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Abstract
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Before
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 know about the concerns SMEs have when it comes to AI adoption as well as about suitable interventions
to help them overcome these barriers.
We aim to study the impact of a designed intervention to increase AI adoption in the population of SMEs in the UK. This will give us the opportunity to analyze the effectiveness of a intervention targeted at increasing UK SMEs' AI adoption in a real world scenario.
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After
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.
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Trial End Date
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December 31, 2026
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After
December 31, 2027
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Last Published
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January 27, 2025 10:00 AM
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After
December 15, 2025 03:51 PM
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Intervention Start Date
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January 30, 2025
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December 16, 2025
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Intervention End Date
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December 31, 2025
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December 31, 2026
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Primary Outcomes (End Points)
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1. AI adoption metrics (Number of AI tools implemented, percentage of employees using AI, number of business functions using AI)
2. Business performance metrics (revenue, costs, productivity)
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After
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)
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Experimental Design (Public)
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Before
The study employs a randomized controlled trial with firm-level randomization. We will use a staggered treatment design with rolling workshop enrollment, targeting 500 firms across 10-12 workshops (40-50 firms per workshop). The study period spans 1 year with multiple surveys.
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After
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.
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Randomization Method
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Randomization will be done in office by a computer. Treatment timing (workshop participation) will be randomly assigned with rolling sign-up of firms for workshops.
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Randomization will be done in office by a computer.
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Planned Number of Clusters
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500 firms
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300-400 firms
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Planned Number of Observations
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500 firms
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300-400 firms
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Sample size (or number of clusters) by treatment arms
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Before
We plan with 10-12 workshops with 40-50 firms each (500 firms in total). We will get sign-up lists for each workshop and randomly assign signed up firms to either treatment (workshop slot) or control (waitlist). Waitlisted firms will act as control and will get the workshop later. With a sign-up rate of 100 firms per workshop, we expect about 40 firms in the treatment group and 40 firms in the control group per workshop, accounting for no-shows.
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After
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.
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Additional Keyword(s)
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AI adoption, SMEs, workshops
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New technologies, Artificial Intelligence, AI adoption, SMEs, workshops, consulting, GenAI tools
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Intervention (Hidden)
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Before
The intervention consists of a half-day AI adoption workshop facilitated by AI experts that includes:
• Keynote presentation on AI applications in business
• Two facilitated workshop sessions focusing on discovery and implementation planning
• Applied use case presentation
• Action planning activities with concrete next steps
We will gather baseline data from treatment firms (workshop) and control firms (waitlist), immediate post-workshop survey from the treatment firms and follow-up surveys from treatment and control firms to evaluate the workshop's effectiveness in multiple dimensions specified below.
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After
We will conduct six half-day AI adoption workshops between Dec 16 and Dec 18, 2025, that help SME leaders to develop an AI action plan for their business. They will identify their current key challenge, how AI can help tackle this challenge, and then define a feasible, measurable AI action plan.
After the workshop, we will randomize 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
to subsets of SMEs. In the following we will refer to this section here as the “treatment arms.”
We will gather data through a baseline survey pre-workshop, an immediate post-workshop survey capturing their action plans, and follow-up surveys (3, 6 ,9, 12 months after the workshops) from all SMEs participating in the workshops, to evaluate the impact of the interventions in multiple dimensions specified below. AI tool providers will report aggregate usage data at the firm level (e.g., number of licenses activated). AI consulting partners will report which firms engaged with consulting services and the extent of engagement (e.g., number of sessions attended).
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Secondary Outcomes (End Points)
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Before
1. Implementation quality (AI action plan completion rate, percentage of staff trained in AI tool usage, implementation timeline achievement, staff satisfaction with AI tools)
2. Organizational development (AI readiness scores, data infrastructure development, staff attitude, implementation barriers)
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After
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)
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