# Shifting Work Patterns with Generative AI

arXiv: https://arxiv.org/abs/2504.11436 · HTML: https://mlsanity.com/paper/2504.11436/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 19 references that are in the map.
- First posted on arXiv 15 Apr 2025.

## Builds on (most cited first, 2 of 2)

- [A Test for Evaluating Performance in Human-Computer Systems](https://mlsanity.com/paper/2206.12390/) (2022)
- [Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India](https://mlsanity.com/paper/1712.04802/) (2017)

## Built on by (most cited first, 5 of 5)

- [Technological folie `a deux: Feedback Loops Between AI Chatbots and Mental Illness](https://mlsanity.com/paper/2507.19218/) (2025)
- [When Do AI Gains Become Broadly Shareable? A Policy Threshold for AI-Driven Automation](https://mlsanity.com/paper/2505.18687/) (2025)
- [Generative AI in Saudi Arabia: A National Survey of Adoption, Risks, and Public Perceptions](https://mlsanity.com/paper/2601.18234/) (2026)
- [How Early Adopters Used Generative AI Worldwide: Variation by Country Income and Language](https://mlsanity.com/paper/2605.30685/) (2026)
- [Governing Generative AI Across Financial Institutions: A Framework for Generative AI Risk Control](https://mlsanity.com/paper/2607.04103/) (2026)

## Abstract (arXiv)

We present evidence from a field experiment across 66 firms and 7,137 knowledge workers. Workers were randomly selected to access a generative AI tool integrated into applications they already used at work for email, meetings, and writing. In the second half of the 6-month experiment, the 80% of treated workers who used this tool spent two fewer hours on email each week and reduced their time working outside of regular hours. Apart from these individual time savings, we do not detect shifts in the quantity or composition of workers' tasks resulting from individual-level AI provision.