Remote Labor Index: Measuring AI Automation of Remote Work
Machine Learning
2025-10-31 v1 Artificial Intelligence
Computation and Language
Abstract
AIs have made rapid progress on research-oriented benchmarks of knowledge and reasoning, but it remains unclear how these gains translate into economic value and automation. To measure this, we introduce the Remote Labor Index (RLI), a broadly multi-sector benchmark comprising real-world, economically valuable projects designed to evaluate end-to-end agent performance in practical settings. AI agents perform near the floor on RLI, with the highest-performing agent achieving an automation rate of 2.5%. These results help ground discussions of AI automation in empirical evidence, setting a common basis for tracking AI impacts and enabling stakeholders to proactively navigate AI-driven labor automation.
Cite
@article{arxiv.2510.26787,
title = {Remote Labor Index: Measuring AI Automation of Remote Work},
author = {Mantas Mazeika and Alice Gatti and Cristina Menghini and Udari Madhushani Sehwag and Shivam Singhal and Yury Orlovskiy and Steven Basart and Manasi Sharma and Denis Peskoff and Elaine Lau and Jaehyuk Lim and Lachlan Carroll and Alice Blair and Vinaya Sivakumar and Sumana Basu and Brad Kenstler and Yuntao Ma and Julian Michael and Xiaoke Li and Oliver Ingebretsen and Aditya Mehta and Jean Mottola and John Teichmann and Kevin Yu and Zaina Shaik and Adam Khoja and Richard Ren and Jason Hausenloy and Long Phan and Ye Htet and Ankit Aich and Tahseen Rabbani and Vivswan Shah and Andriy Novykov and Felix Binder and Kirill Chugunov and Luis Ramirez and Matias Geralnik and Hernán Mesura and Dean Lee and Ed-Yeremai Hernandez Cardona and Annette Diamond and Summer Yue and Alexandr Wang and Bing Liu and Ernesto Hernandez and Dan Hendrycks},
journal= {arXiv preprint arXiv:2510.26787},
year = {2025}
}
Comments
Website: https://www.remotelabor.ai