The effect of Generative AI on Early Stage Business Ideas: An Experimental Approach

Last registered on February 20, 2025
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Pre-Trial

Trial Information

General Information

Title
The effect of Generative AI on Early Stage Business Ideas: An Experimental Approach
RCT ID
AEARCTR-0014305
Initial registration date
February 19, 2025

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
February 20, 2025, 6:03 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
Valentina Contreras
Affiliation
Pontificia Universidad Católica de Chile
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Other Primary Investigator(s)

PI Name
Michael Leatherbee
PI Affiliation
Pontificia Universidad Católica de Chile
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Additional Trial Information

Status
In development
Start date
2024-04-26
End date
2027-02-01
Keywords
Firms & Productivity, Other
Additional Keywords
Entrepreneurship, Artificial intelligence
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Entrepreneurship is one of the main drivers of a country's economic development. Therefore, understanding its motivations, implications, and especially the factors that affect it is highly relevant. On the other hand, in recent years, artificial intelligence (AI) has made significant strides in many fields of application, leading to evaluations of its impact on productivity and industry. In particular, this research focuses on studying the use of generative AI within the context of entrepreneurship. Through a randomized controlled trial (among engineering students who are creating new ventures), we estimate the causal effect of AI usage in the early stages of business idea development. The aim is to explore the potential effects of using AI's natural language processing on entrepreneurs' discovery of novel business ideas.
External Link(s)

Registration Citation

Citation
Contreras, Valentina and Michael Leatherbee. 2025. "The effect of Generative AI on Early Stage Business Ideas: An Experimental Approach." AEA RCT Registry. February 20. https://doi.org/10.1257/rct.14305-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The study subjects, students tasked with developing a high-potential business idea, are randomly divided into a control group and a treatment group. The treatment group will receive guidance on how to effectively use artificial intelligence for the early stages of their business idea development. This includes training on executing prompts that enable them to use AI to explore ideas, identify market opportunities, and develop an early-stage value proposition that is attractive to the market. Meanwhile, the control group receives education in a traditional format regarding the use of tools that enhance their creativity and ability to identify problems to solve.
Intervention Start Date
2024-08-01
Intervention End Date
2026-08-01

Primary Outcomes

Primary Outcomes (end points)
- External judges' grade of the startup's problem relevance
- External judges' grade of the startup's value proposition
- Course grade
- Participation in demo-day
- Wining the demo-day
- Likelihood of founding
- Capital or grants raised
- Jobs created
- Market traction
Primary Outcomes (explanation)
- External judges' grade of the startup's problem relevance: This item evaluates the identification, definition, and relevance of the problem on a scale from 1 to 7 (Chilean grading system).
- External judges' grade of the startup's value proposition: This item assesses the project's value proposition, considering the problem-solution fit and the innovation component, on a scale from 1 to 7 (Chilean grading system).
- Course grade: The final grade for the course will incorporate, in addition to the previously mentioned aspects, factors such as the scalability and economic viability of the project, as well as the development of a prototype, on a scale from 1 to 7 (Chilean grading system).
- Participation in demo-day: A binary variable indicating whether the group's business was selected for the demo day instance. It takes a value of 1 if they participated and 0 if they did not.
- Wining the demo-day: A binary variable indicating whether the group won the demo day, only to those who participated. It takes a value of 1 if they won and 0 if they did not.
- Likelihood of founding: The probability that a group establishes a startup or formally initiates a venture.
- Capital or grants raised: The total financial resources secured by a participant through investments or funding programs.
- Jobs created. The number of employment opportunities generated as a direct result of the participant's entrepreneurial activity.
- Market traction: Evidence of customer interest or demand or engagement with the participant's product or service.

Secondary Outcomes

Secondary Outcomes (end points)
- Prior academic performance
Secondary Outcomes (explanation)
- Prior academic performance: We will use prior student performance upon entering the course as a heterogeneity variable. Students with higher prior academic performance may exhibit different outcomes compared to those below the average.

Experimental Design

Experimental Design
Groups of engineering students of a entrepreneurship course will be randomly assigned to two groups. The treatment group will receive a specific intervention encouraging the use of a specific technological tool. Subsequent performance will be compared between both groups.
Experimental Design Details
Not available
Randomization Method
The randomization was done by a computer software.
Randomization Unit
The randomisation is a group level.
Each group is composed by approximately 4 or 5 individuals.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
The experiment will involve at least 130 groups.
Sample size: planned number of observations
The experiment will involve at least 130 groups.
Sample size (or number of clusters) by treatment arms
Half of the groups will be assigned to each of the two treatment arms.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Comité Ético Científico en Ciencias Sociales, Artes y Humanidades de la Pontificia Universidad Católica de Chile
IRB Approval Date
2024-04-26
IRB Approval Number
230418008
Analysis Plan