Harnessing AI for Sustainable Growth in MSMEs: A Comparative Study of Adoption Barriers and Performance Outcomes in Emerging Economies

Abstract

Micro, Small and Medium Enterprise (MSMEs) are significant to the emerging economies because they generate jobs, innovate and invest a lot to the GDP (Ayyagari et al., 2011). The challenges facing MSMES on scaling sustainably are however numerous due to institutional limitations in terms of financial and technological capabilities.
AI can revolutionize the MSMEs to enhance working efficiency, decision making and sustainable development through enhancing the level of resource automion in the processes, allowing the use of data to make informed insights, and aid in the optimal utilization of available resources (Bharadwaj et al., 2013).
The paper will compare the obstacles to and performance results of AI adoption of MSMEs in one of the sample of emerging economies. It examines technological, financial, organizational and cultural challenges and contribution of regulations in bringing out the key impediments to AI  implementation (Venkatesh et al., 2003; Oliveira and Martins, 2011). It also discusses the relationship between the elimination of these barriers and the improved productivity, innovation and growth in markets and sustainability effects.
The methodology used in the study combines both quantitative surveys and the qualitative interviews between the MSME owner-managers and IT specialists of countries like India, Brazil and South Africa. Statistical and thematic analysis of the data take place to determine trends as well as situation variances.
Among its most important insights they reveal that, the absence of financial resources, as well as digital proficiency, are universal barriers, but also the existence of adoptions is highly conditional on the infrastructure and the context of policies. Users of AI in MSMEs note significant efficacy and client interaction, follow development paths (Kraus et al., 2021; Dwivedi et al., 2021).