AI-driven digital transformation in MSMEs : Modeling adoption, readiness, and implementation challenges
*Ronak R. ModiCorresponding authorronakmaniyarpatan@gmail.comDepartment of Business ManagementFaculty of Management StudiesSmt. S. B. Patel Institute of Business Management, Sankalchand Patel UniversityVisnagar, Gujarat, 384315, India0000-0002-3598-8034View full profile → , Parth M. Modiparthmodi24@yahoo.comDepartment of Commerce & ManagementSevantilal Kantilal School of Business Management (SKSBM)Hemchandracharya North Gujarat UniversityPatan, Gujarat, 384265, India0009-0007-2206-5576View full profile → , Rajesh Patelcbrathodmba_spce@spu.ac.inDepartment of Business ManagementFaculty of Management StudiesSankalchand Patel College of Engineering, Sankalchand Patel UniversityVisnagar, Gujarat, 384315, IndiaView full profile → , Chirag Rasikbhai Patelcrpspce@gmail.comDepartment of Business ManagementFaculty of Management StudiesSankalchand Patel College of Engineering, Sankalchand Patel UniversityVisnagar, Gujarat, 384315, India0000-0003-4788-0749View full profile → , Miteshkumar Babuji Thakormiteshthakor25@gmail.comDepartment of Business ManagementFaculty of Management StudiesSmt. S. B. Patel Institute of Business Management, Sankalchand Patel UniversityVisnagar, Gujarat, 384315, India0000-0002-6214-7687View full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Jun 2026
- Published Online:
- 30 Sep 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2443
- Pages:
- 3463–3472
Abstract
Artificial Intelligence (AI) can improve MSME efficiency, productivity, and decision-making. However, AI adoption among Indian MSMEs remains limited due to low awareness and implementation challenges. This study examines AI adoption in Gujarat’s MSMEs, focusing on AI awareness, perceived benefits, and adoption challenges. Using a quantitative approach, data were collected from MSME owners and managers through structured questionnaires and analysed using descriptive statistics and Structural Equation Modeling (SEM). The study provides empirical insights into AI adoption factors and offers implications for policymakers, business leaders, and technology providers to support effective AI integration and overcome adoption barriers.
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References
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