In-house AI team vs outsourcing: when does each make sense?

An in-house AI team makes more sense once AI is a core, ongoing part of the product and the company needs deep institutional knowledge built up over time, while outsourcing fits better for a defined project, a skill gap that's temporary, or a company that wants to move fast without the overhead of a full hiring process. Many companies start by outsourcing the first AI feature to validate it works before deciding whether it's worth building a permanent team around.