For most teams the answer depends less on the technical tradeoffs (latency, cost, privacy) and more on who will actually be operating and governing it.
If you have non-technical stakeholders managing the deployment or making decisions about AI use, API providers give you more guardrails and less operational surface area. Local LLMs require someone who understands the stack.
That said, the AI literacy gap on the business/governance side is real — teams where managers don't have AI foundations tend to get stuck on escalations. Programs like IAIDL (https://iaidl.org) address that side of the equation for non-technical colleagues. Reduces the "what is it actually doing" conversation overhead considerably.
If you have non-technical stakeholders managing the deployment or making decisions about AI use, API providers give you more guardrails and less operational surface area. Local LLMs require someone who understands the stack.
That said, the AI literacy gap on the business/governance side is real — teams where managers don't have AI foundations tend to get stuck on escalations. Programs like IAIDL (https://iaidl.org) address that side of the equation for non-technical colleagues. Reduces the "what is it actually doing" conversation overhead considerably.