ADOPTION OF AI AND MACHINE LEARNING FOR STRATEGIC DECISION-MAKING IN MSMES: EVIDENCE FROM RAJASTHAN
Micro, Small, and Medium Enterprises (MSMEs) are vital to Rajasthan’s economy, contributing significantly to employment and industrial output. This study examines the adoption of Artificial Intelligence (AI) and Machine Learning (ML) in strategic decision-making among 357 MSMEs in Jaipur District, Rajasthan, using a quantitative survey. Results indicate that only 27.5% of MSMEs adopt AI/ML, with higher adoption in services (34.7%) and manufacturing (30.9%) compared to tourism/handicrafts (20.4%). Small and medium enterprises (mean adoption score = 3.12) outperform micro-enterprises (2.45, p < 0.01), and sectoral differences are significant (F = 5.89, p < 0.003). AI/ML adoption enhances decision accuracy (mean = 3.85 for adopters) and cost efficiency (mean = 3.65), but barriers such as high costs (68% rating 4/5) and skill gaps (55%) limit uptake, particularly among microenterprises (75% non-adopters). The study highlights the need for cost-effective AI solutions, skill development, and infrastructure support to bridge the adoption gap. Findings offer empirical evidence from a developing economy, emphasizing Rajasthan’s unique challenges and opportunities. Recommendations include subsidized AI tools and sector-specific training to empower MSMEs, fostering competitiveness and growth.
Authors
- DR KAMAL KANT
Institutions
- Central University of Rajasthan (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-12-22
- DOI
- https://doi.org/10.5281/zenodo.18020867
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00