AI Adoption in SME Financial Practices: A Paradigm Shift for Risk Mitigation, Cash Flow Optimization, and Sustainable Growth

Small and medium-sized enterprises (SMEs), despite constituting over 90% of global businesses, face persistent financial management challenges, including resource constraints, operational inefficiencies, and vulnerability to market volatility. While artificial intelligence (AI) offers transformative potential for risk mitigation, cash flow optimization, and sustainable growth, existing research disproportionately focuses on large enterprises, leaving SME-specific barriers and opportunities underexplored. This study addresses this gap by examining how AI adoption reshapes SME financial practices, with a dual focus on technological empowerment and systemic inequities. Employing a mixed-methods design, the research synthesizes findings from a systematic literature review (2020–2024) and primary data collected via surveys (n=300 SMEs) and interviews (n=30 managers) across North America, Europe, and Asia-Pacific. Quantitative analysis using structural equation modelling (SEM) and qualitative thematic analysis reveals that AI tools like ChatGPT and feedforward neural networks enhance risk assessment accuracy by 30–40% and reduce fraud detection time by 90%, while blockchain-AI integrations improve transactional transparency. However, data scarcity (reported by 68% of SMEs), infrastructure costs (57%), and skill gaps (63%) disproportionately hinder adoption, particularly in emerging markets. Theoretically, the study extends the Technology–Organization–Environment (TOE) model by emphasizing dynamic organizational learning and ethical governance as critical drivers of AI integration. Practically, it advocates for phased AI implementation strategies, starting with low-cost tools (e.g., generative AI for forecasting) and progressing to advanced systems, complemented by stakeholder training and policy interventions to subsidize infrastructure. The findings underscore AI’s dual role as an enabler of financial resilience and a catalyst for structural inequities, urging policymakers to establish regulatory sandboxes and ethical frameworks to democratize access. This research bridges theoretical gaps in SME-centric AI adoption literature while offering actionable pathways for SMEs to harness AI’s potential, fostering equitable and sustainable growth in the digital economy.