Drivers, Barriers and Business Outcomes of Artificial Intelligence Adoption in SMEs: A Systematic Literature Review and Contextual Framework for Bangladesh

Abstract

Artificial intelligence (AI) is increasingly presented as a route through which small and medium-sized enterprises (SMEs) can overcome information, capability and scale disadvantages. Yet adoption remains uneven, especially in emerging economies where finance, skills, infrastructure and institutional assurance are constrained. This systematic literature review investigates four questions: which technological, organisational and environmental conditions drive AI adoption; which barriers interrupt implementation; which business outcomes are reported; and how the international evidence can be translated into an actionable framework for Bangladesh. Following PRISMA 2020 principles, sixteen structured OpenAlex search routes retrieved 800 records. After removing 320 duplicates, 480 unique records were screened. A relevance pre-screen excluded 309 records; 171 database reports and 14 supplementary reports were assessed. Forty primary empirical studies were included, while eight reviews or conceptual sources were retained separately for theoretical triangulation. Study coding was organised through the Technology–Organization–Environment (TOE) framework and interpreted with resource-based and dynamic-capability perspectives. Human capital and employee skills were the most frequent driver (21 studies), followed by top-management support (12), ecosystem support (11), relative advantage (9) and digital/data readiness (9). The strongest explicit barriers concerned privacy, security, ethics and distrust (7), high cost and limited finance (6), institutional or regulatory gaps (5), and implementation complexity (4). Reported outcomes clustered around workforce learning (14), decision quality and agility (8), operational productivity (8), competitive advantage (8), revenue performance (7) and sustainability (6). However, nineteen studies relied on SEM or PLS-SEM, most evidence was cross-sectional, and only two primary studies directly examined Bangladesh. The paper therefore proposes a capability-gated pathway—diagnose, pilot, integrate, govern and scale—supported by Bangla-ready tools, shared training, affordable finance, vendor assurance and proportionate governance. The review concludes that AI produces business value not as a stand-alone purchase but when complementary skills, data routines, leadership and institutional supports are deliberately assembled.