Build vs. Buy vs. Partner for AI
The build vs. buy decision is wrong the moment it becomes a binary. For AI capabilities, there are three real options — build (own the model and infrastructure), buy (purchase a solution from a vendor), and partner (integrate an API or model where your application layer is still yours). Each involves a fundamentally different long-term position. This skill structures the decision systematically and produces a recommendation with a clear rationale.
---
Context
What the options actually mean in AI:| Option | What you own | What you pay | When it makes sense |
|---|---|---|---|
| Build | Everything — data, model, infrastructure, iteration | High upfront engineering cost; years of ML talent | You have a unique data moat; the capability is core to your product differentiation |
| Buy | Nothing — you use a vendor's end-to-end solution | License fees, vendor lock-in, limited customisation | The capability is not differentiating; speed matters more than control |
| Partner (API) | The application layer — UX, product logic, prompt strategy | Per-token or per-call costs; dependency on provider reliability | The model layer is commodity; you differentiate above it |
---
Step 1 — Define the capability
Ask:
Step 2 — Score the decision criteria
Score each criterion 1–3 for Build, Buy, and Partner: differentiation requirement, data advantage, speed to market, customisation required, cost at scale, engineering capacity, vendor risk tolerance, and compliance/data privacy.
Step 3 — Apply the decision framework
Check scorecard results against strong Build, Partner, and Buy signals with red flags for each option.
Step 4 — Run the total cost of ownership comparison
3-year TCO for all three options including switching costs.
Step 5 — Define the exit strategy
Every AI capability decision must have an exit strategy built in from the start.