is jumping to prompt or data decisions before resolving the hosting and control model that the stated constraint actually targets.
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
✓
Whether to use a fully managed model API or a model whose weights the company can deploy and control itself.
The sponsor's requirement is about where the model executes and who controls the endpoint, which is a hosting and control decision. Choosing between a managed model API and self-deployed model weights shapes architecture, operating cost, and compliance, and every other choice depends on it. Prompt design, user scope, and storage selection are important but subordinate to that first commitment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Whether claim documents should be stored in Cloud Storage or BigQuery.
Why it's wrong here
Storage selection matters for retrieval and analytics, yet it is a data-layer choice independent of whether the model is self-hosted or consumed as a service. Settling storage first does not resolve the hosting constraint and may need to be revisited once the deployment model is known.
- ✗
Which prompt engineering technique will produce the most accurate claim summaries.
Why it's wrong here
Prompt technique affects output quality but presumes a hosting model has already been chosen. Optimizing prompts for an externally managed endpoint would be wasted work if the sponsor later requires self-hosted weights, so this decision is downstream of the hosting question rather than the first thing to resolve.
- ✓
Whether to use a fully managed model API or a model whose weights the company can deploy and control itself.
Why this is correct
The sponsor's constraint is about control over hosting and endpoints, which is fundamentally a build-versus-buy model-hosting decision. Resolving whether the company runs open-weight models on its own infrastructure or consumes a managed API determines architecture, cost model, staffing, and compliance posture, so it must be settled before any other design choice.
- ✗
How many claims adjusters will be granted access to the assistant at launch.
Why it's wrong here
User count influences licensing and capacity planning, but it does not address the sponsor's core requirement about where the model runs. Scoping pilot users is useful later; deciding it first could lock the program into a managed endpoint that cannot satisfy the internal hosting constraint.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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