From LQWiki

AI-complete is used to describe problems or subproblems in AI, to indicate that the solution presupposes a solution to the ‘strong AI problem’ (that is, the synthesis of a human-level intelligence). A problem that is AI-complete is, in other words, just too hard. The term was invented at MIT and Stanford, by analogy with NP-complete.

Examples of AI-complete problems are ‘The Vision Problem’ (building a system that can see as well as a human) and ‘The Natural Language Problem’ (building a system that can understand and speak a natural language as well as a human). These may appear to be modular, but all attempts so far (2003) to solve them have foundered on the amount of context information and ‘intelligence’ they seem to require.

This article is based, in whole or in part, on entry or entries in the Jargon File.