Artificial Intelligence Adoption for Sustainable Development in SMEs: Challenges, Strategic Pathways, and Lessons for Developing Economies
Domaine:
socioeconomicType de record:
This study critically examines the adoption of artificial intelligence (AI) by small and medium-sized
enterprises (SMEs) in developing economies, using Botswana as a primary context. Employing a
structured narrative literature review, this study synthesizes existing empirical evidence, theoretical
frameworks, and policy analyses to elucidate the multifaceted enablers and barriers influencing AI
integration within resource-constrained SME environments. Drawing on the Resource-Based View
(RBV), Dynamic Capabilities (DC), Technology-Organization-Environment (TOE), and Diffusion of
Innovation (DOI) frameworks, this study highlights AI’s role in enhancing operational efficiency, customer
personalization, and innovation capacity, thereby fostering competitive advantage and contributing to
sustainable development. Key enabling factors include supportive government policies, innovation
ecosystems, financial access and external market pressures. Critical constraints include skill shortages,
infrastructural deficits, financial challenges, and fragmented data governance. This analysis advocates
for strategic, phased AI adoption approaches, emphasizing incremental capability development,
ecosystem collaboration, targeted human capital investment, infrastructure enhancement, scalable
financing models, and ultimately, sustainable outcomes. The policy implications underscore the need
for adaptive regulatory frameworks, inclusive financial mechanisms, and robust data governance to
cultivate an environment that enables inclusive and sustainable AI adoption. This integrated analysis
offers actionable insights for policymakers, practitioners, and SME stakeholders to accelerate inclusive
and sustainable digital transformation and economic diversification in developing contexts