AI Adoption in Small and Medium Enterprises (SMEs) in North India: Challenges, Business Performance, and Psychological Barriers

Abstract

 The rapid advancement of artificial intelligence (AI) offers transformative potential for small and medium enterprises (SMEs), yet adoption rates in emerging economies like India remain modest, particularly among firms in North India. This study examines the interplay between technological, organizational, and psychological factors influencing AI adoption in SMEs located in the Chandigarh tricity region and surrounding areas of Punjab and Haryana. Drawing on the Technology Acceptance Model (TAM) and the Job Demands-Resources (JD-R) model, the research investigates how perceived usefulness, ease of use, top management support, and resource constraints shape adoption decisions, while psychological barriers such as technostress, fear of job displacement, and resistance to change affect both implementation and employee well-being. A cross-sectional survey was conducted with 312 owners, managers, and employees from 85 SMEs engaged in manufacturing, services, and IT-enabled sectors. Data were analysed using structural equation modelling (SEM) to test hypothesized relationships. Results indicate that while relative advantage and management support positively predict AI adoption intentions, psychological barriers, particularly technostress and perceived job insecurity significantly moderate the link between adoption and business performance outcomes, including operational efficiency, cost reduction, and customer engagement. SMEs that successfully addressed psychological resistance through targeted training and clear communication reported higher performance gains. The findings highlight the dual nature of AI implementation: it can enhance productivity when psychological resources are strengthened, yet it risks increasing exhaustion and work-family conflict when demands are unmanaged. This study contributes to interdisciplinary scholarship by integrating management and psychological perspectives on digital transformation in resource-constrained settings. Practical implications for SME leaders and policymakers include the need for localized awareness programs, affordable AI tools, and supportive change management strategies to accelerate responsible adoption in North India.