Agency-Driven Labor Theory: A Framework for Understanding Human Work in the AI Age

TL;DR

This paper proposes Agency-Driven Labor Theory (ADLT), a new framework emphasizing human agency as the core source of labor value in AI-augmented workplaces, with implications for job design and policy.

Contribution

It introduces a mathematical model linking human agency to labor value, expanding traditional labor theories to include strategic judgment and system design in AI environments.

Findings

ADLT quantifies labor value based on agency quality and outcomes.

The framework guides organizational strategies for AI integration.

Implications for job design and labor market policies.

Abstract

This paper introduces Agency-Driven Labor Theory as a new theoretical framework for understanding human work in AI-augmented environments. While traditional labor theories have focused primarily on task execution and labor time, ADLT proposes that human labor value is increasingly derived from agency - the capacity to make informed judgments, provide strategic direction, and design operational frameworks for AI systems. The paper presents a mathematical framework expressing labor value as a function of agency quality, direction effectiveness, and outcomes, providing a quantifiable approach to analyzing human value creation in AI-augmented workplaces. Drawing on recent work in organizational economics and knowledge worker productivity, ADLT explains how human workers create value by orchestrating complex systems that combine human and artificial intelligence. The theory has significant implications for job design, compensation structures, professional development, and labor market dynamics. Through applications across various sectors, the paper demonstrates how ADLT can guide organizations in managing the transition to AI-augmented operations while maximizing human value creation. The framework provides practical tools for policymakers and educational institutions as they prepare workers for a labor market where value creation increasingly centers on agency and direction rather than execution.