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Generative AI Leader Practice Question: An enterprise is evaluating whether to build a…
An enterprise is evaluating whether to build a custom fine-tuned model or use a pre-built API for code generation. Which three factors should they consider in the build vs. buy decision? (Choose THREE)
⚠ Common exam trap
The trap is that candidates pick operational or cost-related factors (developer seats, legacy system compatibility) instead of the strategic factors (privacy, customization, model availability) that actually drive the build-vs-buy decision.
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
✓
Data privacy and security requirements
Option A (Data privacy and security requirements) is correct because a build decision is often driven by the need to keep proprietary source code and sensitive data within the organization's own environment, whereas a pre-built API may send prompts and code to a third-party provider, raising data-residency, retention, and compliance concerns. Option D (Level of customization needed for the organization's coding standards) is correct because fine-tuning a custom model allows tailoring to internal style guides, frameworks, and domain-specific APIs, while a generic pre-built API may not align with those standards. Option E (Availability of pre-built models for the specific programming language) is correct because if a suitable pre-built model already supports the target language well, buying is more efficient, whereas a lack of adequate pre-built support pushes the decision toward building. Option B (Number of developer seats) is not a primary build-vs-buy factor because seat count mainly affects licensing cost and scaling, not the fundamental capability or control trade-off. Option C (Compatibility with on-premises legacy systems) is not a core factor because integration can typically be handled through APIs or gateways regardless of whether the model is built or bought.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Data privacy and security requirements
Why this is correct
Where source code cannot leave the tenant or reach third-party endpoints, a hosted API may be disqualified, pushing the decision toward a self-hosted or fine-tuned model. Data privacy and security requirements thus directly constrain the build-versus-buy choice.
- ✗
Number of developer seats in the organization
Why it's wrong here
Developer seat count is a licensing and cost input, not a build-versus-buy factor; the decision turns on data sensitivity, customisation needs and total cost of ownership. It is tempting because seat numbers drive API subscription pricing, which matters when comparing vendor contracts.
- ✗
Compatibility with on-premises legacy systems
Why it's wrong here
On-premises legacy compatibility rarely decides build versus buy for code generation, since both fine-tuned and API models are consumed over network endpoints. It is tempting in organisations with mainframe or air-gapped estates, where deployment locality genuinely constrains model hosting choices.
- ✓
Level of customization needed for the organization's coding standards
Why this is correct
Fine-tuning lets a model internalise proprietary style guides, naming conventions and review rules that generic APIs cannot enforce. The degree of customisation required for the organisation's coding standards therefore directly determines whether building outweighs buying.
- ✓
Availability of pre-built models for the specific programming language
Why this is correct
Pre-built models often already excel at popular languages, so strong existing coverage weakens the case for fine-tuning. This factor directly informs the build-versus-buy decision by revealing whether a purchased API already meets the code-generation need.
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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
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.