The Demand for Artificial Intelligence Ability: Evidence from a Job-Application Experiment

Last registered on January 28, 2026
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Pre-Trial

Trial Information

General Information

Title
The Demand for Artificial Intelligence Ability: Evidence from a Job-Application Experiment
RCT ID
AEARCTR-0017767
Initial registration date
January 26, 2026

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 28, 2026, 7:47 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name
Yican Liu
Affiliation
The University of Hong Kong
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Other Primary Investigator(s)

PI Name
Yiming Cao
PI Affiliation
The University of Hong Kong
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PI Name
Tian Chen
PI Affiliation
Washington University in St. Louis
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PI Name
Shaokai Ding
PI Affiliation
The University of Manchester
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PI Name
Guillermo Rosas
PI Affiliation
Rice University
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Additional Trial Information

Status
In development
Start date
2026-02-01
End date
2026-08-31
Keywords
Behavior, Firms & Productivity, Labor
Additional Keywords
Labor market; Artificial intelligence; Job Application
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We study whether the demand for artificial intelligence–related capabilities influences firms’ hiring policies. To examine this, we conduct a job-application experiment in which we create fictitious applications tailored to different job positions. We then track the callback rates of these applications over several months. This experimental design allows us to estimate how firms respond to technological change associated with advancements in artificial intelligence.
External Link(s)

Registration Citation

Citation
Cao, Yiming et al. 2026. "The Demand for Artificial Intelligence Ability: Evidence from a Job-Application Experiment." AEA RCT Registry. January 28. https://doi.org/10.1257/rct.17767-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-02-01
Intervention End Date
2026-08-31

Primary Outcomes

Primary Outcomes (end points)
The call back rate of each job application.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We implement a job-application experiment by submitting fictitious applications to a variety of job positions and monitoring callback rates over several months. This methodology is commenly used in some other published economic papers.
Experimental Design Details
Not available
Randomization Method
This randomization is done in office by a computer.
Randomization Unit
By job application.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
50,000 job applications.
Sample size: planned number of observations
50,000 job applications.
Sample size (or number of clusters) by treatment arms
50,000 job applications.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Human Research Ethics of the University of Hong Kong
IRB Approval Date
2025-07-31
IRB Approval Number
EA250432
Analysis Plan