---
id: "prereq-task-based-labor-model"
type: "prereq"
source_timestamps: ["¶8", "¶9"]
tags: ["labor-economics", "mental-models"]
related: ["framework-task-categorization-scoring"]
reason: "Required to understand how the researchers categorized 19,000 tasks to determine the augmentation score of 900 occupations."
sources: ["reskilling"]
sourceVaultSlug: "hbr-seg-reskilling"
originDay: 10
articleStem: "hbr-edu-35-ai-changing-labor-market"
sourceUrl: "https://hbr.org/2026/03/research-how-ai-is-changing-the-labor-market"
sourceTitle: "Research: How AI Is Changing the Labor Market"
---
# Task-Based Model of Labor

**Why you need this:** Required to understand how the researchers categorized ~19,000 tasks to determine the [[concept-augmentation-score|augmentation score]] of ~900 occupations.

To understand the methodology and findings, one must accept that **jobs are not monolithic entities but bundles of distinct tasks**. Generative AI does not typically automate an entire job at once; it automates *specific tasks within* that job. The **ratio of automatable tasks to non-automatable tasks** determines whether a job is displaced ([[concept-ai-automation-displacement]]) or augmented ([[concept-ai-augmentation-complementarity]]). This mental model is the foundation of the [[framework-task-categorization-scoring|task-categorization methodology]] and the [[concept-augmentation-score]].

**Enrichment note:** This is the task-based approach to technological change and labor rooted in the work of David Autor and others; jobs are bundles of tasks, some automated and some complemented by technology. Srinivasan et al.'s framework ([[entity-displacement-or-complementarity-paper]]) and the World Bank ([[evidence-world-bank-labor-demand]]) both follow this established paradigm.