  This paper provides a new framework for studying the impact of Artificial
Intelligence (AI) on the organization of knowledge work. We incorporate AI into
an economy where humans endogenously form hierarchical firms: Less
knowledgeable agents become "workers" solving routine problems, while more
knowledgeable agents become "solvers" handling exceptions. We model AI as an
algorithm that uses compute to mimic humans. We compare the equilibrium before
and after AI's introduction, distinguishing between "basic" AI (with knowledge
equivalent to pre-AI workers) and "advanced" AI (with knowledge equivalent to
pre-AI solvers). We show that basic AI increases the knowledge content of human
work, leading to smaller, less productive, and less decentralized firms. In
contrast, advanced AI decreases the knowledge content of human work, resulting
in larger, more productive, and more decentralized firms. In any case, the most
knowledgeable humans benefit from AI, while the least knowledgeable benefit
only when AI is sufficiently advanced. We discuss how these effects depend on
AI's autonomy and the availability of compute.
