AI Economics: Annotation Economics — Crowdsourcing vs Expert Labeling in Enterprise AI

Zenodo (CERN European Organization for Nuclear Research) 2026 Preprint Open access

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Authors: Oleh Ivchenko
DOI: 10.5281/zenodo.18625149
Cited by: 0

Abstract

Data annotation represents one of the most underestimated cost centers in enterprise AI development. This article presents a comprehensive economic framework for annotation decision-making, analyzing the crowdsourcing versus expert labeling dichotomy through total cost of ownership, quality-adjusted returns, and strategic implications. Drawing on case studies from healthcare, autonomous vehicles, financial services, and manufacturing.

Fields of Study & Subjects

Mobile Crowdsensing and Crowdsourcing Artificial Intelligence Applications Machine Learning and Data Classification

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 February 2026
Language
EN
Document type
Preprint