Organizing Intelligence

Alex Imas, Andrew Koh, Shane Legg · Google DeepMind · 29 Oct 2026

Where this sits in the debate

Will AI destroy more jobs than it creates? · its finding: it depends (why studies differ)
Will AI widen inequality? · its finding: it depends (why studies differ)
How fast will the impact arrive? · its finding: it depends (why studies differ)

Direction of the finding as read from the abstract by an AI model (AI-written).

Key takeaway AI-written

A theoretical model of how humans and AI agents sort into competing firms, separating competence (which raises productivity levels) from coordination (which sets how productivity scales with firm size). It finds that teams of complementary humans can beat more capable AI, that better AI competence can shrink firms, and that better AI coordination can trigger a sudden shift to large AI-heavy firms, with wage effects split into a technology effect and a reorganization effect that can reverse it.

The paper in three steps AI-written

Written by an AI agent from the paper's abstract, which is the primary source and is quoted below.

The question

How do improvements in AI capability change market structure, productivity, employment and wages once firms can mix humans and AI agents?

The approach

An equilibrium model in which agents with multidimensional capabilities sort into competing firms; competence shifts productivity levels while coordination governs how productivity scales with size, and AI is reproducible at the cost of compute.

The findings

Organizations of complementary humans can outperform AI that beats the average human. Higher AI competence can change firm composition and reduce firm size; better AI coordination can break the ceiling on firm size and cause a phase transition to concentrated AI-heavy firms. Employment changes are gradual or sudden depending on the mechanism.

How to read it: theory. A theoretical model — its value is the mechanism it isolates; ask whether the assumptions fit the real economy.

Limitations and counterpoints AI-written

A theoretical model; results follow from its assumptions about capability profiles and coordination and are not estimated from economic data.

Source excerpt

When will advances in AI lead to economic transformation? We develop a model of how intelligence, the ability to achieve goals, matters for organizations, the key unit of economic production. Agents (human or AI) with multidimensional capabilities sort endogenously into competing firms. A firm's productivity depends on its agents' capabilities; we distinguish competence, which shifts productivity levels, from coordination, which governs how productivity scales with size. Two differences between AI and humans drive transformation: AI expertise is reproducible while humans' are in fixed supply, and AIs may not face the same limits for coordination as humans. We analyze how equilibrium market structure, productivity, employment, and wages evolve as AI capabilities improve. When AI is more capable than the average human, organizations of complementary humans can nonetheless outperform AI. Increases in AI competence can change the composition of workers within firms and decrease firm size. As AI coordination improves, however, this can break the Coasean ceiling on firm size and the market structure undergoes a phase transition toward large, concentrated AI-heavy firms. Changes in human employment are gradual when AI displaces workers within mixed human-AI firms, or sudden when AI firms outcompete human firms. We decompose wage changes into a technology effect, which changes the value of humans within existing firms, and a reorganization effect as firms adjust size and composition. Reorganization can reverse the technology effect on wages.

About this publication

Industry report. An industry or consultancy report — produced outside academic peer review.

Published: 2026 (recently)
Citations: Not recorded for this source

Alex Imas, Andrew Koh signed the wemustactnow.ai letter — part of why this paper is in the collection.