Impact of AI-Blockchain Adoption on Annual Revenue Growth: An Empirical Analysis of Small and Medium-sized Enterprises in the United States

Abstract

United States economy relies heavily on the contributions of Small and Medium-sized Enterprises (SMEs) which play a big role in job creation, innovation, and overall economic growth. While technology adoption has long been considered a key factor in business performance, the emergence of Artificial Intelligence (AI) and blockchain technologies offers new avenues for operational efficiency and growth. This research aimed to identify the determinants of annual revenue growth among SMEs in the United States, with a particular focus on the impact of AI-based blockchain adoption on revenue growth. Using data from 422 SMEs surveyed in 2020, multiple statistical and machine learning models, including Multiple Regression, Multi-layer Perceptrons, and Gradient Boosting Machines, were employed to analyze the relationship between various independent variables and annual revenue growth. The study found a statistically significant relationship between the adoption of AI-Blockchain and revenue growth. The findings suggest that the adoption the technology could provide SMEs a competitive advantage. Additionally, the variables business age, owner experience, and owner education were significantly correlated with annual revenue growth. however, variables such as family business, owner age, and owner gender were not statistically significant, raising questions about the effectiveness of demographic-focused policies grants for revenue generation among SMEs. Market competition and road proximity exhibited inconsistent significance depending on the analytical model, suggesting their impact may vary by industry or geography. Funding source and exporting status also showed mixed results across different models. Notably, adoption of AI-Blockchain had low feature importance in machine learning models, despite its statistical significance in traditional models. These technologies are still in a nascent phase, undergoing rapid developments and improvements. As a result, the broader economic and operational implications for SMEs may not be entirely evident yet. This early stage of technology could account for why the technology shows statistical significance in traditional models but low feature-importance in machine learning models, which often capture more complex interactions. The findings of the study cloud be relevant for SMEs, especially those that are considering substantial investments in AI-based blockchain technologies.