Buy vs Build Decision Framework
A practical framework to prevent expensive AI mistakes—especially when the “right” answer changes after year one.
Interactive worksheet
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What this helps you decide
- Decide whether to buy a tool, build a system, combine both, or pause.
- Clarify what is truly “core” vs. what is generic capability.
- Surface ownership and failure modes before signing contracts.
When to use it
- You’re evaluating chatbot/automation vendors and prices don’t reflect real ownership cost.
- You have internal data/process constraints that off‑the‑shelf tools won’t respect.
- You want to avoid rebuilding a workflow twice.
The framework
Core questions
- Is this core to your differentiation, or is it a commodity capability?
- Will this require ongoing judgment, or is it mostly repeatable rules + exceptions?
- What breaks if the model changes (pricing, behavior, limits, features)?
- Who owns failure—operationally and reputationally?
- What’s the real cost after year one (licenses, maintenance, monitoring, training)?
Recommendation paths
- Buy: when the capability is standard, integration needs are light, and failure is low‑impact.
- Build: when it’s core, workflows are unique, and you need control over data + logic.
- Hybrid: buy a reliable component, build your routing/governance around it.
- Don’t do either yet: when the workflow isn’t stable enough to automate safely.
Common mistakes
- Buying a tool to “solve process” (tools amplify whatever process exists).
- Building too early without clear requirements and ownership.
- Ignoring what happens when accuracy drops or a vendor changes terms.
What this does NOT answer
- Exactly which vendor to choose (use the Vendor Evaluation framework for that).
- Whether AI should make accountable decisions for you (it shouldn’t).
If you want a grounded recommendation path for your specific workflow, the AI Automation Audit scopes what’s worth building, buying, or postponing.
