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Principal Workers: Orchestrating AI Agents Improves Productivity

Year: 2026

Type: article

Abstract: For the artificial intelligence (AI) economy, we propose a principal worker model where each knowledge worker is both a task architect and an AI agent orchestrator. As task architect, the worker divides each task into subtasks and delegates some to AI agents. As agent orchestrator, the worker optimizes outputs from AI agents and synthesizes all outputs into a coherent deliverable. Workers who augment themselves with AI agents produce more and earn more. To reap productivity gains, organizations must implement policy changes on how they develop workers and incentivize them to use AI effectively.

Source: California Management Review

DOI: 10.1177/00081256261470827

Authors: Teck-Hua Ho, Catherine Yeung

Institutions: Nanyang Technological University, AI Singapore, Chinese University of Hong Kong

Language: English

Topic: AI and HR Technologies

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Decent work and economic growth

Open Access status: hybrid

Estimated APC paid: $3,900