ResearchAI/TechLocal ImpactLead Researcher

Small Business AI Adoption and Abandonment Study

Faculty-mentored study on small-business AI adoption and abandonment with Dr. Murugan Anandarajan of Drexel LeBow.

The problem

Small businesses hear constant promises about AI, but there is limited primary data on what they actually adopt, what they abandon, and whether the time and software costs create a useful return.

The approach

01Interview small business owners about current and past AI use
02Transcribe and code sessions for cost, setup time, training, abandoned tools, and perceived ROI
03Compare adoption patterns across business types and team sizes
04Synthesize findings into an accessible executive summary and preprint-style paper

Tools & stack

Owner interviewsSurvey instrument and response collectionTranscript codingSpreadsheet analysisResearch writing

Results

→ 7 interviews and 38 survey responses as of July 27, 2026
→ 4 interviews with documented preliminary thematic analysis
→ Data collection ongoing toward roughly 150 survey responses
→ Faculty mentorship from Dr. Murugan Anandarajan (Drexel LeBow)
→ Prospectus and measurement plan externally reviewed by Johannes Habel (University of Houston) — an external reviewer, not a collaborator, mentor, or coauthor
→ Research in progress — not published, not Drexel-sponsored

In progressPrimary dataLead researcher

Working title

The Hidden Costs of AI Adoption in Small Businesses: Survey Evidence from Local Business Owners

This study examines how small business owners evaluate, adopt, abandon, and measure the value of AI and digital tools. It draws on in-person owner conversations, interviews, and surveys collected through local work with Digital Lift and VenoxAI.

Research questions

What makes small business owners try AI tools?
What expectations do they have before adoption?
Why do some tools get abandoned?
How do owners judge whether AI is worth the cost, time, and training?
Which barriers matter most: cost, complexity, privacy, trust, unclear ROI, staff resistance, or integration?

Variables and themes

AI tools currently used
Monthly AI and software spend
Tools tried and later abandoned
Setup time before usefulness
Staff training burden
Main adoption barriers
Hours saved or lost per week
Perceived return on investment
Industry, business size, and years in operation
Whether implementation help would increase adoption

Planned output: A public-facing executive summary and a research paper translating the findings into practical guidance for small businesses.
Current status: Data collection is in progress. If you own or operate a small business and want to participate, get in touch.

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