Teaming Up with AI: Coordination and Cooperation

2026-07-03

AI Summary

This study addresses how to achieve efficient human–AI collaboration in the workplace so as to augment rather than replace human labor and maximize economic value. The work proposes a two-tier framework that integrates algorithmic coordination with contractual incentive mechanisms: at the upper level, algorithmic task scheduling manages interdependencies between humans and AI agents, while at the lower level, an incentive-compatible mechanism grounded in contract theory aligns their objectives. By synthesizing insights from theoretical computer science and mechanism design, this approach offers a scalable theoretical foundation for human–AI collaborative systems, enhancing collective productivity and coordination, and providing institutional support for the emerging AI labor market.

Abstract

Successful diffusion of AI in the workforce hinges on the economic value that AI brings to human endeavors. Bringing AI into the workforce is more than deploying a powerful new technology -- it is launching a new form of collaboration. Each human worker is now endowed with a team of AI agents; work can be delegated to these agents, and the role of the human shifts towards managing and monitoring. How can we maximize the economic value from collaboration with AI in the workforce? How can we make it a "true" collaboration that empowers human workers rather than replacing them? We take an approach that combines the fields of theoretical computer science and economics, highlighting the potential of algorithmic tools grounded in economic principles to improve the effectiveness of human-AI collective work. We consider two tiers of tools: (1) tools for better coordination, via algorithmic management of interdependencies; (2) tools for better cooperation, via contractual incentive alignment. We show how a principled approach based on algorithmic and economic research enhances both coordination and cooperation, charting a pathway for future research to inform AI markets.

Problem

• human-AI collaboration
• economic value
• workforce integration
• AI empowerment
• coordination and cooperation

Innovation

• human-AI collaboration
• algorithmic coordination
• incentive alignment
• economic principles
• AI workforce integration