Build vs Buy for AI: Choose Without Creating Strategic Debt

Decompose the system before choosing

Assign strategic value, available products, risk, skills, interfaces, and exit needs to each layer rather than labelling the whole solution build or buy.

Compare TCO for build, buy, and hybrid

Model delivery, licence, tokens, integration, data, security, review, operations, change, scaling, support, and exit over several volume horizons.

Choose prompt, API, RAG, or fine-tuning deliberately

Use prompting for instruction, RAG for changing private knowledge with sources, fine-tuning for repeatable behaviour or format when justified, and model training only with a distinct evidence-based need.

Perform SaaS and model due diligence

• Data use and retention.
• Security and access.
• Quality and evaluation.
• SLA, support, and price change.
• Export, termination, and replacement.

Build realistic portability

Own prompts, evaluation sets, business rules, interfaces, and data exports. Avoid expensive abstraction across suppliers unless a measured risk justifies it.

Make the decision reviewable

Record assumptions and triggers such as volume, price, quality, regulation, capability, or supplier change that require a new review.