The Challenges and Limitations of Artificial Intelligence Adoption in Small and Medium-Sized Enterprises

Abstract

The study investigates the challenges and limitations of Artificial Intelligence (AI) adoption among small and medium-sized enterprises (SMEs) and its impact on operational efficiency. Global economies mostly rely on SMEs. However, these enterprises face multiple adoption obstacles due to monetary restrictions, lack of technological skills, data requirements, human skepticism, and restricted AI solutions. Research data from 150 representative SMEs operating in various fields demonstrates which constraints shape their AI adoption assessments. Analysis of SMEs shows their moderate mutual agreement about financial and data-related hurdles creates no statistically relevant impact on their observed operational advantages. Research indicates that Small and Medium Enterprises solve obstacles by utilizing cost-effective Artificial Intelligence technologies and cooperation from external parties. The study highlights essential requirements for personalized intervention methods, including state incentives, worker training initiatives, and straightforward AI systems for proper SME service. The research finds that SME organizations succeed at AI implementation. However, future research needs to address industry-based AI barriers, leadership patterns, and collaborative measures to create broad AI adoption strategies. The research leads to practical steps that policymakers, AI solution providers, and SME leaders can implement to integrate AI, resulting in better innovation and competitiveness for SMEs.