An internal AI review board has exactly two failure modes: it approves everything, in which case it is theatre, or it becomes the reason nothing ships, in which case teams route around it and it is worse than theatre. Both are avoidable, and the avoidance is mostly about latency.
What a board is for
Not to decide whether AI is a good idea, and not to re-litigate a technology choice per project. A board exists to do three things that nobody inside a single team can do.
Give one answer. Two teams asking the same question about the same data class must get the same answer, or the policy is not a policy. Consistency is the whole product.
See the aggregate. Six individually reasonable projects can add up to a data flow nobody would have approved as a whole, or to a dependency on one supplier that nobody chose deliberately. Only a central view notices.
