AI Adoption: Opportunities and Challenges for Small and Medium Businesses

Last registered on December 15, 2025
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Pre-Trial

Trial Information

General Information

Title
AI Adoption: Opportunities and Challenges for Small and Medium Businesses
RCT ID
AEARCTR-0015262
Initial registration date
January 23, 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
January 27, 2025, 10:00 AM EST

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

Last updated
December 15, 2025, 3:51 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Name
Christina Langer
Affiliation
Stanford University
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Other Primary Investigator(s)

PI Name
Angela Aristidou
PI Affiliation
UCL School of Management
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PI Name
Erik Brynjolfsson
PI Affiliation
Stanford University
PI Name
Bart Vanneste
PI Affiliation
UCL School of Management
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Additional Trial Information

Status
In development
Start date
2025-01-30
End date
2027-12-31
Keywords
Firms & Productivity
Additional Keywords
New technologies, Artificial Intelligence, AI adoption, SMEs, workshops, consulting, GenAI tools
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The impressive rise of Artificial Intelligence (AI) has sparked significant attention and awe but also concerns on what these new technologies may mean for the economy and society. Especially small and medium enterprises (SMEs) exhibit room to grow regarding AI adoption. However, less is known about the concerns SMEs have when it comes to AI adoption, about suitable interventions to help them overcome these barriers, and the impact of GenAI adoption on these businesses.

We aim to study the impact of interventions designed to increase AI adoption in the population of SMEs in the UK. This will give us the opportunity to analyze the effectiveness of different interventions targeted at increasing UK SMEs' AI adoption in a real-world scenario.
External Link(s)

Registration Citation

Citation
Aristidou, Angela et al. 2025. "AI Adoption: Opportunities and Challenges for Small and Medium Businesses." AEA RCT Registry. December 15. https://doi.org/10.1257/rct.15262-2.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-12-16
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
1. AI adoption metrics (Number of AI tools implemented, percentage of employees using AI, number of business functions using AI; self-reported survey questions)
2. Business performance metrics (revenue, new products or services, number of employees; self-reported survey questions and administrative data from Companies House)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1. Implementation quality (AI action plan completion rate, percentage of staff trained in AI tool usage, implementation timeline achievement; self-reported survey questions)
2. Organizational development (AI readiness scores, data infrastructure development, staff attitude, implementation barriers; self-reported survey questions)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study employs an RCT with firm-level randomization. 300-400 SMEs will participate in six half-day AI adoption workshops that take place between Dec 16 and Dec 18, 2025 (around 50 SMEs per workshop). After the workshops, we will randomize participants to the following treatment arms:

- Control: workshop only
- Treatment arm 1: workshop + free pro GenAI tool access for one year
- Treatment arm 2: workshop + free pro GenAI tool access for one year + free AI consulting for nine months

The study period spans 1 year with multiple surveys.

Experimental Design Details
Not available
Randomization Method
Randomization will be done in office by a computer.
Randomization Unit
Firm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
300-400 firms
Sample size: planned number of observations
300-400 firms
Sample size (or number of clusters) by treatment arms
We plan six workshops with around 50 firms each (300-400 firms in total). We will get sign-up lists for each workshop and randomly assign signed up firms that have completed the baseline survey to one of the two treatment arms or control (workshop only). We expect around 200 SMEs to be in the control group, 50 SMEs in treatment arm 1 and 50 SMEs in treatment arm 2. This allocation was determined by available intervention resources.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
UCL LREC
IRB Approval Date
2024-11-21
IRB Approval Number
UCLSOM0197
Analysis Plan